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  • Articles  (214)
  • Computational Methods, Genomics  (140)
  • Cooperatives  (74)
  • Oxford University Press  (214)
  • 1
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    A low-latency, big database system and browser for storage, querying and visualization of 3D genomic data (2015)
    Oxford University Press
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    Publication Date: 2015-09-19
    Description: Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data ( 3DBG ), and a 3D genome browser to visualize and explore 3D genome structures ( 3DGB ). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
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    Analysis of strand-specific RNA-seq data using machine learning reveals the structures of transcription units in Clostridium thermocellum (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available at https://code.google.com/p/seqtu/ . We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 3
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    A thesaurus of genetic variation for interrogation of repetitive genomic regions (2015)
    Oxford University Press
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    Publication Date: 2015-05-29
    Description: Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.
    Keywords: Computational Methods, Genomics
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    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 4
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    A new molecular signature method for prediction of driver cancer pathways from transcriptional data (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways.
    Keywords: Computational Methods, Genomics
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  • 5
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    DanQ: a hybrid convolutional and recurrent deep neural network for quantifying the function of DNA sequences (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory ‘grammar’ to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ .
    Keywords: Computational Methods, Genomics
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  • 6
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    Phylogeny-aware identification and correction of taxonomically mislabeled sequences (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: Molecular sequences in public databases are mostly annotated by the submitting authors without further validation. This procedure can generate erroneous taxonomic sequence labels. Mislabeled sequences are hard to identify, and they can induce downstream errors because new sequences are typically annotated using existing ones. Furthermore, taxonomic mislabelings in reference sequence databases can bias metagenetic studies which rely on the taxonomy. Despite significant efforts to improve the quality of taxonomic annotations, the curation rate is low because of the labor-intensive manual curation process. Here, we present SATIVA, a phylogeny-aware method to automatically identify taxonomically mislabeled sequences (‘mislabels’) using statistical models of evolution. We use the Evolutionary Placement Algorithm (EPA) to detect and score sequences whose taxonomic annotation is not supported by the underlying phylogenetic signal, and automatically propose a corrected taxonomic classification for those. Using simulated data, we show that our method attains high accuracy for identification (96.9% sensitivity/91.7% precision) as well as correction (94.9% sensitivity/89.9% precision) of mislabels. Furthermore, an analysis of four widely used microbial 16S reference databases (Greengenes, LTP, RDP and SILVA) indicates that they currently contain between 0.2% and 2.5% mislabels. Finally, we use SATIVA to perform an in-depth evaluation of alternative taxonomies for Cyanobacteria. SATIVA is freely available at https://github.com/amkozlov/sativa .
    Keywords: Computational Methods, Genomics
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  • 7
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    iGEMS: an integrated model for identification of alternative exon usage events (2016)
    Oxford University Press
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    Publication Date: 2016-06-21
    Description: DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with ( n = 9) or without ( n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (~90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3'UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.
    Keywords: Computational Methods, Genomics
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  • 8
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    TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.
    Keywords: Computational Methods, Genomics
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  • 9
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    Robust detection of alternative splicing in a population of single cells (2016)
    Oxford University Press
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    Publication Date: 2016-05-06
    Description: Single cell RNA-seq experiments provide valuable insight into cellular heterogeneity but suffer from low coverage, 3' bias and technical noise. These unique properties of single cell RNA-seq data make study of alternative splicing difficult, and thus most single cell studies have restricted analysis of transcriptome variation to the gene level. To address these limitations, we developed SingleSplice, which uses a statistical model to detect genes whose isoform usage shows biological variation significantly exceeding technical noise in a population of single cells. Importantly, SingleSplice is tailored to the unique demands of single cell analysis, detecting isoform usage differences without attempting to infer expression levels for full-length transcripts. Using data from spike-in transcripts, we found that our approach detects variation in isoform usage among single cells with high sensitivity and specificity. We also applied SingleSplice to data from mouse embryonic stem cells and discovered a set of genes that show significant biological variation in isoform usage across the set of cells. A subset of these isoform differences are linked to cell cycle stage, suggesting a novel connection between alternative splicing and the cell cycle.
    Keywords: Computational Methods, Genomics
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  • 10
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    CARGO: effective format-free compressed storage of genomic information (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this hinders flexible and effective data sharing. Here, we present CARGO (Compressed ARchiving for GenOmics), a high-level framework to automatically generate software systems optimized for the compressed storage of arbitrary types of large genomic data collections. Straightforward applications of our approach to FASTQ and SAM archives require a few lines of code, produce solutions that match and sometimes outperform specialized format-tailored compressors and scale well to multi-TB datasets. All CARGO software components can be freely downloaded for academic and non-commercial use from http://bio-cargo.sourceforge.net .
    Keywords: Computational Methods, Genomics
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  • 11
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    InPhaDel: integrative shotgun and proximity-ligation sequencing to phase deletions with single nucleotide polymorphisms (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Phasing of single nucleotide (SNV), and structural variations into chromosome-wide haplotypes in humans has been challenging, and required either trio sequencing or restricting phasing to population-based haplotypes. Selvaraj et al . demonstrated single individual SNV phasing is possible with proximity ligated (HiC) sequencing. Here, we demonstrate HiC can phase structural variants into phased scaffolds of SNVs. Since HiC data is noisy, and SV calling is challenging, we applied a range of supervised classification techniques, including Support Vector Machines and Random Forest, to phase deletions. Our approach was demonstrated on deletion calls and phasings on the NA12878 human genome. We used three NA12878 chromosomes and simulated chromosomes to train model parameters. The remaining NA12878 chromosomes withheld from training were used to evaluate phasing accuracy. Random Forest had the highest accuracy and correctly phased 86% of the deletions with allele-specific read evidence. Allele-specific read evidence was found for 76% of the deletions. HiC provides significant read evidence for accurately phasing 33% of the deletions. Also, eight of eight top ranked deletions phased by only HiC were validated using long range polymerase chain reaction and Sanger. Thus, deletions from a single individual can be accurately phased using a combination of shotgun and proximity ligation sequencing. InPhaDel software is available at: http://l337x911.github.io/inphadel/.
    Keywords: Computational Methods, Genomics
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  • 12
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    Redundans: an assembly pipeline for highly heterozygous genomes (2016)
    Oxford University Press
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    Publication Date: 2016-07-09
    Description: Many genomes display high levels of heterozygosity (i.e. presence of different alleles at the same loci in homologous chromosomes), being those of hybrid organisms an extreme such case. The assembly of highly heterozygous genomes from short sequencing reads is a challenging task because it is difficult to accurately recover the different haplotypes. When confronted with highly heterozygous genomes, the standard assembly process tends to collapse homozygous regions and reports heterozygous regions in alternative contigs. The boundaries between homozygous and heterozygous regions result in multiple assembly paths that are hard to resolve, which leads to highly fragmented assemblies with a total size larger than expected. This, in turn, causes numerous problems in downstream analyses such as fragmented gene models, wrong gene copy number, or broken synteny. To circumvent these caveats we have developed a pipeline that specifically deals with the assembly of heterozygous genomes by introducing a step to recognise and selectively remove alternative heterozygous contigs. We tested our pipeline on simulated and naturally-occurring heterozygous genomes and compared its accuracy to other existing tools. Our method is freely available at https://github.com/Gabaldonlab/redundans .
    Keywords: Computational Methods, Genomics
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  • 13
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    Graph-based modeling of tandem repeats improves global multiple sequence alignment (2013)
    Oxford University Press
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    Publication Date: 2013-09-26
    Description: Tandem repeats (TRs) are often present in proteins with crucial functions, responsible for resistance, pathogenicity and associated with infectious or neurodegenerative diseases. This motivates numerous studies of TRs and their evolution, requiring accurate multiple sequence alignment. TRs may be lost or inserted at any position of a TR region by replication slippage or recombination, but current methods assume fixed unit boundaries, and yet are of high complexity. We present a new global graph-based alignment method that does not restrict TR unit indels by unit boundaries. TR indels are modeled separately and penalized using the phylogeny-aware alignment algorithm. This ensures enhanced accuracy of reconstructed alignments, disentangling TRs and measuring indel events and rates in a biologically meaningful way. Our method detects not only duplication events but also all changes in TR regions owing to recombination, strand slippage and other events inserting or deleting TR units. We evaluate our method by simulation incorporating TR evolution, by either sampling TRs from a profile hidden Markov model or by mimicking strand slippage with duplications. The new method is illustrated on a family of type III effectors, a pathogenicity determinant in agriculturally important bacteria Ralstonia solanacearum. We show that TR indel rate variation contributes to the diversification of this protein family.
    Keywords: Computational Methods, Genomics
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  • 14
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    Meander: visually exploring the structural variome using space-filling curves (2013)
    Oxford University Press
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    Publication Date: 2013-06-08
    Description: The introduction of next generation sequencing methods in genome studies has made it possible to shift research from a gene-centric approach to a genome wide view. Although methods and tools to detect single nucleotide polymorphisms are becoming more mature, methods to identify and visualize structural variation (SV) are still in their infancy. Most genome browsers can only compare a given sequence to a reference genome; therefore, direct comparison of multiple individuals still remains a challenge. Therefore, the implementation of efficient approaches to explore and visualize SVs and directly compare two or more individuals is desirable. In this article, we present a visualization approach that uses space-filling Hilbert curves to explore SVs based on both read-depth and pair-end information. An interactive open-source Java application, called Meander , implements the proposed methodology, and its functionality is demonstrated using two cases. With Meander , users can explore variations at different levels of resolution and simultaneously compare up to four different individuals against a common reference. The application was developed using Java version 1.6 and Processing.org and can be run on any platform. It can be found at http://homes.esat.kuleuven.be/~bioiuser/meander .
    Keywords: Computational Methods, Genomics
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  • 15
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    Following the footprints of polymorphic inversions on SNP data: from detection to association tests (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 16
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    Reconstructing genome-scale metabolic models with merlin (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: The Metabolic Models Reconstruction Using Genome-Scale Information ( merlin ) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin .
    Keywords: Computational Methods, Genomics
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  • 17
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    Inferential modeling of 3D chromatin structure (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: For eukaryotic cells, the biological processes involving regulatory DNA elements play an important role in cell cycle. Understanding 3D spatial arrangements of chromosomes and revealing long-range chromatin interactions are critical to decipher these biological processes. In recent years, chromosome conformation capture (3C) related techniques have been developed to measure the interaction frequencies between long-range genome loci, which have provided a great opportunity to decode the 3D organization of the genome. In this paper, we develop a new Bayesian framework to derive the 3D architecture of a chromosome from 3C-based data. By modeling each chromosome as a polymer chain, we define the conformational energy based on our current knowledge on polymer physics and use it as prior information in the Bayesian framework. We also propose an expectation-maximization (EM) based algorithm to estimate the unknown parameters of the Bayesian model and infer an ensemble of chromatin structures based on interaction frequency data. We have validated our Bayesian inference approach through cross-validation and verified the computed chromatin conformations using the geometric constraints derived from fluorescence in situ hybridization (FISH) experiments. We have further confirmed the inferred chromatin structures using the known genetic interactions derived from other studies in the literature. Our test results have indicated that our Bayesian framework can compute an accurate ensemble of 3D chromatin conformations that best interpret the distance constraints derived from 3C-based data and also agree with other sources of geometric constraints derived from experimental evidence in the previous studies. The source code of our approach can be found in https://github.com/wangsy11/InfMod3DGen .
    Keywords: Computational Methods, Genomics
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  • 18
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    Integrating motif, DNA accessibility and gene expression data to build regulatory maps in an organism (2015)
    Oxford University Press
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    Publication Date: 2015-05-03
    Description: Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF–DNA binding specificities (‘motifs’). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF–DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of ~200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays.
    Keywords: Computational Methods, Genomics
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  • 19
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    Decomposing the Farmer's Share of the Food Dollar (2015)
    Oxford University Press
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    Publication Date: 2015-05-12
    Description: The Canadian farm share for five crop-based products and seven livestock-based products from 1997 to 2010 is calculated using a supply chain IO analysis. Significant differences exist in farm shares across food commodities with higher farm shares for livestock products and lower farm shares for grain-based products. The decline in the Canadian farm share for food consumed at home is driven in large part by the food purchasing habits of consumers. This paper also addresses the hypothesis that the decline in the Canadian farm share could be partially driven by rising input costs in post-farmgate processes or rising input costs that have greater impact on downstream sectors than primary agricultural producers. Three experiments were conducted to assess the impact of an increase in the cost of corn, energy, and farm labor would have on commodity output prices, farm returns, food expenditure, and farm share. In all three cases, the overall farm share increases, albeit by a small amount, suggesting that these shocks have a larger relative impact on the prices of agricultural commodities than the prices of marketing commodities used in post-farmgate activities. A two-period comparison of these simulations shows that energy (corn and farm labour) price shocks would have had a greater (lower) impact on the farm share in 2007 than 1997.
    Keywords: Q11 - Aggregate Supply and Demand Analysis ; Prices, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 20
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    Strengthening Market Linkages of Farm Households in Developing Countries (2015)
    Oxford University Press
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    Publication Date: 2015-05-12
    Description: Farm households in developing countries generally allocate a major portion of their resources to staple food production, mainly for self-consumption. Hence, many of them are more or less delinked from the market. It is well recognized, however, that market participation is crucial for farm households to ensure a flow of cash income, leading to poverty alleviation and improved livelihoods. Thus, it is meaningful to understand what factors affect farm households' decision to sell food crops, which is important for strengthening their linkages with markets. The empirical literature on impacts of market linkages has seldom focused on the determinants of market participation. Using rice farm households in Bangladesh and applying a double-hurdle model, this article demonstrates that the provision of general education and the development of agricultural infrastructure such as irrigation facilities can strengthen the market linkages of farm households by enhancing their marketable surplus through increased production. By contrast, rainfall beyond the optimum level, drought spells, and flood incidences can weaken market linkages by reducing their marketable surplus through decreased production. Specific policies such as investment in general education are drawn up based on the findings.
    Keywords: C24 - Truncated and Censored Models, D01 - Microeconomic Behavior: Underlying Principles, D13 - Household Production and Intrahousehold Allocation, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 21
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    FOAM (Functional Ontology Assignments for Metagenomes): a Hidden Markov Model (HMM) database with environmental focus (2014)
    Oxford University Press
    Details
    Publication Date: 2014-11-07
    Description: A new functional gene database, FOAM (Functional Ontology Assignments for Metagenomes), was developed to screen environmental metagenomic sequence datasets. FOAM provides a new functional ontology dedicated to classify gene functions relevant to environmental microorganisms based on Hidden Markov Models (HMMs). Sets of aligned protein sequences (i.e. ‘profiles’) were tailored to a large group of target KEGG Orthologs (KOs) from which HMMs were trained. The alignments were checked and curated to make them specific to the targeted KO. Within this process, sequence profiles were enriched with the most abundant sequences available to maximize the yield of accurate classifier models. An associated functional ontology was built to describe the functional groups and hierarchy. FOAM allows the user to select the target search space before HMM-based comparison steps and to easily organize the results into different functional categories and subcategories. FOAM is publicly available at http://portal.nersc.gov/project/m1317/FOAM/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Production standards, competition and vertical relationship (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-29
    Description: This article investigates the collective choice of production standards by farmer and processor groups within a vertical food supply chain, taking into account their competition behaviours. We develop a general model to analyse the strategic motive of using standards to limit supply and shift rents between farmers and processors in the vertical chain. We find that a stringent standard can raise farmers' profit, but at the expense of processors. This is the case when the standard affects more variable costs than fixed cost of production, when the demand for the final product is inelastic, and when processors have a high degree of oligopoly power.
    Keywords: L13 - Oligopoly and Other Imperfect Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    A Framework to Analyze the Performance of Thinly Traded Agricultural Commodity Markets (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-31
    Description: Thinly traded agricultural commodity markets are a concern for farmers and policy markers due to the belief that prices in these settings will be highly volatile, subject to manipulation, and incapable of efficiently allocating resources. Analysis of thin agricultural markets has to date been impeded by lack of an appropriate analytical framework from which to study their behavior. In this paper we propose the modern agricultural markets (MAM) framework as an appropriate paradigm through which to view and evaluate thin markets. We argue that thinly traded markets that meet key conditions required for a MAM will generate maximum economic surplus and enable farmers to earn at least a competitive return on their investments. In the absence of these conditions, however, the concerns known as the "thin market problem" have validity. We set forth the MAM framework, interpret it in a thin-market context, and conduct several brief case studies of thin markets to illustrate use of the approach and draw some key inferences about these markets' behavior. The analysis indicates that appropriate government policies directed to thin markets are those that facilitate their convergence to MAM status, but in reality key policies under recent consideration would have the opposite effect.
    Keywords: L10 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    A statistical framework for revealing signaling pathways perturbed by DNA variants (2015)
    Oxford University Press
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    Publication Date: 2015-06-24
    Description: Much of the inter-individual variation in gene expression is triggered via perturbations of signaling networks by DNA variants. We present a novel probabilistic approach for identifying the particular pathways by which DNA variants perturb the signaling network. Our procedure, called PINE, relies on a systematic integration of established biological knowledge of signaling networks with data on transcriptional responses to various experimental conditions. Unlike previous approaches, PINE provides statistical aspects that are critical for prioritizing hypotheses for followup experiments. Using simulated data, we show that higher accuracy is attained with PINE than with existing methods. We used PINE to analyze transcriptional responses of immune dendritic cells to several pathogenic stimulations. PINE identified statistically significant genetic perturbations in the pathogen-sensing signaling network, suggesting previously uncharacterized regulatory mechanisms for functional DNA variants.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses (2015)
    Oxford University Press
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    Publication Date: 2015-08-29
    Description: Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package.
    Keywords: Computational Methods, Genomics
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    RAX2: a genome-wide detection method of condition-associated transcription variation (2015)
    Oxford University Press
    Details
    Publication Date: 2015-08-29
    Description: Most mammalian genes have mRNA variants due to alternative promoter usage, alternative splicing, and alternative cleavage and polyadenylation. Expression of alternative RNA isoforms has been found to be associated with tumorigenesis, proliferation and differentiation. Detection of condition-associated transcription variation requires association methods. Traditional association methods such as Pearson chi-square test and Fisher Exact test are single test methods and do not work on count data with replicates. Although the Cochran Mantel Haenszel (CMH) approach can handle replicated count data, our simulations showed that multiple CMH tests still had very low power. To identify condition-associated variation of transcription, we here proposed a ranking analysis of chi-squares (RAX2) for large-scale association analysis. RAX2 is a nonparametric method and has accurate and conservative estimation of FDR profile. Simulations demonstrated that RAX2 performs well in finding condition-associated transcription variants. We applied RAX2 to primary T-cell transcriptomic data and identified 1610 (16.3%) tags associated in transcription with immune stimulation at FDR 〈 0.05. Most of these tags also had differential expression. Analysis of two and three tags within genes revealed that under immune stimulation short RNA isoforms were preferably used.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Following Up on Smallholder Farmers and Supermarkets in Kenya (2015)
    Oxford University Press
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    Publication Date: 2015-07-10
    Description: In many developing countries, supermarkets are expanding rapidly. This affects farmers’ marketing options. Previous studies have analyzed welfare effects of smallholder participation in supermarket channels from a static perspective, using cross-section data. We develop a conceptual framework and use panel data to better understand participation and impact dynamics. The analysis focuses on vegetable producers in Kenya. Participation in supermarket channels is associated with income gains. However, many farmers have dropped out of the supermarket channel due to various constraints. The initial income gains cannot be sustained when returning to the traditional market. Organizational support may be needed to avoid widening income disparities.
    Keywords: L24 - Contracting Out ; Joint Ventures ; Technology Licensing, O12 - Microeconomic Analyses of Economic Development, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Unique transposon landscapes are pervasive across Drosophila melanogaster genomes (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-16
    Description: To understand how transposon landscapes (TLs) vary across animal genomes, we describe a new method called the Transposon Insertion and Depletion AnaLyzer (TIDAL) and a database of 〉300 TLs in Drosophila melanogaster (TIDAL-Fly). Our analysis reveals pervasive TL diversity across cell lines and fly strains, even for identically named sub-strains from different laboratories such as the ISO1 strain used for the reference genome sequence. On average, 〉500 novel insertions exist in every lab strain, inbred strains of the Drosophila Genetic Reference Panel (DGRP), and fly isolates in the Drosophila Genome Nexus (DGN). A minority (〈25%) of transposon families comprise the majority (〉70%) of TL diversity across fly strains. A sharp contrast between insertion and depletion patterns indicates that many transposons are unique to the ISO1 reference genome sequence. Although TL diversity from fly strains reaches asymptotic limits with increasing sequencing depth, rampant TL diversity causes unsaturated detection of TLs in pools of flies. Finally, we show novel transposon insertions negatively correlate with Piwi-interacting RNA (piRNA) levels for most transposon families, except for the highly-abundant roo retrotransposon. Our study provides a useful resource for Drosophila geneticists to understand how transposons create extensive genomic diversity in fly cell lines and strains.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Mixed Integer Linear Programming based machine learning approach identifies regulators of telomerase in yeast (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.
    Keywords: Computational Methods, Genomics
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    f-divergence cutoff index to simultaneously identify differential expression in the integrated transcriptome and proteome (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: The ability to integrate ‘omics’ (i.e. transcriptomics and proteomics) is becoming increasingly important to the understanding of regulatory mechanisms. There are currently no tools available to identify differentially expressed genes (DEGs) across different ‘omics’ data types or multi-dimensional data including time courses. We present fCI (f-divergence Cut-out Index), a model capable of simultaneously identifying DEGs from continuous and discrete transcriptomic, proteomic and integrated proteogenomic data. We show that fCI can be used across multiple diverse sets of data and can unambiguously find genes that show functional modulation, developmental changes or misregulation. Applying fCI to several proteogenomics datasets, we identified a number of important genes that showed distinctive regulation patterns. The package fCI is available at R Bioconductor and http://software.steenlab.org/fCI/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    CLASS2: accurate and efficient splice variant annotation from RNA-seq reads (2016)
    Oxford University Press
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    Publication Date: 2016-06-03
    Description: Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to accurately capture splicing variation has proven difficult. Current programs can find major isoforms of a gene but miss lower abundance variants, or are sensitive but imprecise. CLASS2 is a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads based on the model of splice graph. An extension of our program CLASS, CLASS2 jointly optimizes read patterns and the number of supporting reads to score and prioritize transcripts, implemented in a novel, scalable and efficient dynamic programming algorithm. When compared against reference programs, CLASS2 had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool to produce consistently reliable transcript models for a wide range of applications and sequencing strategies, including ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS2 requires 〈3GB RAM and can analyze a 350 million read set within hours, and can be widely applied to transcriptomics studies ranging from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing (2016)
    Oxford University Press
    Details
    Publication Date: 2016-09-20
    Description: Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    A genome-wide approach for detecting novel insertion-deletion variants of mid-range size (2016)
    Oxford University Press
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    Publication Date: 2016-09-03
    Description: We present SWAN, a statistical framework for robust detection of genomic structural variants in next-generation sequencing data and an analysis of mid-range size insertion and deletions (〈10 Kb) for whole genome analysis and DNA mixtures. To identify these mid-range size events, SWAN collectively uses information from read-pair, read-depth and one end mapped reads through statistical likelihoods based on Poisson field models. SWAN also uses soft-clip/split read remapping to supplement the likelihood analysis and determine variant boundaries. The accuracy of SWAN is demonstrated by in silico spike-ins and by identification of known variants in the NA12878 genome. We used SWAN to identify a series of novel set of mid-range insertion/deletion detection that were confirmed by targeted deep re-sequencing. An R package implementation of SWAN is open source and freely available.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Cuba's Agricultural Transition and Food Security in a Global Perspective (2016)
    Oxford University Press
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    Publication Date: 2016-08-20
    Description: This paper reviews the situation in the agricultural sector and food security in Cuba, and particularly the transformations that have (not) taken place since 1990. We compare the Cuban transition with transitions in other "transition countries" and show that Cuba does not easily fit into one of the transition patterns, and, in a way, has characteristics of "a bit of everything". To conclude, we discuss the (potential) effects of the recent policy changes and the new economic reforms that were announced.
    Keywords: O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, P21 - Planning, Coordination, and Reform, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Comprehensive analysis of high-throughput screens with HiTSeekR (2016)
    Oxford University Press
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    Publication Date: 2016-08-20
    Description: High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. We chose three use cases that demonstrate the potential of HiTSeekR to fully exploit HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNFα, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is publicly available at http://hitseekr.compbio.sdu.dk . It is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.
    Keywords: Computational Methods, Genomics
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    An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next-generation sequencing data (2015)
    Oxford University Press
    Details
    Publication Date: 2015-04-21
    Description: Next-generation sequencing (NGS) approaches rapidly produce millions to billions of short reads, which allow pathogen detection and discovery in human clinical, animal and environmental samples. A major limitation of sequence homology-based identification for highly divergent microorganisms is the short length of reads generated by most highly parallel sequencing technologies. Short reads require a high level of sequence similarities to annotated genes to confidently predict gene function or homology. Such recognition of highly divergent homologues can be improved by reference-free ( de novo ) assembly of short overlapping sequence reads into larger contigs. We describe an ensemble strategy that integrates the sequential use of various de Bruijn graph and overlap-layout-consensus assemblers with a novel partitioned sub-assembly approach. We also proposed new quality metrics that are suitable for evaluating metagenome de novo assembly. We demonstrate that this new ensemble strategy tested using in silico spike-in, clinical and environmental NGS datasets achieved significantly better contigs than current approaches.
    Keywords: Computational Methods, Genomics
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    Distinguishing between productive and abortive promoters using a random forest classifier in Mycoplasma pneumoniae (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: Distinguishing between promoter-like sequences in bacteria that belong to true or abortive promoters, or to those that do not initiate transcription at all, is one of the important challenges in transcriptomics. To address this problem, we have studied the genome-reduced bacterium Mycoplasma pneumoniae , for which the RNAs associated with transcriptional start sites have been recently experimentally identified. We determined the contribution to transcription events of different genomic features: the –10, extended –10 and –35 boxes, the UP element, the bases surrounding the –10 box and the nearest-neighbor free energy of the promoter region. Using a random forest classifier and the aforementioned features transformed into scores, we could distinguish between true, abortive promoters and non-promoters with good –10 box sequences. The methods used in this characterization of promoters can be extended to other bacteria and have important applications for promoter design in bacterial genome engineering.
    Keywords: Computational Methods, Genomics
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    Mobile Phone Coverage and Producer Markets: Evidence from West Africa (2015)
    Oxford University Press
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    Publication Date: 2015-05-21
    Description: Mobile phone coverage has expanded considerably throughout the developing world, particularly within sub-Saharan Africa. Existing evidence suggests that increased access to information technology has improved agricultural market efficiency for consumer markets and certain commodities, but there is less evidence of its impact on producer markets. Building on the work of Aker (2010) , we estimate the impact of mobile phone coverage on producer price dispersion for three commodities in Niger. Our results suggest that mobile phone coverage reduces spatial producer price dispersion by 6 percent for cowpea, a semi-perishable commodity. These effects are strongest for remote markets and during certain periods of the year. The introduction of mobile phone coverage has no effect on producer price dispersion for millet and sorghum, two staple grains that are less perishable and are commonly stored by farmers. There are no impacts of mobile phone coverage on producer price levels, but mobile phone coverage is associated with a reduction in the intra-annual price variation for cowpea.
    Keywords: O30 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0258-6770
    Electronic ISSN: 1564-698X
    Topics: Economics
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    Under-contribution to generic advertising due to self-interested inequity aversion (2015)
    Oxford University Press
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    Publication Date: 2015-05-26
    Description: We modify the behavioural postulate of self-centred inequity aversion to explain producers' reluctance to fund generic fruit and vegetable advertising as a result of experiencing negative utility when others benefit more from a public good than themselves, but positive utility when they earn more than others. We find that higher variability in returns decreases the probability of a favourable vote. Conversely, if information about payoffs is incomplete, if subjects are allowed to experience a trial run of a generic advertising programme, if returns are equal across producers, or if there is government support for the programme, the likelihood of approval rises.
    Keywords: H41 - Public Goods, M37 - Advertising, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Pathway analysis from lists of microRNAs: common pitfalls and alternative strategy (2015)
    Oxford University Press
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    Publication Date: 2015-04-21
    Description: MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods.
    Keywords: Computational Methods, Genomics
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    svaseq: removing batch effects and other unwanted noise from sequencing data (2014)
    Oxford University Press
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    Publication Date: 2014-11-28
    Description: It is now known that unwanted noise and unmodeled artifacts such as batch effects can dramatically reduce the accuracy of statistical inference in genomic experiments. These sources of noise must be modeled and removed to accurately measure biological variability and to obtain correct statistical inference when performing high-throughput genomic analysis. We introduced surrogate variable analysis (sva) for estimating these artifacts by (i) identifying the part of the genomic data only affected by artifacts and (ii) estimating the artifacts with principal components or singular vectors of the subset of the data matrix. The resulting estimates of artifacts can be used in subsequent analyses as adjustment factors to correct analyses. Here I describe a version of the sva approach specifically created for count data or FPKMs from sequencing experiments based on appropriate data transformation. I also describe the addition of supervised sva (ssva) for using control probes to identify the part of the genomic data only affected by artifacts. I present a comparison between these versions of sva and other methods for batch effect estimation on simulated data, real count-based data and FPKM-based data. These updates are available through the sva Bioconductor package and I have made fully reproducible analysis using these methods available from: https://github.com/jtleek/svaseq .
    Keywords: Computational Methods, Genomics
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    Insyght: navigating amongst abundant homologues, syntenies and gene functional annotations in bacteria, it's that symbol! (2014)
    Oxford University Press
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    Publication Date: 2014-11-28
    Description: High-throughput techniques have considerably increased the potential of comparative genomics whilst simultaneously posing many new challenges. One of those challenges involves efficiently mining the large amount of data produced and exploring the landscape of both conserved and idiosyncratic genomic regions across multiple genomes. Domains of application of these analyses are diverse: identification of evolutionary events, inference of gene functions, detection of niche-specific genes or phylogenetic profiling. Insyght is a comparative genomic visualization tool that combines three complementary displays: (i) a table for thoroughly browsing amongst homologues, (ii) a comparator of orthologue functional annotations and (iii) a genomic organization view designed to improve the legibility of rearrangements and distinctive loci. The latter display combines symbolic and proportional graphical paradigms. Synchronized navigation across multiple species and interoperability between the views are core features of Insyght. A gene filter mechanism is provided that helps the user to build a biologically relevant gene set according to multiple criteria such as presence/absence of homologues and/or various annotations. We illustrate the use of Insyght with scenarios. Currently, only Bacteria and Archaea are supported. A public instance is available at http://genome.jouy.inra.fr/Insyght . The tool is freely downloadable for private data set analysis.
    Keywords: Computational Methods, Genomics
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    iPro54-PseKNC: a sequence-based predictor for identifying sigma-54 promoters in prokaryote with pseudo k-tuple nucleotide composition (2014)
    Oxford University Press
    Details
    Publication Date: 2014-11-28
    Description: The 54 promoters are unique in prokaryotic genome and responsible for transcripting carbon and nitrogen-related genes. With the avalanche of genome sequences generated in the postgenomic age, it is highly desired to develop automated methods for rapidly and effectively identifying the 54 promoters. Here, a predictor called ‘ iPro54-PseKNC ’ was developed. In the predictor, the samples of DNA sequences were formulated by a novel feature vector called ‘pseudo k -tuple nucleotide composition’, which was further optimized by the incremental feature selection procedure. The performance of iPro54-PseKNC was examined by the rigorous jackknife cross-validation tests on a stringent benchmark data set. As a user-friendly web-server, iPro54-PseKNC is freely accessible at http://lin.uestc.edu.cn/server/iPro54-PseKNC . For the convenience of the vast majority of experimental scientists, a step-by-step protocol guide was provided on how to use the web-server to get the desired results without the need to follow the complicated mathematics that were presented in this paper just for its integrity. Meanwhile, we also discovered through an in-depth statistical analysis that the distribution of distances between the transcription start sites and the translation initiation sites were governed by the gamma distribution, which may provide a fundamental physical principle for studying the 54 promoters.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Binding site discovery from nucleic acid sequences by discriminative learning of hidden Markov models (2014)
    Oxford University Press
    Details
    Publication Date: 2014-11-28
    Description: We present a discriminative learning method for pattern discovery of binding sites in nucleic acid sequences based on hidden Markov models. Sets of positive and negative example sequences are mined for sequence motifs whose occurrence frequency varies between the sets. The method offers several objective functions, but we concentrate on mutual information of condition and motif occurrence. We perform a systematic comparison of our method and numerous published motif-finding tools. Our method achieves the highest motif discovery performance, while being faster than most published methods. We present case studies of data from various technologies, including ChIP-Seq, RIP-Chip and PAR-CLIP, of embryonic stem cell transcription factors and of RNA-binding proteins, demonstrating practicality and utility of the method. For the alternative splicing factor RBM10, our analysis finds motifs known to be splicing-relevant. The motif discovery method is implemented in the free software package Discrover. It is applicable to genome- and transcriptome-scale data, makes use of available repeat experiments and aside from binary contrasts also more complex data configurations can be utilized.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Direct Payments, Spatial Competition, and Farm Survival in Norway (2015)
    Oxford University Press
    Details
    Publication Date: 2015-07-10
    Description: We argue that farm survival is influenced by neighboring farmers’ characteristics and, in particular, by the direct payments neighboring farmers receive. The article shows empirically that these interdependencies are crucial for an assessment of the effects of direct payments on farm survival. Using spatially explicit farm-level data for nearly all Norwegian farms, a spatial probit model is estimated to explain farm survival from 1999 to 2009 controlling for spatial farm interdependence. We show that ignoring spatial interdependencies between farms leads to a substantial overestimation of the effects of direct payments on farm survival. To our knowledge, this article is the first attempt to empirically analyze the importance of neighboring interdependencies for the effects of direct payments on farm survival.
    Keywords: C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models, C25 - Discrete Regression and Qualitative Choice Models, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    A Triple-Hurdle Model of Production and Market Participation in Kenya's Dairy Market (2015)
    Oxford University Press
    Details
    Publication Date: 2015-07-10
    Description: Existing analyses of market participation are based on a "double-hurdle" modeling approach. Such models are appropriate only when all members of the population of interest actually produce the good. In some contexts, however (e.g., smallholder farmers), many members of the population do not produce particular goods that they could produce and that their neighbors do produce. Policies influencing market participation among producers may thus also induce additional farmers to become producers. Previous double-hurdle approaches do not allow explicitly for this possibility. To address these limitations, this article presents a "triple-hurdle" approach with an initial stage that includes nonproducers. The model is used to identify the factors associated with Kenyan smallholder farmers choosing to participate in dairy production, and the role that these producers choose to play (or not) in the marketplace. In the midst of debates underway over the privatization of the parastatal Kenya Creameries Company, new knowledge about smallholder participation in dairy could be an important contribution. Results suggest the importance of rural electrification, training, and improved grazing practices. We find that expected net sales are significantly higher when farmers have access to informal private markets. We also describe a version of the ordered tobit model that includes nonproducers and is nested in our triple-hurdle model. A likelihood ratio test shows the latter to be a significantly better fit to our data. We discuss how insights gained from this study differ from the insights that would come from a double-hurdle ordered tobit that also includes nonproducers.
    Keywords: C51 - Model Construction and Estimation, C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data, O12 - Microeconomic Analyses of Economic Development, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    What Happens When Food Marketers Require Restrictive Farming Practices? (2015)
    Oxford University Press
    Details
    Publication Date: 2015-07-10
    Description: The dimensions that define a food product have expanded rapidly to include characteristics of the production process, marketing arrangements, and implications that production and consumption of the product have for the environment. Some market intermediaries have responded by requiring that their suppliers abide by restrictive production practices. We examine the economic effects of such restrictions and apply this analysis to limitations on the use of antibiotics in U.S. pork production. Results from conceptual and simulation analyses show that, in the absence of demand growth, less pork is sold due to higher costs in the restricted segment, and both pork consumers (on average) and producers are harmed. Demand growth of between 6–11% from adding new consumers who will consume the restricted (antibiotic-free) product but not the conventional product is needed to return consumer surplus to the level in the base case, and between 2–4% demand growth was required to return producer surplus to base. When restricted and conventional products are modeled using a vertical differentiation framework, results depend importantly on the ease with which consumers can switch to a seller who offers their desired product type. Significant distributional impacts among consumers are present when switching costs are prohibitive.
    Keywords: I18 - Government Policy ; Regulation ; Public Health, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Product quality in the agri-food chain: do cooperatives offer high-quality wine? (2012)
    Oxford University Press
    Details
    Publication Date: 2012-12-28
    Description: We investigate the impact of decentralised decision-making on product quality. Comparing a cooperative and an investor-owned firm suggests that members of the cooperative have an incentive to produce too much and to free-ride on quality. Whether or not cooperatives deliver higher quality products depends on the way in which the quality of the final product is determined from the quality levels of the inputs delivered (quality aggregation) as well as the number of members of the cooperative. Empirical evidence on the Austrian wine market suggests that wines produced by cooperatives tend to be of significantly lower quality, ceteris paribus .
    Keywords: D22 - Firm Behavior: Empirical Analysis, D23 - Organizational Behavior ; Transaction Costs ; Property Rights, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Spatial localization of co-regulated genes exceeds genomic gene clustering in the Saccharomyces cerevisiae genome (2013)
    Oxford University Press
    Details
    Publication Date: 2013-02-20
    Description: While it has been long recognized that genes are not randomly positioned along the genome, the degree to which its 3D structure influences the arrangement of genes has remained elusive. In particular, several lines of evidence suggest that actively transcribed genes are spatially co-localized, forming transcription factories; however, a generalized systematic test has hitherto not been described. Here we reveal transcription factories using a rigorous definition of genomic structure based on Saccharomyces cerevisiae chromosome conformation capture data, coupled with an experimental design controlling for the primary gene order. We develop a data-driven method for the interpolation and the embedding of such datasets and introduce statistics that enable the comparison of the spatial and genomic densities of genes. Combining these, we report evidence that co-regulated genes are clustered in space, beyond their observed clustering in the context of gene order along the genome and show this phenomenon is significant for 64 out of 117 transcription factors. Furthermore, we show that those transcription factors with high spatially co-localized targets are expressed higher than those whose targets are not spatially clustered. Collectively, our results support the notion that, at a given time, the physical density of genes is intimately related to regulatory activity.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Farmers' satisfaction and intention to continue membership in agricultural marketing co-operatives: neoclassical versus transaction cost considerations (2013)
    Oxford University Press
    Details
    Publication Date: 2013-02-26
    Description: The survival of agricultural marketing co-operatives depends on their capability of satisfying and maintaining their base of farmer members. Hypotheses regarding these two success factors are developed in neoclassical economics and transaction cost economics. They are tested with a survey of 321 members of marketing co-operatives specialising in fresh fruits and vegetables. Our results show support for both perspectives. Price paid to farmers is important for their satisfaction with the co-operative. Farmers' perceptions of transaction costs are even more important.
    Keywords: D22 - Firm Behavior: Empirical Analysis, D23 - Organizational Behavior ; Transaction Costs ; Property Rights, P13 - Cooperative Enterprises, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Combining discrete and continuous mixing distributions to identify niche markets for food (2013)
    Oxford University Press
    Details
    Publication Date: 2013-02-26
    Description: This paper explores the demand and willingness to pay (WTP) for value-added services to chicken. Since the demand for such services are likely to be highly segmented and often applies only to a market niche, models based on assumptions of homogeneity among consumers are likely to be inappropriate. For this reason, this paper combines discrete and continuous mixing distributions to concurrently identify the size of the niche market and the heterogeneity among consumers within the market niche. Failing to account for the niche market nature of value-added services is shown to have implications for predictions of WTP, demand and total revenue.
    Keywords: C25 - Discrete Regression and Qualitative Choice Models, D12 - Consumer Economics: Empirical Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species (2012)
    Oxford University Press
    Details
    Publication Date: 2012-12-14
    Description: Pan-genome ortholog clustering tool ( PanOCT ) is a tool for pan-genomic analysis of closely related prokaryotic species or strains. PanOCT uses conserved gene neighborhood information to separate recently diverged paralogs into orthologous clusters where homology-only clustering methods cannot. The results from PanOCT and three commonly used graph-based ortholog-finding programs were compared using a set of four publicly available strains of the same bacterial species. All four methods agreed on ~70% of the clusters and ~86% of the proteins. The clusters that did not agree were inspected for evidence of correctness resulting in 85 high-confidence manually curated clusters that were used to compare all four methods.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    A novel ab initio identification system of transcriptional regulation motifs in genome DNA sequences based on direct comparison scheme of signal/noise distributions (2012)
    Oxford University Press
    Details
    Publication Date: 2012-10-10
    Description: A novel ab initio parameter-tuning-free system to identify transcriptional factor (TF) binding motifs (TFBMs) in genome DNA sequences was developed. It is based on the comparison of two types of frequency distributions with respect to the TFBM candidates in the target DNA sequences and the non-candidates in the background sequence, with the latter generated by utilizing the intergenic sequences. For benchmark tests, we used DNA sequence datasets extracted by ChIP-on-chip and ChIP-seq techniques and identified 65 yeast and four mammalian TFBMs, with the latter including gaps. The accuracy of our system was compared with those of other available programs (i.e. MEME, Weeder, BioProspector, MDscan and DME) and was the best among them, even without tuning of the parameter set for each TFBM and pre-treatment/editing of the target DNA sequences. Moreover, with respect to some TFs for which the identified motifs are inconsistent with those in the references, our results were revealed to be correct, by comparing them with other existing experimental data. Thus, our identification system does not need any other biological information except for gene positions, and is also expected to be applicable to genome DNA sequences to identify unknown TFBMs as well as known ones.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Identification of new microRNA-regulated genes by conserved targeting in plant species (2012)
    Oxford University Press
    Details
    Publication Date: 2012-10-10
    Description: MicroRNAs (miRNAs) are major regulators of gene expression in multicellular organisms. They recognize their targets by sequence complementarity and guide them to cleavage or translational arrest. It is generally accepted that plant miRNAs have extensive complementarity to their targets and their prediction usually relies on the use of empirical parameters deduced from known miRNA–target interactions. Here, we developed a strategy to identify miRNA targets which is mainly based on the conservation of the potential regulation in different species. We applied the approach to expressed sequence tags datasets from angiosperms. Using this strategy, we predicted many new interactions and experimentally validated previously unknown miRNA targets in Arabidopsis thaliana . Newly identified targets that are broadly conserved include auxin regulators, transcription factors and transporters. Some of them might participate in the same pathways as the targets known before, suggesting that some miRNAs might control different aspects of a biological process. Furthermore, this approach can be used to identify targets present in a specific group of species, and, as a proof of principle, we analyzed Solanaceae -specific targets. The presented strategy can be used alone or in combination with other approaches to find miRNA targets in plants.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    Use of ChIP-Seq data for the design of a multiple promoter-alignment method (2012)
    Oxford University Press
    Details
    Publication Date: 2012-04-15
    Description: We address the challenge of regulatory sequence alignment with a new method, Pro-Coffee, a multiple aligner specifically designed for homologous promoter regions. Pro-Coffee uses a dinucleotide substitution matrix estimated on alignments of functional binding sites from TRANSFAC. We designed a validation framework using several thousand families of orthologous promoters. This dataset was used to evaluate the accuracy for predicting true human orthologs among their paralogs. We found that whereas other methods achieve on average 73.5% accuracy, and 77.6% when trained on that same dataset, the figure goes up to 80.4% for Pro-Coffee. We then applied a novel validation procedure based on multi-species ChIP-seq data. Trained and untrained methods were tested for their capacity to correctly align experimentally detected binding sites. Whereas the average number of correctly aligned sites for two transcription factors is 284 for default methods and 316 for trained methods, Pro-Coffee achieves 331, 16.5% above the default average. We find a high correlation between a method's performance when classifying orthologs and its ability to correctly align proven binding sites. Not only has this interesting biological consequences, it also allows us to conclude that any method that is trained on the ortholog data set will result in functionally more informative alignments.
    Keywords: Computational Methods, Genomics
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    MCScanX: a toolkit for detection and evolutionary analysis of gene synteny and collinearity (2012)
    Oxford University Press
    Details
    Publication Date: 2012-04-15
    Description: MCScan is an algorithm able to scan multiple genomes or subgenomes in order to identify putative homologous chromosomal regions, and align these regions using genes as anchors. The MCScanX toolkit implements an adjusted MCScan algorithm for detection of synteny and collinearity that extends the original software by incorporating 14 utility programs for visualization of results and additional downstream analyses. Applications of MCScanX to several sequenced plant genomes and gene families are shown as examples. MCScanX can be used to effectively analyze chromosome structural changes, and reveal the history of gene family expansions that might contribute to the adaptation of lineages and taxa. An integrated view of various modes of gene duplication can supplement the traditional gene tree analysis in specific families. The source code and documentation of MCScanX are freely available at http://chibba.pgml.uga.edu/mcscan2/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    A General Equilibrium Theory of Contracts in Community Supported Agriculture (2015)
    Oxford University Press
    Details
    Publication Date: 2015-09-12
    Description: Community Supported Agriculture (CSA) contracts allow consumers to buy claims on a farm's future production. In turn, the consumer provides working capital to the farm during the growing season. CSA contracts also provide risk management for farmers with limited access to Federal crop insurance by transferring part of the farm's risk to the consumer. We derive a theory of CSA contract pricing for the two most prevalent types of CSA contracts: yield contracts, in which consumers receive a percentage of the farm's production, and weight contracts, in which consumers receive fixed quantities. We develop a two-period model in which expected utility maximizing producers and consumers engage in CSA contracting in the first period based on anticipation of yields and spot prices in the second period. Using the model, we generate several testable hypotheses to be explored in future research. Additionally, we present an overview of the data necessary to test the propositions and potential challenges that might arise in related empirical work.
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q14 - Agricultural Finance
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    LARVA: an integrative framework for large-scale analysis of recurrent variants in noncoding annotations (2015)
    Oxford University Press
    Details
    Publication Date: 2015-09-30
    Description: In cancer research, background models for mutation rates have been extensively calibrated in coding regions, leading to the identification of many driver genes, recurrently mutated more than expected. Noncoding regions are also associated with disease; however, background models for them have not been investigated in as much detail. This is partially due to limited noncoding functional annotation. Also, great mutation heterogeneity and potential correlations between neighboring sites give rise to substantial overdispersion in mutation count, resulting in problematic background rate estimation. Here, we address these issues with a new computational framework called LARVA. It integrates variants with a comprehensive set of noncoding functional elements, modeling the mutation counts of the elements with a β-binomial distribution to handle overdispersion. LARVA, moreover, uses regional genomic features such as replication timing to better estimate local mutation rates and mutational hotspots. We demonstrate LARVA's effectiveness on 760 whole-genome tumor sequences, showing that it identifies well-known noncoding drivers, such as mutations in the TERT promoter. Furthermore, LARVA highlights several novel highly mutated regulatory sites that could potentially be noncoding drivers. We make LARVA available as a software tool and release our highly mutated annotations as an online resource ( larva.gersteinlab.org ).
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    The Economics of Wine, Weather, and Climate Change (2016)
    Oxford University Press
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    Publication Date: 2016-02-03
    Description: In this article, we provide an overview of the extensive literature on the impact of weather and climate on grapes and wine, with the goal of identifying how climate change is likely to affect their production. We first discuss the physical impact of weather on vine phenology (i.e., the timing of biological events such as bud break or flowering), berry composition, and yields. Then we examine the economic literature that measures the effects of temperature on wine quality, prices, costs, and profits and, based on this review, infer how climate change will affect these variables. We also describe what has been learned thus far about possible adaptation strategies for grape growers that would allow them to mitigate the economic effects of climate change. We conclude that climate change is likely to produce both winners and losers, with the winners being those located closer to the North and South Poles. There are also likely to be some substantial short-run costs as growers adapt to climate change. Nevertheless, wine making has survived through thousands of years of recorded history, a history that has included significant climate changes. ( JEL : Q13, Q18, Q54)
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy, Q54 - Climate ; Natural Disasters ; Global Warming
    Print ISSN: 1750-6816
    Electronic ISSN: 1750-6824
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Political Science , Economics
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    Beegle: from literature mining to disease-gene discovery (2016)
    Oxford University Press
    Details
    Publication Date: 2016-01-30
    Description: Disease-gene identification is a challenging process that has multiple applications within functional genomics and personalized medicine. Typically, this process involves both finding genes known to be associated with the disease (through literature search) and carrying out preliminary experiments or screens (e.g. linkage or association studies, copy number analyses, expression profiling) to determine a set of promising candidates for experimental validation. This requires extensive time and monetary resources. We describe Beegle , an online search and discovery engine that attempts to simplify this process by automating the typical approaches. It starts by mining the literature to quickly extract a set of genes known to be linked with a given query, then it integrates the learning methodology of Endeavour (a gene prioritization tool) to train a genomic model and rank a set of candidate genes to generate novel hypotheses. In a realistic evaluation setup, Beegle has an average recall of 84% in the top 100 returned genes as a search engine, which improves the discovery engine by 12.6% in the top 5% prioritized genes. Beegle is publicly available at http://beegle.esat.kuleuven.be/ .
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    A computational method for studying the relation between alternative splicing and DNA methylation (2016)
    Oxford University Press
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    Publication Date: 2016-01-30
    Description: Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed. We design a flexible self-organizing map approach to pattern grouping. Exemplary application on available data sets indicates that stable patterns which correlate non-trivially with exon inclusion do indeed exist. To improve the reliability of these predictions, further studies on larger data sets will be required. We have thus taken great care that our software runs efficiently on modern hardware, so that it can support future studies on large-scale data sets.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    BubbleTree: an intuitive visualization to elucidate tumoral aneuploidy and clonality using next generation sequencing data (2016)
    Oxford University Press
    Details
    Publication Date: 2016-03-01
    Description: Tumors are characterized by properties of genetic instability, heterogeneity, and significant oligoclonality. Elucidating this intratumoral heterogeneity is challenging but important. In this study, we propose a framework, BubbleTree, to characterize the tumor clonality using next generation sequencing (NGS) data. BubbleTree simultaneously elucidates the complexity of a tumor biopsy, estimating cancerous cell purity, tumor ploidy, allele-specific copy number, and clonality and represents this in an intuitive graph. We further developed a three-step heuristic method to automate the interpretation of the BubbleTree graph, using a divide-and-conquer strategy. In this study, we demonstrated the performance of BubbleTree with comparisons to similar commonly used tools such as THetA2, ABSOLUTE, AbsCN-seq and ASCAT, using both simulated and patient-derived data. BubbleTree outperformed these tools, particularly in identifying tumor subclonal populations and polyploidy. We further demonstrated BubbleTree's utility in tracking clonality changes from patients’ primary to metastatic tumor and dating somatic single nucleotide and copy number variants along the tumor clonal evolution. Overall, the BubbleTree graph and corresponding model is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in human tumors. BubbleTree is R-based and freely available to the research community ( https://www.bioconductor.org/packages/release/bioc/html/BubbleTree.html ).
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    Somatic cell counts in dairy marketing: quantile regression for count data (2016)
    Oxford University Press
    Details
    Publication Date: 2016-02-20
    Description: We study the determinants of somatic cell count (SCC) for farm milk among US dairies. We synthesise much of the work that has been done to model SCC determinants in order to identify the potential impacts of buyer-imposed penalties and incentives within the supply chain. Additionally, we estimate quantile regression for count data to measure impacts specifically for those operations with the highest SCC and to account for the statistical properties of the data. Premiums in particular have the potential to reduce SCC considerably where it is currently the highest. We draw implications for profitability in relation to SCC reduction.
    Keywords: C25 - Discrete Regression and Qualitative Choice Models, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q16 - R&D ; Agricultural Technology ; Agricultural Extension Services
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Producer heterogeneity and voting power in mandatory US agricultural marketing organisations (2015)
    Oxford University Press
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    Publication Date: 2015-10-31
    Description: We consider how cost heterogeneity and market power affect voting power in producer referenda for mandatory agricultural marketing organisations with generic promotion programmes in the United States. We measure voting power using the Banzhaf Power Index and propose a new version of this index based on the profit-maximising theory of the firm that provides an improved estimate of voting power. Examining several types of demand shifts and voting rules, we find that both Banzhaf Power and our new measure vary considerably depending on the market structure and level of cost heterogeneity.
    Keywords: D71 - Social Choice ; Clubs ; Committees ; Associations, D72 - Models of Political Processes: Rent-Seeking, Elections, Legislatures, and Voting Behavior, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Discovery and characterization of Alu repeat sequences via precise local read assembly (2015)
    Oxford University Press
    Details
    Publication Date: 2015-12-02
    Description: Alu insertions have contributed to 〉11% of the human genome and ~30–35 Alu subfamilies remain actively mobile, yet the characterization of polymorphic Alu insertions from short-read data remains a challenge. We build on existing computational methods to combine Alu detection and de novo assembly of WGS data as a means to reconstruct the full sequence of insertion events from Illumina paired end reads. Comparison with published calls obtained using PacBio long-reads indicates a false discovery rate below 5%, at the cost of reduced sensitivity due to the colocation of reference and non-reference repeats. We generate a highly accurate call set of 1614 completely assembled Alu variants from 53 samples from the Human Genome Diversity Project (HGDP) panel. We utilize the reconstructed alternative insertion haplotypes to genotype 1010 fully assembled insertions, obtaining 〉99% agreement with genotypes obtained by PCR. In our assembled sequences, we find evidence of premature insertion mechanisms and observe 5' truncation in 16% of Alu Ya5 and Alu Yb8 insertions. The sites of truncation coincide with stem-loop structures and SRP9/14 binding sites in the Alu RNA, implicating L1 ORF2p pausing in the generation of 5' truncations. Additionally, we identified variable Alu J and Alu S elements that likely arose due to non-retrotransposition mechanisms.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    A mostly traditional approach improves alignment of bisulfite-converted DNA (2012)
    Oxford University Press
    Details
    Publication Date: 2012-07-22
    Description: Cytosines in genomic DNA are sometimes methylated. This affects many biological processes and diseases. The standard way of measuring methylation is to use bisulfite, which converts unmethylated cytosines to thymines, then sequence the DNA and compare it to a reference genome sequence. We describe a method for the critical step of aligning the DNA reads to the correct genomic locations. Our method builds on classic alignment techniques, including likelihood-ratio scores and spaced seeds. In a realistic benchmark, our method has a better combination of sensitivity, specificity and speed than nine other high-throughput bisulfite aligners. This study enables more accurate and rational analysis of DNA methylation. It also illustrates how to adapt general-purpose alignment methods to a special case with distorted base patterns: this should be informative for other special cases such as ancient DNA and AT-rich genomes.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    PhiSpy: a novel algorithm for finding prophages in bacterial genomes that combines similarity- and composition-based strategies (2012)
    Oxford University Press
    Details
    Publication Date: 2012-09-13
    Description: Prophages are phages in lysogeny that are integrated into, and replicated as part of, the host bacterial genome. These mobile elements can have tremendous impact on their bacterial hosts’ genomes and phenotypes, which may lead to strain emergence and diversification, increased virulence or antibiotic resistance. However, finding prophages in microbial genomes remains a problem with no definitive solution. The majority of existing tools rely on detecting genomic regions enriched in protein-coding genes with known phage homologs, which hinders the de novo discovery of phage regions. In this study, a weighted phage detection algorithm, PhiSpy was developed based on seven distinctive characteristics of prophages, i.e. protein length, transcription strand directionality, customized AT and GC skew, the abundance of unique phage words, phage insertion points and the similarity of phage proteins. The first five characteristics are capable of identifying prophages without any sequence similarity with known phage genes. PhiSpy locates prophages by ranking genomic regions enriched in distinctive phage traits, which leads to the successful prediction of 94% of prophages in 50 complete bacterial genomes with a 6% false-negative rate and a 0.66% false-positive rate.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Exploiting mid-range DNA patterns for sequence classification: binary abstraction Markov models (2012)
    Oxford University Press
    Details
    Publication Date: 2012-06-06
    Description: Messenger RNA sequences possess specific nucleotide patterns distinguishing them from non-coding genomic sequences. In this study, we explore the utilization of modified Markov models to analyze sequences up to 44 bp, far beyond the 8-bp limit of conventional Markov models, for exon/intron discrimination. In order to analyze nucleotide sequences of this length, their information content is first reduced by conversion into shorter binary patterns via the application of numerous abstraction schemes. After the conversion of genomic sequences to binary strings, homogenous Markov models trained on the binary sequences are used to discriminate between exons and introns. We term this approach the Binary Abstraction Markov Model (BAMM). High-quality abstraction schemes for exon/intron discrimination are selected using optimization algorithms on supercomputers. The best MM classifiers are then combined using support vector machines into a single classifier. With this approach, over 95% classification accuracy is achieved without taking reading frame into account. With further development, the BAMM approach can be applied to sequences lacking the genetic code such as ncRNAs and 5'-untranslated regions.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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    New methods for finding common insertion sites and co-occurring common insertion sites in transposon- and virus-based genetic screens (2012)
    Oxford University Press
    Details
    Publication Date: 2012-05-13
    Description: Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Modelling pig sector dynamic adjustment to livestock epidemics with stochastic-duration trade disruptions (2011)
    Oxford University Press
    Details
    Publication Date: 2011-11-24
    Description: We use a stochastic dynamic programming model to simulate the market implications of alternative foot and mouth disease scenarios in the Finnish pig sector. The model considers the dynamics of animal stock adjustment and price movements when the duration of export disruptions is unknown. Explicit treatment of these issues is crucial in the economic analysis of livestock epidemics, especially if there is a risk of a prolonged export ban. Results suggest that the risk of a prolonged ban increases disease losses considerably. It also increases economic benefits from production adjustments.
    Keywords: C61 - Optimization Techniques ; Programming Models ; Dynamic Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Is embedding entailed in consumer valuation of food safety characteristics? (2011)
    Oxford University Press
    Details
    Publication Date: 2011-11-24
    Description: Consumers' preferences for food safety characteristics are investigated with a particular focus on the existence of an embedding effect. Embedding exists if consumer valuation of food safety is insensitive to scope. We conduct between-attribute external tests for embedding in two choice experiments concerning the value of food safety attributes in minced pork and chicken breasts. We find no evidence of embedding neither when using food safety attributes that are not close substitutes and which exhibit both private and public good characteristics, nor when using food safety attributes that are closer substitutes and which have primarily private good characteristics.
    Keywords: Q10 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Intangible expenses: a solution to increase the French wine industry performance? (2011)
    Oxford University Press
    Details
    Publication Date: 2011-11-24
    Description: This paper presents an empirical investigation of the link between intangible expenses of French wine companies and their financial performance. A flexible moment-based approach is used to analyse the impact of tangible and intangible expenses on the mean, variance and skewness of profit. Econometric evidence shows that a high level of intangible expenses has a positive impact on performance by increasing the expected profit and reducing variance risk. A lower level of intangible expenses reduces risk and mean of profit of corporations. This study provides insights on the use of intangible expenses as a risk management tool.
    Keywords: G32 - Financing Policy ; Financial Risk and Risk Management ; Capital and Ownership Structure, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Consumer inferences of food safety and quality (2011)
    Oxford University Press
    Details
    Publication Date: 2011-11-24
    Description: Economists frequently use choice experiments (CEs) to evaluate demand for new attributes in food products. Using a split-sample experimental design focused on demand for pork chop attributes, we find consumer inferences regarding food safety and quality to impact estimates of marginal willingness to pay, market participation, policy appropriateness and consumer welfare effects. Our results suggest that interpretation of findings should be noted as conditional on attributes included in original analyses. A split-sample experimental approach involving multiple CE designs is described and suggested to practitioners to better consider consumer inference effects in future studies.
    Keywords: B40 - General, D12 - Consumer Economics: Empirical Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Consumers' preferences for geographical origin labels: evidence from the Canadian olive oil market (2011)
    Oxford University Press
    Details
    Publication Date: 2011-11-24
    Description: Geographical origin labels are important information and marketing tools and have recently become a central component of EU agricultural promotion. We consider demand in a non-EU export market for two distinct label types: country of origin (COO) and geographical indications (GIs). Additionally, two types of GIs, ‘protected designations of origin’ (PDOs) and ‘protected GIs’ (PGIs) are considered. Empirical findings indicate consumers’ willingness to pay varies with the oil's COO and is greater for GIs than for non-GIs from a given country. Weaker evidence that consumers value PDOs more than PGIs is also found.
    Keywords: C25 - Discrete Regression and Qualitative Choice Models, D12 - Consumer Economics: Empirical Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Chain interdependencies, measurement problems and efficient governance structure: cooperatives versus publicly listed firms (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-08
    Description: We determine the circumstances when the absence of public listing, often believed to be a disadvantage, makes a cooperative the unique efficient governance structure. This is established in a multi-task principal–agent model, capturing that cooperatives are not publicly listed and their CEOs have to bring the downstream enterprise to value as well as to serve upstream member interests. Not having a public listing prevents the CEO from choosing the level of the downstream activities too high. Cooperatives are uniquely efficient when the upstream marginal product multiplied with a function increasing in the strength of the chain complementarities is higher than the downstream marginal product.
    Keywords: D21 - Firm Behavior, L23 - Organization of Production, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Is producing a private label counterproductive for a branded manufacturer? (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-08
    Description: Branded food manufacturers vindicate the use of excess production capacities to justify their production of retailers’ brands. We study the distributor's and food manufacturer's private label (PL) strategy for production within a framework featuring endogenous store brand quality, bargaining power, possible differences in production technology and potential capacity constraints for the branded manufacturer. Depending on the structure of capacity constraint (applying to both products or to the PL only), we find that the retailer may prefer to choose an independent firm for the production of the store brand whereas the branded manufacturer is chosen in the case of excess capacity.
    Keywords: L11 - Production, Pricing, and Market Structure ; Size Distribution of Firms, L13 - Oligopoly and Other Imperfect Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Cooperation against theft: A test of incentives for water management In Tunisia (2014)
    Oxford University Press
    Details
    Publication Date: 2014-01-22
    Description: Water theft carried out by manipulating water meters constrains volumetric pricing in semi-arid regions. Cooperative management can reduce theft and improve incentives for efficient water use by inducing peer monitoring. Using a theoretical model, we show that theft is more likely when prices are high, punishments are weak, and cooperatives are large. We also show how cooperative membership and punishment levels are determined endogenously by constraints on monitoring. We test the model on data from Tunisia for the years 2001–2003, relying on instruments that proxy for unobservable monitoring costs. The results confirm that well-designed incentives can reduce theft, and that constraints on monitoring costs affect institutional design.
    Keywords: D82 - Asymmetric and Private Information, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation, Q25 - Water
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes (2014)
    Oxford University Press
    Details
    Publication Date: 2014-05-01
    Description: Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based classification-system), a novel computational approach to derive and then transfer gene-signatures from one analytical platform to another. We applied PIGExClass to design a reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) based molecular-subtyping assay for glioblastoma multiforme (GBM), the most aggressive primary brain tumors. Unsupervised clustering of TCGA (the Cancer Genome Altas Consortium) GBM samples, based on isoform-level gene-expression profiles, recaptured the four known molecular subgroups but switched the subtype for 19% of the samples, resulting in significant ( P = 0.0103) survival differences among the refined subgroups. PIGExClass derived four-class classifier, which requires only 121 transcript-variants, assigns GBM patients’ molecular subtype with 92% accuracy. This classifier was translated to an RT-qPCR assay and validated in an independent cohort of 206 GBM samples. Our results demonstrate the efficacy of PIGExClass in the design of clinically adaptable molecular subtyping assay and have implications for developing robust diagnostic assays for cancer patient stratification.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    fourSig: a method for determining chromosomal interactions in 4C-Seq data (2014)
    Oxford University Press
    Details
    Publication Date: 2014-05-01
    Description: The ability to correlate chromosome conformation and gene expression gives a great deal of information regarding the strategies used by a cell to properly regulate gene activity. 4C-Seq is a relatively new and increasingly popular technology where the set of genomic interactions generated by a single point in the genome can be determined. 4C-Seq experiments generate large, complicated data sets and it is imperative that signal is properly distinguished from noise. Currently, there are a limited number of methods for analyzing 4C-Seq data. Here, we present a new method, fourSig , which in addition to being precise and simple to use also includes a new feature that prioritizes detected interactions. Our results demonstrate the efficacy of fourSig with previously published and novel 4C-Seq data sets and show that our significance prioritization correlates with the ability to reproducibly detect interactions among replicates.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    The Behavior of Bid-Ask Spreads in the Electronically-Traded Corn Futures Market (2014)
    Oxford University Press
    Details
    Publication Date: 2014-03-21
    Description: This is the first paper to analyze liquidity costs in agricultural futures markets based on the observed bid-ask spread (BAS) faced by market participants. The results reveal a highly liquid corn market that mostly offers order execution at minimum cost. The BAS responds negatively to volume and positively to price volatility, but also affects volume traded and price volatility. While statistically significant, these responses on a cents/bushel or a percentage basis are generally small. Liquidity costs are also virtually impervious to short-term changes in demand for spreading and trend-following trader activity, as well as differences from day-of-the-week changes in market activity. Much larger cents/bushel and percentage changes in BAS occur during commodity index trader roll periods and on USDA report release days. The roll period findings indicate a sunshine trading effect, while announcement effects identify the importance of unexpected information and adverse selection on order execution costs. Overall, our research demonstrates that the transition to electronic trading in the corn futures market has led to low and stable liquidity costs, despite the market turbulence in 2008–2009.
    Keywords: C36- Instrumental Variables (IV) Estimation, G12 - Asset Pricing ; Trading volume ; Bond Interest Rates, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Angel Investment and Collective Agricultural Marketing: The Case of the Minnesota Food Network (2014)
    Oxford University Press
    Details
    Publication Date: 2014-03-21
    Description: The Minnesota Food Network is a limited liability company comprised of 52 farmers producing a variety of high-quality, sustainably produced agricultural products in southern Minnesota. The network's goal is to develop a regional food system to provide locally grown food at a price that "is fair" to both consumers and producers. This case outlines the challenges that the network faces in their efforts to expand to take advantage of a market opportunity. One of their biggest challenges is that they face high operating costs because of their disaggregated distribution system and need to purchase a distribution and storage facility and two vehicles. They will fund the purchase of a building through an angel investor. An angel investor is necessary because the network cannot sustain traditional loan payments in its current form. Students are asked to consider a number of questions pertaining to the decisions in this case outlined in the final section of the case study.
    Keywords: A22 - Undergraduate, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Social Networks and New Product Choice (2014)
    Oxford University Press
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    Publication Date: 2014-03-21
    Description: To successfully market new products in a social network it is essential to identify influential individuals whose product recommendations influence the consumption choices of their peers. In this study, we use spatial econometric methods to determine how individuals revise their preferences for product attributes when exposed to product recommendations from peers, and how different individuals who vary in their degree of network connectedness exert influence on the product choices of others. We find evidence that consumers look to others for guidance from peers in their preference for subjective, taste-specific parameters, but tend not to respond to peer price choices. Our spatial methods allow us to empirically determine the influence exerted by individual members on the consumption choices of other members of the social network. We find that connected members of the social network are not always the most influential in revising the consumption choices of others. Our estimates reveal that network proximity explains only 8.8% of influence.
    Keywords: D12 - Consumer Economics: Empirical Analysis, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    High-resolution functional annotation of human transcriptome: predicting isoform functions by a novel multiple instance-based label propagation method (2014)
    Oxford University Press
    Details
    Publication Date: 2014-04-03
    Description: Alternative transcript processing is an important mechanism for generating functional diversity in genes. However, little is known about the precise functions of individual isoforms. In fact, proteins (translated from transcript isoforms), not genes, are the function carriers. By integrating multiple human RNA-seq data sets, we carried out the first systematic prediction of isoform functions, enabling high-resolution functional annotation of human transcriptome. Unlike gene function prediction, isoform function prediction faces a unique challenge: the lack of the training data—all known functional annotations are at the gene level. To address this challenge, we modelled the gene–isoform relationships as multiple instance data and developed a novel label propagation method to predict functions. Our method achieved an average area under the receiver operating characteristic curve of 0.67 and assigned functions to 15 572 isoforms. Interestingly, we observed that different functions have different sensitivities to alternative isoform processing, and that the function diversity of isoforms from the same gene is positively correlated with their tissue expression diversity. Finally, we surveyed the literature to validate our predictions for a number of apoptotic genes. Strikingly, for the famous ‘TP53’ gene, we not only accurately identified the apoptosis regulation function of its five isoforms, but also correctly predicted the precise direction of the regulation.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Behavioral Responses and the Impact of New Agricultural Technologies: Evidence from a Double-blind Field Experiment in Tanzania (2014)
    Oxford University Press
    Details
    Publication Date: 2014-04-05
    Description: Randomized controlled trials (RCTs) in the social sciences are typically not double-blind, so participants know they are "treated" and will adjust their behavior accordingly. Such effort responses complicate the assessment of impact. To gauge the potential magnitude of effort responses we implement a conventional RCT and double-blind trial in rural Tanzania, and randomly allocate modern and traditional cowpea seed varieties to a sample of farmers. Effort responses can be quantitatively important—for our case they explain the entire "treatment effect on the treated" as measured in a conventional economic RCT. Specifically, harvests are the same for people who know they received the modern seeds and for people who did not know what type of seeds they got; however, people who knew they had received the traditional seeds did much worse. Importantly, we also find that most of the behavioral response is unobserved by the analyst, or at least not readily captured using coarse, standard controls.
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Efficient large-scale protein sequence comparison and gene matching to identify orthologs and co-orthologs (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-29
    Description: Broadly, computational approaches for ortholog assignment is a three steps process: (i) identify all putative homologs between the genomes, (ii) identify gene anchors and (iii) link anchors to identify best gene matches given their order and context. In this article, we engineer two methods to improve two important aspects of this pipeline [specifically steps (ii) and (iii)]. First, computing sequence similarity data [step (i)] is a computationally intensive task for large sequence sets, creating a bottleneck in the ortholog assignment pipeline. We have designed a fast and highly scalable sort-join method (afree) based on k -mer counts to rapidly compare all pairs of sequences in a large protein sequence set to identify putative homologs. Second, availability of complex genomes containing large gene families with prevalence of complex evolutionary events, such as duplications, has made the task of assigning orthologs and co-orthologs difficult. Here, we have developed an iterative graph matching strategy where at each iteration the best gene assignments are identified resulting in a set of orthologs and co-orthologs. We find that the afree algorithm is faster than existing methods and maintains high accuracy in identifying similar genes. The iterative graph matching strategy also showed high accuracy in identifying complex gene relationships. Standalone afree available from http://vbc.med.monash.edu.au/~kmahmood/afree . EGM2, complete ortholog assignment pipeline (including afree and the iterative graph matching method) available from http://vbc.med.monash.edu.au/~kmahmood/EGM2 .
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    The allele distribution in next-generation sequencing data sets is accurately described as the result of a stochastic branching process (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-29
    Description: With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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    Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition (2012)
    Oxford University Press
    Details
    Publication Date: 2012-03-14
    Description: An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Structural change in European calf markets: decoupling and the blue tongue disease (2011)
    Oxford University Press
    Details
    Publication Date: 2011-12-27
    Description: European cattle markets have recently undergone significant change. We explore the simultaneous impacts of agricultural policy reform and the occurrence of an animal health crisis on spatial interdependencies of calf prices of four major European Union markets. The markets are found to be integrated. Price shocks are rapidly absorbed. We find that the member state specific implementations of the 2003 Common Agricultural Policy reforms significantly affected prices of both the national market and of other member states. The blue tongue disease further induced structural change. Using counterfactual scenarios, we show that the decoupling of payments from production led to reduced calf prices.
    Keywords: C32 - Time-Series Models, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
    Published by Oxford University Press
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    NTRFinder: a software tool to find nested tandem repeats (2012)
    Oxford University Press
    Details
    Publication Date: 2012-02-17
    Description: We introduce the software tool NTRFinder to search for a complex repetitive structure in DNA we call a nested tandem repeat (NTR). An NTR is a recurrence of two or more distinct tandem motifs interspersed with each other. We propose that NTRs can be used as phylogenetic and population markers. We have tested our algorithm on both real and simulated data, and present some real NTRs of interest. NTRFinder can be downloaded from http://www.maths.otago.ac.nz/~aamatroud/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    sPARTA: a parallelized pipeline for integrated analysis of plant miRNA and cleaved mRNA data sets, including new miRNA target-identification software (2014)
    Oxford University Press
    Details
    Publication Date: 2014-10-10
    Description: Parallel analysis of RNA ends (PARE) is a technique utilizing high-throughput sequencing to profile uncapped, mRNA cleavage or decay products on a genome-wide basis. Tools currently available to validate miRNA targets using PARE data employ only annotated genes, whereas important targets may be found in unannotated genomic regions. To handle such cases and to scale to the growing availability of PARE data and genomes, we developed a new tool, ‘ sPARTA ’ (small RNA-PARE target analyzer) that utilizes a built-in, plant-focused target prediction module (aka ‘ miRferno ’). sPARTA not only exhibits an unprecedented gain in speed but also it shows greater predictive power by validating more targets, compared to a popular alternative. In addition, the novel ‘seed-free’ mode, optimized to find targets irrespective of complementarity in the seed-region, identifies novel intergenic targets. To fully capitalize on the novelty and strengths of sPARTA , we developed a web resource, ‘ comPARE ’, for plant miRNA target analysis; this facilitates the systematic identification and analysis of miRNA-target interactions across multiple species, integrated with visualization tools. This collation of high-throughput small RNA and PARE datasets from different genomes further facilitates re-evaluation of existing miRNA annotations, resulting in a ‘cleaner’ set of microRNAs.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    A statistical model of ChIA-PET data for accurate detection of chromatin 3D interactions (2014)
    Oxford University Press
    Details
    Publication Date: 2014-10-10
    Description: Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    COMET: adaptive context-based modeling for ultrafast HIV-1 subtype identification (2014)
    Oxford University Press
    Details
    Publication Date: 2014-10-10
    Description: Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Large-scale modeling of condition-specific gene regulatory networks by information integration and inference (2014)
    Oxford University Press
    Details
    Publication Date: 2014-11-28
    Description: Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE ( http://mips.helmholtz-muenchen.de/cogere ), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient 2 (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Gone in Ten Minutes: Intraday Evidence of Announcement Effects in the Electronic Corn Futures Market (2014)
    Oxford University Press
    Details
    Publication Date: 2014-09-06
    Description: This article investigates the announcement effects of major USDA reports using intraday Chicago Board of Trade corn futures prices and trading volume from the electronic trading platform for July 2009 to May 2012. Focusing on intraday market reactions, we analyze the extent to which new information impacts and is rapidly reflected in prices. Results show that USDA reports contain substantial information for market participants. Strongest price reactions to the releases are found immediately after the market opens, and market reactions persist for approximately ten minutes. The electronic corn futures market quickly incorporates this new public information, and little evidence exists to support systematic under- or overreactions in prices. Other more subtle reactions occur in the last trading session before USDA announcements as traders adjust their market exposure in anticipation of the release.
    Keywords: D80 - General, G14 - Information and Market Efficiency ; Event Studies, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Determinants of Occupational Safety for Agribusiness Workers (2014)
    Oxford University Press
    Details
    Publication Date: 2014-09-06
    Description: Increases in crop yields and changing cropping patterns have placed stress on agribusiness handling and storage facilities. The objective of this research is to gain insight into the relationship between safety culture and safety performance, and to identify the determinants of safety culture in agribusinesses. The research suggests that investments in labor inputs such as increased training, consistent discipline, and recognition of safety achievements all increase safety culture. Furthermore, improvements in employee perceptions of safety culture have a positive impact on reducing employee injuries. Congress has recently funded nine centers to work on occupational health and safety research in agriculture, fisheries, and forestry.
    Keywords: J43 - Agricultural Labor Markets, L66 - Food ; Beverages ; Cosmetics ; Tobacco ; Wine and Spirits, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    Futures Market Failure? (2014)
    Oxford University Press
    Details
    Publication Date: 2014-12-13
    Description: In a well-functioning futures market, the futures price at expiration equals the price of the underlying asset. This condition failed to hold in grain markets for most of 2005-2010, calling into question the ability of these markets to perform their price discovery and risk management functions. During this period, futures contracts expired up to 35% above the cash grain price. We develop a dynamic rational expectations model of commodity storage that explains how these recent convergence failures were generated by the institutional structure of the delivery system. When delivery occurs on a grain futures contract, the firm on the short side of the market provides a delivery instrument (a warehouse receipt or shipping certificate) to the firm on the long side of the market. The firm taking delivery may hold the delivery instrument indefinitely, providing it pays a daily storage rate. The futures exchange sets the maximum allowable storage rate at a fixed value. We show that non-convergence arises in equilibrium when the market price of physical grain storage exceeds the maximum storage rate on delivery instruments. We call the difference between the price of carrying physical grain and the maximum storage rate the wedge , and demonstrate theoretically and empirically that the magnitude of the non-convergence equals the expected present discounted value of a function of future wedges.
    Keywords: G13 - Contingent Pricing ; Futures Pricing, G14 - Information and Market Efficiency ; Event Studies, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    ptRNApred: computational identification and classification of post-transcriptional RNA (2014)
    Oxford University Press
    Details
    Publication Date: 2014-12-17
    Description: Non-coding RNAs (ncRNAs) are known to play important functional roles in the cell. However, their identification and recognition in genomic sequences remains challenging. In silico methods, such as classification tools, offer a fast and reliable way for such screening and multiple classifiers have already been developed to predict well-defined subfamilies of RNA. So far, however, out of all the ncRNAs, only tRNA, miRNA and snoRNA can be predicted with a satisfying sensitivity and specificity. We here present ptRNApred , a tool to detect and classify subclasses of non-coding RNA that are involved in the regulation of post-transcriptional modifications or DNA replication, which we here call post-transcriptional RNA (ptRNA). It (i) detects RNA sequences coding for post-transcriptional RNA from the genomic sequence with an overall sensitivity of 91% and a specificity of 94% and (ii) predicts ptRNA-subclasses that exist in eukaryotes: snRNA, snoRNA, RNase P, RNase MRP, Y RNA or telomerase RNA. AVAILABILITY: The ptRNApred software is open for public use on http://www.ptrnapred.org/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    The eSNV-detect: a computational system to identify expressed single nucleotide variants from transcriptome sequencing data (2014)
    Oxford University Press
    Details
    Publication Date: 2014-12-17
    Description: Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6–96.8% precision and 91.6–95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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    Price Explosiveness, Speculation, and Grain Futures Prices (2014)
    Oxford University Press
    Details
    Publication Date: 2014-12-13
    Description: A recently developed testing procedure is used to detect and date-stamp explosive episodes ("bubbles") in corn, soybean, and wheat futures markets during 2004–2013. We find that the markets experienced price explosiveness only approximately two percent of the time and, when bubbles do occur, they are generally short-lived and small in magnitude. The correspondence between observed price spikes and bubbles is rather low, with a large portion of the price explosiveness occurring during downward price movements. Commodity index trader positions do not significantly affect the probability of a positive bubble occurring in grain futures markets, which directly contradicts the argument (the "Masters Hypothesis") that waves of index investment distorted underlying supply-and-demand relationships and led to a series of massive bubbles in agricultural futures markets. In addition, commodity index trader positions tend to reduce negative bubble occurrence, while general speculative activity as measured by Working's T reduces the probability of a positive bubble. There is some evidence that the positions of noncommercial traders have a direct effect on positive bubble occurrence, but the effect declines when accounting for the composition of other traders in the market. Overall, speculation has little effect or negative effects on price explosiveness. Finally, positive bubbles are more likely to occur in the presence of low inventories, strong exports, a weak U.S. dollar, and booming economic growth, whereas negative bubbles are more likely to occur with large inventories, weak exports, and stagnant economic growth.
    Keywords: D84 - Expectations ; Speculations, G12 - Asset Pricing ; Trading volume ; Bond Interest Rates, G13 - Contingent Pricing ; Futures Pricing, G14 - Information and Market Efficiency ; Event Studies, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q41 - Demand and Supply
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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    China's Dairy United: A New Model for Milk Production (2015)
    Oxford University Press
    Details
    Publication Date: 2015-03-14
    Description: A milk scandal erupted in China in 2008 when the industrial chemical melamine was found in dairy products nationwide. While many Chinese dairy companies faced huge losses or bankruptcy as a result, one small firm, Dairy United, accelerated its development. Dairy United is one of the fastest-growing and most innovative Chinese dairy producers, one that features an unusual organizational structure and business model. Unlike most corporate and cooperative dairies that purchase cows on the market, Dairy United leases dairy cows from local farmers, giving it access to its primary asset without a large up-front investment, and letting the firm grow its dairy herds with newborn heifers. In return, farmers receive fixed payments biannually, but relinquish control rights and residual claims to the firm. Thus, Dairy United's leasing is helping transform Chinese milk production from a backyard, labor-intensive activity to a more industrialized mode of farming. The case is particularly interesting for understanding applications of agency theory in agribusiness.
    Keywords: A22 - Undergraduate, A23 - Graduate, D23 - Organizational Behavior ; Transaction Costs ; Property Rights, M10 - General, M20 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
    Published by Oxford University Press
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