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  • Computational Methods, Genomics  (140)
  • Food Policy  (110)
  • Oxford University Press  (250)
  • International Union of Crystallography (IUCr)
  • 1
    Publication Date: 2015-08-11
    Description: The Special Supplemental Nutrition Program for Women, Infants and Children (WIC) Program is a key part of America's safety net, but its structure fails to incentivize participants to be cost-conscious in their purchases and may cause retailers to attach excessive markups to WIC products. We investigate cost containment in the WIC Program, with a focus on California. Results show that smaller vendors often charge considerably higher prices for WIC foods than their larger counterparts. However, larger vendors do not mark up WIC foods more or promote them less than comparable control products. Cost containment can be improved by targeting WIC Program sales to larger vendors when it is possible to do so without compromising participant access, and using large-vendor prices as a benchmark to limit prices set by smaller vendors.
    Keywords: D12 - Consumer Economics: Empirical Analysis, I38 - Government Policy ; Provision and Effects of Welfare Programs, 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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  • 2
    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
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  • 3
    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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  • 4
    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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  • 5
    Publication Date: 2015-05-26
    Description: With the enactment of Regulation (EC) No. 1924/2006, 20 December 2006, ‘ On nutrition and health claims made on foods ’ several health claims can no longer be used on food products in European markets. We simulate the overall impact of the regulation on consumers and producers using the Italian yogurt market as a case study, and data prior to the introduction of the policy. We quantify welfare losses incurred if accepted claims were false, and simulate scenarios where rejected truthful health claims are removed, considering also the case where the products carrying them exit the market. We find that consumers can incur large welfare losses if approved claims are untruthful; if truthful claims are instead denied both consumers and producers may incur losses, with consumers being penalised more than producers.
    Keywords: L66 - Food ; Beverages ; Cosmetics ; Tobacco ; Wine and Spirits, M38 - Government Policy and Regulation, 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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  • 6
    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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  • 7
    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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  • 8
    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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  • 9
    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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  • 10
    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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  • 11
    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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  • 12
    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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  • 13
    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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  • 14
    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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  • 15
    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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  • 16
    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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  • 17
    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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  • 18
    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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  • 19
    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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  • 20
    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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  • 21
    Publication Date: 2015-05-12
    Description: China has long struggled to achieve food security. In the era of a planned economy, local self-sufficiency was dictated by policy. With China's transition to a market economy, however, different policy schemes have been utilized, with greater emphasis placed on the role of market forces, especially in conjunction with China's accession to the World Trade Organization in 2001. Nevertheless, self-sufficiency in grain production remains a deeply rooted goal, and interventionist measures geared towards its achievement are still viewed as the most direct and effective means of food security. This paper examines how the well-being of China's rural population, proxied by measures of food consumption, is affected by the promotion of grain production. Our findings suggest that targeted households bear a disproportionate burden of food security policy, as it is currently implemented.
    Keywords: O12 - Microeconomic Analyses of Economic Development, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 22
    Publication Date: 2015-05-12
    Description: Policymakers have dedicated increasing attention to whether Americans have access to healthful food. As a result, various methods for measuring food store access at the national level have been developed to identify areas that lack access. However, these methods face definitional, data, and methodological limitations. The focus on neighborhoods instead of individuals underestimates the barriers that some individuals face in accessing healthy food, and overestimates the problem in other neighborhoods. This paper reviews and critiques currently available national-level measures of food access. While multiple measures of food access are needed to understand the problem, we recommend greater attention be paid to individual measures of food store access.
    Keywords: I14 - Health and Inequality, I18 - Government Policy ; Regulation ; Public Health, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 23
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 24
    Publication Date: 2015-05-12
    Description: Household food insecurity in the United States has reached its highest levels to date. As public and private initiatives have emerged to help improve diets by fostering access to food, the availability of more food stores may result in lower levels of food insecurity. In this article, we assess the relationship between adult food insecurity and food store density in metropolitan areas of the United States. We find that while small grocery/convenience stores show a mitigating effect on adult food insecurity across different samples of households, the effects of large supermarkets/grocery stores and supercenters vary. We also find that Supplemental Nutrition Assistance Program participation and food access can have a simultaneously beneficial effect in reducing adult food insecurity. Implications for policies aiming to improve food security by fostering access to food stores are discussed.
    Keywords: I14 - Health and Inequality, L81 - Retail and Wholesale Trade ; e-Commerce, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 25
    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
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  • 26
    Publication Date: 2015-12-29
    Description: This article empirically investigates the impact of trade barriers on the world wine trade focusing on trade costs impeding exports, including transport, tariffs, technical barriers and sanitary and phytosanitary (SPS) standards. A gravity model is estimated using data from the main importing and exporting countries for the years 1997–2010. The Poison pseudo-maximum likelihood estimator accounts for heteroskedasticity and the presence of zero trade flows. Our results identify which regulations can adversely affect trade providing useful information to policy-makers involved in negotiations on trade frictions. While SPS measures do not seem to obstruct exports, technical barriers have a varying impact on trade. A decreasing trend for tariffs has largely been compensated by more stringent technical barriers. The overall result is that frictions in the world wine trade have not changed during the past 15 years.
    Keywords: F13 - Trade Policy ; International Trade Organizations, Q17 - Agriculture in International Trade, 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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  • 27
    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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  • 28
    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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  • 29
    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
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  • 30
    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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  • 31
    Publication Date: 2015-07-15
    Description: Although the importance of diet quality for improving child health is widely recognized, the roles of environmental factors and the absorption of nutrients for children's physical growth and morbidity have not been adequately integrated into a policy framework. Moreover, nutrient intakes gradually affect child health, so it is helpful to use alternative tools to evaluate short-term interventions versus long-term food policies. This article emphasizes the role of diet quality reflected in the intake of nutrients such as protein, calcium, and iron for children's physical growth. Vitamins A and C are important for reducing morbidity. Children's growth and morbidity affect their cognitive development, which is critical for the future supply of skilled labor and economic growth. Evidence on these issues from countries such as Bangladesh, India, Kenya, the Philippines, and Tanzania is summarized. The supply of nutritious foods is appraised from the viewpoint of improving diet quality. Finally, the roles of educational campaigns and indirect taxes on unhealthy processed foods consumed by the affluent in developing countries are discussed.
    Keywords: O12 - Microeconomic Analyses of Economic Development, I15 - Health and Economic Development, I25 - Education and Economic Development, J10 - General, Q01 - Sustainable Development, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0257-3032
    Electronic ISSN: 1564-6971
    Topics: Economics
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  • 32
    Publication Date: 2016-08-20
    Description: Concerns about the growing prevalence of obesity worldwide have led researchers and policy makers to investigate the potential health impact of fiscal policies such as taxes on unhealthy foods. A common instrument used to measure the relationship between food prices and food consumption is the price elasticity of demand. Using meta-regression analysis we assessed how differences in methodological approaches to estimating demand affected food price elasticities. Most methodological differences had a statistically significant impact on elasticity estimates, which stresses the importance of using meta-estimates or testing the sensitivity of simulation outcomes to a range of elasticity parameters before drawing policy conclusions.
    Keywords: D11 - Consumer Economics: Theory, H31 - Household, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 33
    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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  • 34
    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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  • 35
    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
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  • 36
    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
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  • 37
    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
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  • 38
    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
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  • 39
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 40
    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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  • 41
    Publication Date: 2016-07-09
    Description: If agricultural subsidies are largely capitalized into farmland values through their effect on rental rates, then expanding support for agriculture may not benefit farmers who rent the land they farm. Existing evidence on the incidence of subsidies on cash rental rates is mixed. Identification is obscured by unobserved or imprecisely measured factors that tend to be correlated with subsidies, especially land quality and time-varying factors like commodity prices and adverse weather events. A problem that has received less attention is the fact that subsidies and land quality on rented land may differ from owned land. Since most farms possess both rented and owned acreage, farm-level measures of subsidies, land values, and rental rates may bias estimated incidence. Using a new, field-level data set that, for the first time, precisely links subsidies to land parcels, we show that this bias is considerable: where farm-level estimates suggest an incidence of 42–49 cents of the marginal subsidy dollar, field-level estimates from the same farms indicate that landlords capture just 20–28 cents. The size of the farm and the duration of the rental arrangement have substantial effects. Incidence falls by 5–15 cents when doubling total operated acres, and the incidence falls by 0.1–0.8 cents with each additional year of the rental arrangement. Low incidence of subsidies on rents combined with the farm-size and duration effects suggest that farmers renting land have monopsony power.
    Keywords: H22 - Incidence, Q14 - Agricultural Finance, Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 42
    Publication Date: 2016-07-09
    Description: Many countries adjust their trade policies counter-cyclically with food prices, to the extent that the use of restrictions by food-exporting countries has occasionally threatened the food security of food-importing countries. These trade policies are inconsistent with the terms-of-trade motivation often retained to characterize the payoff frontier of self-enforcing trade agreements, as they can worsen the terms of trade of the countries that apply them. This article analyzes trade policy coordination when trade policies are driven by terms-of-trade effects and a desire to reduce domestic food price volatility. This framework implies that importing and exporting countries have incentives to deviate from cooperation at different periods: the latter when prices are high and the former when prices are low. Since staple food prices tend to have asymmetric distributions, with more prices below than above the mean but with occasional spikes, a self-enforcing agreement generates asymmetric outcomes. Without cooperation, an importing country uses its trade policy more frequently because of the concentration of prices below the mean, but an exporting country has a greater incentive to deviate from a cooperative trade policy because positive deviations from the mean price are larger than negative ones. Thus, the asymmetry of the distribution of commodity prices can make it more difficult to discipline export taxes than tariffs in trade agreements.
    Keywords: F13 - Trade Policy ; International Trade Organizations, Q17 - Agriculture in International Trade, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 43
    Publication Date: 2016-07-09
    Description: We analyze the effects of the interactions that the two pillars of the European Union Common Agricultural Policy—market support and rural development—have on farmers’ uptake of organic farming practices. Special attention is given to the 2003 reform, which substantially altered the relative importance of the two types of support by decoupling direct agricultural payments from the production of a specific crop. In our empirical analysis we study the case of Sweden, making use of the variation in the timing of farmers’ decisions regarding participation in support programs. We estimate a dynamic non-linear unobserved effects probit model to account for unobserved individual heterogeneity and state dependence. Our results indicate the existence of a negative effect of the market support system in place when organic farming techniques were adopted before the 2003 reform. However, this effect is reversed by the introduction of decoupling. Furthermore, the effects of support differ between certified and non-certified organic production: both pillars have significant effects on non-certified organic farming, whereas certified organic farming is exclusively driven by agro-environmental subsidies.
    Keywords: C23 - Models with Panel Data, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 44
    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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  • 45
    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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  • 46
    Publication Date: 2015-05-26
    Description: The European Union (EU) is the world's largest wine producer, as well as the world's most regulated wine market. In 2007, the EU decided on a major reform of its wine policy. A crucial element was the abolishment of a system of planting rights to limit the planting of vineyards. However, after intense lobbying by opponents of the liberalisation, this decision was reversed in 2013. Despite the importance of planting rights in European (and hence global) wine production, and despite the fierce debates surrounding the reforms, no model exists to study the effects of this policy. We develop the first theoretical model of planting rights, integrating the markets for land, planting rights and wine to analyse efficiency and distributional effects. We use the model to study the effects of differences among EU member states in restrictions on trade in planting rights, the role of government reserves and the impact of imperfect enforcement.
    Keywords: 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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  • 47
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    Oxford University Press
    Publication Date: 2015-04-18
    Description: The prospects for plant variety protection to deliver improved varieties of self-pollinating crops is assessed using the experience of the Australian wheat breeding sector as a natural experiment. The analysis is based on detailed new data on the agronomic performance of all wheat varieties released by Australian breeders between 1976 and 2011. The results indicate that plant variety protection, and associated reforms, led to a substantial fall in breeder output. Qualitative evidence indicates that this was caused by a combination of fewer research spillovers, lower release standards, and a possible fall in total investment in breeding.
    Keywords: O34 - Intellectual Property Rights, Q16 - R&D ; Agricultural Technology ; Agricultural Extension Services, Q18 - Agricultural Policy ; Food Policy
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  • 48
    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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  • 49
    Publication Date: 2015-02-11
    Description: Excess returns to producers insured by the Federal Crop Insurance Corporation can arise due to asymmetric information or from the design of the insurance programs themselves. Using unique, unit-level crop insurance contract data for major crops such as corn, soybeans, and wheat in five growing regions, we find evidence that producers in most regions may profit by selecting optional units, buy-up coverage, or by using transitional yields to participate in the federal crop insurance program. We also find evidence that advantages increase with land resource heterogeneity. However, the results do not support hypotheses that producers profit by selecting revenue insurance, nor that high levels of government "incompetence" exist in the design and administration of the crop insurance system.
    Keywords: Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 50
    Publication Date: 2015-02-11
    Description: We analyze the various welfare costs, transfers, trade, and employment consequences of the current U.S. sugar program for U.S. consumers, other sugar users, sugar refiners, cane and beet growing and processing industries, other associated agricultural sectors, and world markets. The removal of the sugar program would increase U.S. consumers' welfare by $2.9 to $3.5 billion each year and generate a modest job creation of 17,000 to 20,000 new jobs in food manufacturing and related industries. Imports of sugar containing products would fall dramatically, especially confectioneries substituting for domestic inputs under the sugar program. Sugar imports would rise substantially to 5–6 million short tons raw sugar equivalent. World sugar price increases would be minor, equivalent to about 1 cent per pound.
    Keywords: F13 - Trade Policy ; International Trade Organizations, Q17 - Agriculture in International Trade, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 51
    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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  • 52
    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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  • 53
    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
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  • 54
    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
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  • 55
    Publication Date: 2014-12-03
    Description: This study presents evidence from a survey and choice experiment on the preferences of Hispanic immigrants who entered the United States illegally for different immigration reform proposal attributes. Key components of the current competing US Senate and House immigration reform bills are considered including pathways to legal permanent residence, temporary work visas, family visitation rights, and access to medical care. The results quantify the value Hispanic immigrants place on different policy attributes and suggest that longer-term work visas are highly valued. Ability to legally work in the United States and a pathway to citizenship are substantially more valued than social services such as medical care and social security benefits.
    Keywords: J15 - Economics of Minorities and Races ; Non-labor Discrimination, K37 - Immigration Law, 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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  • 56
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 57
    Publication Date: 2015-07-10
    Description: This article argues that the structure of the Vietnamese rice export system is, in political economy terms, a rational response to the volatility present in the international rice market. In particular, it is argued that the Vietnamese Food Agency, along with VINAFOOD-1 and VINAFOOD-2, have been structured so that they can benefit from the domestic demands for export restrictions anticipated to occur as a consequence of international price volatility and the psychological demand of consumers for price stability. In turn, the actions of these agencies also contribute to international price volatility and the resulting demand for export restrictions. Since the political and economic elite in Vietnam obtain both political and economic power from this system, it is unlikely to be replaced with more effective and efficient policies to combat domestic price volatility. Thus, continued volatility in the price of rice can be expected.
    Keywords: N55 - Asia including Middle East, P26 - Political Economy ; Property Rights, Q17 - Agriculture in International Trade, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 58
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 59
    Publication Date: 2012-12-28
    Description: Sometimes, authorities are unable to rapidly identify the origin of a tainted product. In such cases, recalls or warnings often apply to all suppliers, even to those that had not contributed to the contamination. Traceability enables more targeted recalls by identifying the product's origin more specifically. In this article, we show how increased traceability protects the reputation of industries by limiting the size of recalls. We show the relationships between traceability and the level of food safety with many identical small farms in a competitive industry and for an industry using collective action to set rules and standards.
    Keywords: D21 - Firm Behavior, Q10 - General, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 60
    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
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  • 61
    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
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  • 62
    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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  • 63
    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
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  • 64
    Publication Date: 2012-08-03
    Description: This paper analyses the impact of the recent decision by the European Union to ‘decouple’ agricultural support payments from agricultural production on Irish farmers' land market decisions. The land market participation decisions of Irish farmers are modelled using a dynamic probit model, while the extent of participation decisions is modelled using a dynamic tobit model. Decoupling does not appear to have significantly altered farmers' land market decisions. One likely explanation for this is the cross-compliance obligation for farmers to maintain land in a state fit for agricultural production in order to receive their full payments.
    Keywords: Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 65
    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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  • 66
    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
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  • 67
    Publication Date: 2015-09-12
    Description: This article examines bilateral trade patterns in the Asia-Pacific using a new model in which comparative advantage within the agricultural sector is linked to agro-ecological characteristics, and trade costs are product-specific. Bilateral market share is a function of productivity and trade costs. However, countries with similar land and climate characteristics systematically have high productivity in similar products making them disproportionately sensitive to changes in each other's trade costs. We use a random coefficients logit model to estimate a parametric distribution of comparative advantage and trade costs across products and calculate regional trade liberalization elasticities for each exporter in each import market. Unlike most existing models, the value of the elasticity depends on the degree to which liberalization includes competitors with similar comparative advantage within the agricultural sector. We find disproportionately larger trade elasticities under China-led liberalization relative to U.S.-led liberalization among close U.S. competitors compared to countries whose agricultural products are unlikely to compete head-to-head with U.S. exports. For the United States, we find that the "lost opportunity" cost of exclusion from regional liberalization is increasing in the extent to which its close competitors gain new access.
    Keywords: F13 - Trade Policy ; International Trade Organizations, F14 - Country and Industry Studies of Trade, F15 - Economic Integration, Q17 - Agriculture in International Trade, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 68
    Publication Date: 2015-09-12
    Description: Contracts between farmers and intermediaries and crop insurers are important means for farmers to mitigate risks in modern U.S. agriculture. In this paper, we investigate the effect of crop insurance enrollment on contract terms and farmers’ participation in marketing contracts. Following Ligon (2003) , we set up a mechanism design framework to demonstrate an intermediary's contract design problem, where farmers are assumed to be utility maximizing agents. We depict farmers’ optimal choices of insurance coverage using the specification developed by Babcock (2012) . Our model shows that improved terms of crop insurance (lower premiums, higher subsidies) make contracts less appealing to farmers as mechanisms for mitigating risk. Therefore, intermediaries may revise their contract offers so that they are more attractive. However, improvements in contract terms are limited by their cost to the intermediaries and will not lead to expanded participation in contracts.
    Keywords: Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 69
    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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  • 70
    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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  • 71
    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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  • 72
    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
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  • 73
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 74
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    Oxford University Press
    Publication Date: 2015-11-06
    Description: I compare the distribution of risk attitudes of farm owners in the United States to nonfarm business owners and the general population using a measure of risk tolerance collected from national surveys. I find that farmers are significantly more tolerant of risk than the general population, though they are significantly less tolerant of risk than nonfarm business owners. Once demographic differences are controlled, farm and nonfarm business owners are more similar in their risk attitudes and both groups remain significantly more risk tolerant than the general population. First-generation farmers display greater risk tolerance than farmers who inherit operations from family members, as do farmers who have just begun operating a farm; neither pattern emerges among nonfarm business owners. The most risk tolerant farmers are young and male with larger operations, higher incomes, less formal education and close proximity to metropolitan centers. Among farmers, those with less diversified operations and those with specialty enterprises are more risk tolerant than other types of farmers. Crop farmers are less risk tolerant than fruit and vegetable farmers or farmers with specialty enterprises, while farmers who receive government payments or buy enterprise insurance are not significantly different in risk tolerance from farmers who eschew such opportunities. These findings stimulate questions about how farm programs and the distinct challenges of entry in the production agriculture sector shape the underlying distribution of key farmer characteristics such as risk tolerance.
    Keywords: D81 - Criteria for Decision-Making under Risk and Uncertainty, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 75
    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
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  • 76
    Publication Date: 2015-12-13
    Description: Families in low-income neighborhoods sometimes lack access to supermarkets that provide a broad range of healthy foods. We investigate whether these so called "food deserts" play a role in childhood obesity using a statewide panel data set of Arkansas elementary schoolchildren. We use fixed-effects panel data regression models to estimate the average food desert effect. We next compare children who left (entered) food deserts to children who were always (never) in food deserts and homogenize samples for those whose food desert status changed as a result of a change in residence and those whose status changed only as a consequence of the entry or exit of a supermarket. We present evidence that exposure to food deserts is associated with higher z-scores for body mass index. On average, this is in the neighborhood of 0.04 standard deviations. The strongest evidence and largest association is among urban students and especially those that transition into food deserts from non-deserts. Our food desert estimates are similar in magnitude to findings reported in earlier work on diet and lifestyle interventions targeting similarly aged schoolchildren. That said, we are unable to conclude that the estimated food desert effect is causal because many of the transitions into or out of food deserts result from a change in residence, an event that is endogenous to the child's household. However, there is evidence that food deserts are a risk indicator and that food desert areas may be obesogenic in ways that other low-income neighborhoods are not.
    Keywords: I14 - Health and Inequality, I19 - Other, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 77
    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
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    Topics: Biology
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  • 78
    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
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  • 79
    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
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  • 80
    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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  • 81
    Publication Date: 2011-11-24
    Description: This paper evaluates the farm-level supply and income effects from removing milk quotas and reducing producer prices with increasing direct compensatory payments. Using a panel of Belgian dairy farms, we first estimate a multi-output multi-input flexible cost function that generates a U-shaped marginal cost curve for each farm of the sample. We then embed each farm cost function in a profit-maximisation programming model that is built and calibrated for each farm in the sample. Accounting for farm heterogeneity, the simulations show how dairy farms without quotas may respond differently to changes in prices and structural changes that may take place within the dairy sector. A quota removal with a 20 per cent reduction in milk prices keeps aggregate milk supply and farm income at about the same level of the 2006 reference year.
    Keywords: C33 - Models with Panel Data, C63 - Computational Techniques, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, 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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  • 82
    Publication Date: 2011-11-24
    Description: This paper analyses the impact of milk quotas on the size structure of dairy herds in two major EU milk-producing member states, Germany and the Netherlands, using Markov chain models. Four mobility indicators characterising structural change are developed and calculated. Structural change in the dairy sector as measured by the mobility measures is found to be affected by the milk quota scheme. In the quota period, mobility out of dairying is lower, but the overall and upward mobility increase. This effect is stronger in the Netherlands than in West Germany.
    Keywords: D92 - Intertemporal Firm Choice and Growth, Investment, or Financing, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, 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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  • 83
    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
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    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 84
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 85
    Publication Date: 2011-11-24
    Description: In this article, we present one of the first real-world empirical applications of state-contingent production theory. Our state-contingent behavioural model allows us to analyse production under both inefficiency and uncertainty without regard to the nature of producer risk preferences. Using farm data for Finland, we estimate a flexible production model that permits substitutability between state-contingent outputs. We test empirically and reject an assumption that has been implicit in almost all efficiency studies conducted in the last three decades, namely that the production technology is output-cubical, i.e. that outputs are not substitutable between states of nature.
    Keywords: D81 - Criteria for Decision-Making under Risk and Uncertainty, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 86
    Publication Date: 2011-11-24
    Description: In this paper, a modelling approach is developed for the treatment of ‘don't know’(DK) responses, within choice experiments (CEs). A DK option is motivated by the need to allow respondents the opportunity to express uncertainty. Our model explains a DK using an entropy measure of the similarity between options given to respondents within the CE. We illustrate our model by applying it to a CE examining consumer preferences for nutrient contents in food. We find that similarity between options in a given choice set does explain the tendency for respondents to report DK.
    Keywords: C35 - Discrete Regression and Qualitative Choice Models, I18 - Government Policy ; Regulation ; Public Health, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 87
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 88
    Publication Date: 2012-03-08
    Description: Economists have long relied on utilitarian principles in carrying out cost–benefit analysis, but such utilitarianism is typically limited to the well-being of humans. Some prominent philosophers have argued such an approach is unjustifiably speciesist, but what are the consequences of including animal well-being in cost–benefit analysis? This paper considers this question in the context of human altruism towards animals in which people's concerns for the well-being of animals create an externality. After uncovering some conceptual challenges involved in carrying out cost–benefit analysis on animal welfare policies, we report the results of a novel experiment used to measure the public-good value of farm animal welfare, and show that although the average value in our sample is quite large, the result is due to the preferences of only a small subset of the subjects.
    Keywords: C91 - Laboratory, Individual Behavior, D61 - Allocative Efficiency ; Cost-Benefit Analysis, D64 - Altruism, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 89
    Publication Date: 2014-01-22
    Description: Crop insurance is similar to flood and hurricane insurance in that spatially correlated weather tends to cause violations of the independence assumption. Ideally, one would seek to pool uncorrelated risk drawn from the same distribution in crop insurance. This article proposes a testing procedure for the cross-sectional pooling of group units, and empirically analyzes whether the proposed test improves out-of-sample rating performance. We utilize a balanced panel of U.S. county-level corn yields for 510 counties, and the results of an out-of-sample crop insurance rating performance exercise provide economic significance to the proposed pooling methodology and results.
    Keywords: C12 - Hypothesis Testing, 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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  • 90
    Publication Date: 2014-01-22
    Description: Is low input use by poor, smallholder farmers caused by time-inconsistent behavior or by limited ability to buy inputs? Are input subsidies the best solution to stimulate input demand or are there smarter solutions? These issues are investigated by combining survey data, stated preference questions, and randomized experiments in Malawi. The demand for fertilizer at harvest time and at planting time, farm gate shadow prices for fertilizer, and the gap between the willingness-to-accept (WTA) and willingness-to-pay (WTP) prices for a standard input package were investigated. Significant effects of timing and of cash constraints were found, suggesting the possibility that smarter designs exist, such as distribution of smaller packages from harvest time to planting time.
    Keywords: Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 91
    Publication Date: 2014-01-23
    Description: This paper studies the effect of political regime transitions on public policy using a new data set on global agricultural and food policies over a 50-year period (including data from 74 developing and developed countries over the 1955–2005 period). We find evidence that democratization leads to a reduction of agricultural taxation, an increase in agricultural subsidization, or both. The empirical findings are consistent with the predictions of the median voter model because political transitions occurred primarily in countries with a majority of farmers. The results are robust to different specifications, estimation approaches, and variable definitions.
    Keywords: D72 - Models of Political Processes: Rent-Seeking, Elections, Legislatures, and Voting Behavior, F13 - Trade Policy ; International Trade Organizations, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, P16 - Political Economy, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0258-6770
    Electronic ISSN: 1564-698X
    Topics: Economics
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  • 92
    Publication Date: 2014-01-23
    Description: In times of highly volatile commodity markets, governments often try to protect their populations from rapidly rising food prices, which can be particularly harmful for the poor. A potential solution for food-deficit countries is to hold strategic reserves that can be called on when international prices spike. But how large should strategic stockpiles be, and what rules should govern their release? In this paper, we develop a dynamic competitive storage model for wheat in the Middle East and North Africa region, where imported wheat is the most significant component of the average diet. We analyze a strategy that sets aside wheat stockpiles, which can be used to keep domestic prices below a targeted price. Our analysis shows that if the target price is set high and reserves are adequate, the strategy can be effective and robust. Contrary to most interventions, strategic storage policies are counter-cyclical, and when the importing region is sufficiently large, a regional policy can smooth global prices. Simulations indicate that this is the case for the Middle East and North Africa region. Nevertheless, the policy is more costly than a procyclical policy similar to food stamps that uses targeted transfers to directly offset high prices with a subsidy.
    Keywords: F10 - General, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0258-6770
    Electronic ISSN: 1564-698X
    Topics: Economics
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  • 93
    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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  • 94
    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
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  • 95
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 96
    Publication Date: 2014-03-21
    Description: Simulated prices from a stochastic storage model are used to examine the price impacts of speculation by rational investors who diversify their financial portfolios by holding agricultural commodity futures. The main result is that rather than destabilizing commodity prices, as is commonly believed, portfolio speculation actually reduces price volatility. Portfolio speculation can potentially destabilize a commodity's price because the additional demand for long futures by speculators is expected to drive up the cash price during both periods of low net demand, when the cash price is below average, and periods of high net demand, when the cash price is above average. Our theoretical analysis demonstrates that the higher level of inventory that is associated with portfolio speculation results in a larger release of stocks during periods of high net demand. The price simulations reveal that this stock adjustment effect is strong since overall price volatility is smaller rather than larger with portfolio speculation.
    Keywords: Q11 - Aggregate Supply and Demand Analysis ; Prices, Q14 - Agricultural Finance, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 97
    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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  • 98
    Publication Date: 2014-04-05
    Description: This paper uses framed choice experiments to examine the preferences of smallholder farmers in Malawi regarding alternative policy-based incentives to adopt conservation practices that reduce soil erosion and increase yields. The policy incentives offered in the choice experiments included an ideal index-based crop insurance contract, an index insurance contract with basis risk, cash payments, and fertilizer subsidies. Prior to implementing the choice experiments, the farmers participated in a workshop utilizing small group-based dynamic learning games that demonstrated how index-based crop insurance contracts function. The choice experiment results indicate that most farmers preferred cash payments to index insurance contracts, even when the insurance contracts offered substantially higher expected returns. Further, more risk averse farmers were more likely to prefer cash payments than less risk averse and risk loving farmers.
    Keywords: C93 - Field Experiments, O12 - Microeconomic Analyses of Economic Development, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 99
    Publication Date: 2014-04-05
    Description: We develop a dynamic model to assess the effects of policy expectations on crop supply and illustrate the approach with estimates of the effects of base updating in U.S. crop programs. For corn and soybeans in the Corn Belt, the effect of base updating is relatively small because relevant crop alternatives are subject to similar policies and the alternatives are substitutes in production. Increasing acreage of one program crop to capture future payments from base updating reduces future payments from the alternative crop. We also use our model to assess the effect of base updating on acreage response to prices.
    Keywords: Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 100
    Publication Date: 2014-04-05
    Description: A substantial share of U.S. hog producers incorporate antimicrobial drugs into their livestock's feed or water at sub-therapeutic levels to promote feed efficiency and weight gain. Recently, in response to concerns that the overuse of antibiotics in livestock could promote the development of antimicrobial drug-resistant bacteria, the U.S. Food and Drug Administration adopted a strategy to phase out the use of antibiotics for production purposes. This study uses a stochastic frontier model and data from the 2009 USDA Agricultural Resource Management Survey of feeder-to-finish hog producers to estimate the potential effects on hog output and output variability resulting from a ban on antibiotics used for growth promotion. We use propensity score nearest neighbor matching to create a balanced sample of sub-therapeutic antibiotic (STA) users and nonusers. We estimate the frontier model for the pooled sample and separately for users and non-users—which allows for a flexible interaction between STA use and the production technology. Point estimates for the matched sample indicate that STA use has a small positive effect on productivity and production risk, increasing output by 1.0–1.3% and reducing the standard deviation of unexplained output by 1.4%. The results indicate that improvements in productivity resulted exclusively from technological improvement rather than from an increase in technical efficiency.
    Keywords: D24 - Production ; Cost ; Capital and Total Factor Productivity ; Capacity, I18 - Government Policy ; Regulation ; Public Health, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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