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  • Computational Methods, Genomics  (67)
  • Food Policy  (65)
  • Oxford University Press  (132)
  • International Union of Crystallography (IUCr)
  • 2010-2014  (132)
  • 1
    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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  • 2
    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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  • 3
    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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  • 4
    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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  • 5
    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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  • 6
    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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  • 7
    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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  • 8
    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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  • 9
    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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  • 10
    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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  • 11
    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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  • 12
    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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  • 13
    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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  • 14
    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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  • 15
    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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  • 16
    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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  • 17
    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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  • 18
    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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  • 19
    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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  • 20
    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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  • 21
    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
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  • 22
    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
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  • 23
    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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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 24
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 25
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 26
    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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  • 27
    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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  • 28
    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
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 29
    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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  • 30
    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
    Print ISSN: 0002-9092
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 31
    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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  • 32
    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
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    Electronic ISSN: 1564-698X
    Topics: Economics
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  • 33
    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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  • 34
    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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  • 35
    Publication Date: 2014-03-21
    Description: The Minnesota Food Network is a limited liability company comprised of 52 farmers producing a variety of high-quality, sustainably produced agricultural products in southern Minnesota. The network's goal is to develop a regional food system to provide locally grown food at a price that "is fair" to both consumers and producers. This case outlines the challenges that the network faces in their efforts to expand to take advantage of a market opportunity. One of their biggest challenges is that they face high operating costs because of their disaggregated distribution system and need to purchase a distribution and storage facility and two vehicles. They will fund the purchase of a building through an angel investor. An angel investor is necessary because the network cannot sustain traditional loan payments in its current form. Students are asked to consider a number of questions pertaining to the decisions in this case outlined in the final section of the case study.
    Keywords: A22 - Undergraduate, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 36
    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
    Print ISSN: 0002-9092
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 37
    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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  • 38
    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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  • 39
    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
    Print ISSN: 0002-9092
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 40
    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
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 41
    Publication Date: 2012-03-29
    Description: Broadly, computational approaches for ortholog assignment is a three steps process: (i) identify all putative homologs between the genomes, (ii) identify gene anchors and (iii) link anchors to identify best gene matches given their order and context. In this article, we engineer two methods to improve two important aspects of this pipeline [specifically steps (ii) and (iii)]. First, computing sequence similarity data [step (i)] is a computationally intensive task for large sequence sets, creating a bottleneck in the ortholog assignment pipeline. We have designed a fast and highly scalable sort-join method (afree) based on k -mer counts to rapidly compare all pairs of sequences in a large protein sequence set to identify putative homologs. Second, availability of complex genomes containing large gene families with prevalence of complex evolutionary events, such as duplications, has made the task of assigning orthologs and co-orthologs difficult. Here, we have developed an iterative graph matching strategy where at each iteration the best gene assignments are identified resulting in a set of orthologs and co-orthologs. We find that the afree algorithm is faster than existing methods and maintains high accuracy in identifying similar genes. The iterative graph matching strategy also showed high accuracy in identifying complex gene relationships. Standalone afree available from http://vbc.med.monash.edu.au/~kmahmood/afree . EGM2, complete ortholog assignment pipeline (including afree and the iterative graph matching method) available from http://vbc.med.monash.edu.au/~kmahmood/EGM2 .
    Keywords: Computational Methods, Genomics
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  • 42
    Publication Date: 2012-03-29
    Description: With the availability of next-generation sequencing (NGS) technology, it is expected that sequence variants may be called on a genomic scale. Here, we demonstrate that a deeper understanding of the distribution of the variant call frequencies at heterozygous loci in NGS data sets is a prerequisite for sensitive variant detection. We model the crucial steps in an NGS protocol as a stochastic branching process and derive a mathematical framework for the expected distribution of alleles at heterozygous loci before measurement that is sequencing. We confirm our theoretical results by analyzing technical replicates of human exome data and demonstrate that the variance of allele frequencies at heterozygous loci is higher than expected by a simple binomial distribution. Due to this high variance, mutation callers relying on binomial distributed priors are less sensitive for heterozygous variants that deviate strongly from the expected mean frequency. Our results also indicate that error rates can be reduced to a greater degree by technical replicates than by increasing sequencing depth.
    Keywords: Computational Methods, Genomics
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  • 43
    Publication Date: 2012-03-14
    Description: An approach to infer the unknown microbial population structure within a metagenome is to cluster nucleotide sequences based on common patterns in base composition, otherwise referred to as binning. When functional roles are assigned to the identified populations, a deeper understanding of microbial communities can be attained, more so than gene-centric approaches that explore overall functionality. In this study, we propose an unsupervised, model-based binning method with two clustering tiers, which uses a novel transformation of the oligonucleotide frequency-derived error gradient and GC content to generate coarse groups at the first tier of clustering; and tetranucleotide frequency to refine these groups at the secondary clustering tier. The proposed method has a demonstrated improvement over PhyloPythia, S-GSOM, TACOA and TaxSOM on all three benchmarks that were used for evaluation in this study. The proposed method is then applied to a pyrosequenced metagenomic library of mud volcano sediment sampled in southwestern Taiwan, with the inferred population structure validated against complementary sequencing of 16S ribosomal RNA marker genes. Finally, the proposed method was further validated against four publicly available metagenomes, including a highly complex Antarctic whale-fall bone sample, which was previously assumed to be too complex for binning prior to functional analysis.
    Keywords: Computational Methods, Genomics
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  • 44
    Publication Date: 2011-12-27
    Description: We investigate farm size inequality in France using agricultural censuses and farm structure surveys at the NUTS3 level (‘départements’) during the period 1970–2007. Using calculated Gini coefficients, we show that farm size inequality has not systematically increased in France. An econometric analysis of the determinants of farm size inequality reveals that policy measures significantly affected farm size inequality, with most of the measures considered decreasing it. Empirical results suggest that the main contributor was the activity of the SAFER (Société d'Aménagement Foncier et d'Etablissement Rural), a specific feature of the French farm structural policy aimed at regulating rural land management. Besides, this research highlights the great complexity of the dynamics underlying the evolution of farm size distribution.
    Keywords: D30 - General, Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation, 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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  • 45
    Publication Date: 2011-12-27
    Description: This paper analyses implementation policies of environmental quota trade, with the Flemish nutrient production rights as an example. Implementation policies concern the transaction quantity, quota reduction and prevention of speculation. They are analysed with a static and a dynamic multi-agent quota trade model. The static model with discrete non-auctioned quota trade shows that the obligation for quota sellers to entirely stop their production stimulates structural change. The dynamic model version indicates that a flat rate reduction on traded quota and measures taken to prevent speculation combined with too low penalties for overuse stimulate the total production.
    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
    Print ISSN: 0165-1587
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 46
    Publication Date: 2011-12-27
    Description: European cattle markets have recently undergone significant change. We explore the simultaneous impacts of agricultural policy reform and the occurrence of an animal health crisis on spatial interdependencies of calf prices of four major European Union markets. The markets are found to be integrated. Price shocks are rapidly absorbed. We find that the member state specific implementations of the 2003 Common Agricultural Policy reforms significantly affected prices of both the national market and of other member states. The blue tongue disease further induced structural change. Using counterfactual scenarios, we show that the decoupling of payments from production led to reduced calf prices.
    Keywords: C32 - Time-Series Models, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 47
    Publication Date: 2011-12-27
    Description: We apply a spatial price equilibrium model of the world sugar market to simulate an abolition of the European Union (EU) quota system in 2015/16. To overcome the normative nature of the approach, we calibrate the model by attaching a non-linear cost term to each trade flow. This is in some regards similar to positive mathematical programming. We suggest an economic interpretation and an econometric specification of the cost term. EU sugar production is simulated to increase from 13.3 to 15.5 million tons in case of quota abolition by 2019/20. Ten member states increase production, nine reduce it. Preferential imports are significantly reduced. Simulated effects are found to be more pronounced the higher the world market price.
    Keywords: F11 - Neoclassical Models of Trade, F17 - Trade Forecasting and Simulation, 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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  • 48
    Publication Date: 2012-02-17
    Description: We introduce the software tool NTRFinder to search for a complex repetitive structure in DNA we call a nested tandem repeat (NTR). An NTR is a recurrence of two or more distinct tandem motifs interspersed with each other. We propose that NTRs can be used as phylogenetic and population markers. We have tested our algorithm on both real and simulated data, and present some real NTRs of interest. NTRFinder can be downloaded from http://www.maths.otago.ac.nz/~aamatroud/ .
    Keywords: Computational Methods, Genomics
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  • 49
    Publication Date: 2014-10-10
    Description: Parallel analysis of RNA ends (PARE) is a technique utilizing high-throughput sequencing to profile uncapped, mRNA cleavage or decay products on a genome-wide basis. Tools currently available to validate miRNA targets using PARE data employ only annotated genes, whereas important targets may be found in unannotated genomic regions. To handle such cases and to scale to the growing availability of PARE data and genomes, we developed a new tool, ‘ sPARTA ’ (small RNA-PARE target analyzer) that utilizes a built-in, plant-focused target prediction module (aka ‘ miRferno ’). sPARTA not only exhibits an unprecedented gain in speed but also it shows greater predictive power by validating more targets, compared to a popular alternative. In addition, the novel ‘seed-free’ mode, optimized to find targets irrespective of complementarity in the seed-region, identifies novel intergenic targets. To fully capitalize on the novelty and strengths of sPARTA , we developed a web resource, ‘ comPARE ’, for plant miRNA target analysis; this facilitates the systematic identification and analysis of miRNA-target interactions across multiple species, integrated with visualization tools. This collation of high-throughput small RNA and PARE datasets from different genomes further facilitates re-evaluation of existing miRNA annotations, resulting in a ‘cleaner’ set of microRNAs.
    Keywords: Computational Methods, Genomics
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  • 50
    Publication Date: 2014-10-10
    Description: Identification of three-dimensional (3D) interactions between regulatory elements across the genome is crucial to unravel the complex regulatory machinery that orchestrates proliferation and differentiation of cells. ChIA-PET is a novel method to identify such interactions, where physical contacts between regions bound by a specific protein are quantified using next-generation sequencing. However, determining the significance of the observed interaction frequencies in such datasets is challenging, and few methods have been proposed. Despite the fact that regions that are close in linear genomic distance have a much higher tendency to interact by chance, no methods to date are capable of taking such dependency into account. Here, we propose a statistical model taking into account the genomic distance relationship, as well as the general propensity of anchors to be involved in contacts overall. Using both real and simulated data, we show that the previously proposed statistical test, based on Fisher's exact test, leads to invalid results when data are dependent on genomic distance. We also evaluate our method on previously validated cell-line specific and constitutive 3D interactions, and show that relevant interactions are significant, while avoiding over-estimating the significance of short nearby interactions.
    Keywords: Computational Methods, Genomics
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  • 51
    Publication Date: 2014-10-10
    Description: Viral sequence classification has wide applications in clinical, epidemiological, structural and functional categorization studies. Most existing approaches rely on an initial alignment step followed by classification based on phylogenetic or statistical algorithms. Here we present an ultrafast alignment-free subtyping tool for human immunodeficiency virus type one (HIV-1) adapted from Prediction by Partial Matching compression. This tool, named COMET, was compared to the widely used phylogeny-based REGA and SCUEAL tools using synthetic and clinical HIV data sets (1 090 698 and 10 625 sequences, respectively). COMET's sensitivity and specificity were comparable to or higher than the two other subtyping tools on both data sets for known subtypes. COMET also excelled in detecting and identifying new recombinant forms, a frequent feature of the HIV epidemic. Runtime comparisons showed that COMET was almost as fast as USEARCH. This study demonstrates the advantages of alignment-free classification of viral sequences, which feature high rates of variation, recombination and insertions/deletions. COMET is free to use via an online interface.
    Keywords: Computational Methods, Genomics
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  • 52
    Publication Date: 2014-11-11
    Description: This paper deals with the determinants of out-farm migration across the European Union (EU) regions focusing on the role played by CAP payments. We add to the existing literature in three main directions. First, our analysis has broad coverage (150 EU regions over the 1990–2009 period); second, we work on the entire portfolio of CAP instruments; third, we rely on modern panel data methods. Results show that standard drivers, such as the relative income and the relative labour share, are important determinants of out-farm migration. Overall, CAP payments significantly contributed to maintain job in agriculture, though the magnitude of the economic effect has been quite moderate and heterogeneous across policy instruments. Pillar I subsidies exerted an effect more than two times greater than that of Pillar II payments.
    Keywords: J21 - Labor Force and Employment, Size, and Structure, J43 - Agricultural Labor Markets, J60 - General, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, 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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  • 53
    Publication Date: 2014-11-28
    Description: Understanding how regulatory networks globally coordinate the response of a cell to changing conditions, such as perturbations by shifting environments, is an elementary challenge in systems biology which has yet to be met. Genome-wide gene expression measurements are high dimensional as these are reflecting the condition-specific interplay of thousands of cellular components. The integration of prior biological knowledge into the modeling process of systems-wide gene regulation enables the large-scale interpretation of gene expression signals in the context of known regulatory relations. We developed COGERE ( http://mips.helmholtz-muenchen.de/cogere ), a method for the inference of condition-specific gene regulatory networks in human and mouse. We integrated existing knowledge of regulatory interactions from multiple sources to a comprehensive model of prior information. COGERE infers condition-specific regulation by evaluating the mutual dependency between regulator (transcription factor or miRNA) and target gene expression using prior information. This dependency is scored by the non-parametric, nonlinear correlation coefficient 2 (eta squared) that is derived by a two-way analysis of variance. We show that COGERE significantly outperforms alternative methods in predicting condition-specific gene regulatory networks on simulated data sets. Furthermore, by inferring the cancer-specific gene regulatory network from the NCI-60 expression study, we demonstrate the utility of COGERE to promote hypothesis-driven clinical research.
    Keywords: Computational Methods, Genomics
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  • 54
    Publication Date: 2014-12-03
    Description: Decoupled direct payments to farmers were introduced in the European Union (EU) in the form of the Single Payment Scheme (SPS) in 2005. The 2013 Common Agriculture Policy (CAP) reform changed both the implementation of the SPS and its budget. We assess the possible effects of the 2013 CAP reform on EU land markets, particularly the capitalization of the SPS in land rental values. Our analyses suggest that the implementation details of the 2013 CAP reform will largely determine the impact of the SPS on land markets. The key considerations are the reference period for entitlement allocation, regionalization, payment differentiation, and budgetary changes. Our analysis also implies that a number of relatively minor policy changes could have substantial impacts on land markets.
    Keywords: H22 - Incidence, Q11 - Aggregate Supply and Demand Analysis ; Prices, 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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  • 55
    Publication Date: 2014-09-06
    Description: We examine the effect that investments in education have on household expenditure on fruits and vegetables using a two-stage model that accounts for differences in ability and heterogeneous returns to education. For this, we use the 2008 Consumer Expenditure Survey for the United States. We find that higher levels of education contribute to greater household expenditures on both fresh and processed fruits and vegetables. We find a nonlinear effect on fresh fruits and vegetables, indicating that education impacts the quality of purchases as well. Although nutritional education is often touted as important for a healthful diet, these results highlight how investments in human capital via formal education can potentially improve dietary quality as well.
    Keywords: I12 - Health Production, I20 - General, 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: 2014-09-06
    Description: In this article, we explore how using imputed income data in the Survey of Income and Program Participation affects the observed relationship between household income volatility and food insufficiency. We find that measuring income volatility using imputed income data substantially understates the association between large drops in household income and food insufficiency. After excluding observations with imputed income, large drops in income are associated with a 2.1–percentage point increased probability of food insufficiency, or a 31% higher likelihood of food insufficiency.
    Keywords: C18 - Methodological Issues: General, C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Q18 - Agricultural Policy ; Food Policy
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    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 57
    Publication Date: 2014-09-06
    Description: This research explores the viability of an alternative design for crop insurance based upon farmer-owned savings accounts that are regulated, monitored, and marginally assisted by the government. Such accounts could be an effective risk management tool for many farmers and could operate without major government subsidization. Relative to the current program, the proposed design should exhibit minimal moral hazard and adverse selection problems, and since farm-level risk does not have to be priced, the proposed design eliminates the premium rating difficulties that weaken actuarial soundness and trigger the need for substantial external subsidies. In addition, administrative costs should be considerably lower.
    Keywords: 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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  • 58
    Publication Date: 2014-09-06
    Description: The recent spikes of global food prices induced a rapid increase in mass media coverage, public policy attention, and donor funding for food security and for agriculture and rural poverty. This has occurred while the shift from low to high food prices has induced a shift in (demographic or social) location of the hunger and poverty effects, but the total number of undernourished and poor people has declined over the same period. We suggest that the observed pattern can be explained by the presence of a global urban bias on agriculture and food policy in developing countries, and we discuss whether this global urban bias may actually benefit poor farmers. We argue that the food price spikes have succeeded where others have failed in the past: to move the problems of poor and hungry farmers to the top of the policy agenda and to induce development and donor strategies to help them.
    Keywords: F35 - Foreign Aid, Q11 - Aggregate Supply and Demand Analysis ; Prices, 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: 2014-12-17
    Description: Non-coding RNAs (ncRNAs) are known to play important functional roles in the cell. However, their identification and recognition in genomic sequences remains challenging. In silico methods, such as classification tools, offer a fast and reliable way for such screening and multiple classifiers have already been developed to predict well-defined subfamilies of RNA. So far, however, out of all the ncRNAs, only tRNA, miRNA and snoRNA can be predicted with a satisfying sensitivity and specificity. We here present ptRNApred , a tool to detect and classify subclasses of non-coding RNA that are involved in the regulation of post-transcriptional modifications or DNA replication, which we here call post-transcriptional RNA (ptRNA). It (i) detects RNA sequences coding for post-transcriptional RNA from the genomic sequence with an overall sensitivity of 91% and a specificity of 94% and (ii) predicts ptRNA-subclasses that exist in eukaryotes: snRNA, snoRNA, RNase P, RNase MRP, Y RNA or telomerase RNA. AVAILABILITY: The ptRNApred software is open for public use on http://www.ptrnapred.org/ .
    Keywords: Computational Methods, Genomics
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  • 60
    Publication Date: 2014-12-17
    Description: Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, annotate and prioritize expressed SNVs (eSNVs) from non-directional paired-end RNA-Seq data. We have developed the eSNV-Detect, a novel computational system, which utilizes data from multiple aligners to call, even at low read depths, and rank variants from RNA-Seq. Multi-platform comparisons with the eSNV-Detect variant candidates were performed. The method was first applied to RNA-Seq from a lymphoblastoid cell-line, achieving 99.7% precision and 91.0% sensitivity in the expressed SNPs for the matching HumanOmni2.5 BeadChip data. Comparison of RNA-Seq eSNV candidates from 25 ER+ breast tumors from The Cancer Genome Atlas (TCGA) project with whole exome coding data showed 90.6–96.8% precision and 91.6–95.7% sensitivity. Contrasting single-cell mRNA-Seq variants with matching traditional multicellular RNA-Seq data for the MD-MB231 breast cancer cell-line delineated variant heterogeneity among the single-cells. Further, Sanger sequencing validation was performed for an ER+ breast tumor with paired normal adjacent tissue validating 29 out of 31 candidate eSNVs. The source code and user manuals of the eSNV-Detect pipeline for Sun Grid Engine and virtual machine are available at http://bioinformaticstools.mayo.edu/research/esnv-detect/ .
    Keywords: Computational Methods, Genomics
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  • 61
    Publication Date: 2014-12-13
    Description: Are labels good or bad for consumers and firms? The answer may seem straightforward since labels improve information, yet economic theory reveals situations where their introduction reduces the welfare of at least some market participants. This essay reviews the theoretical literature on labels in order to identify and explain the main reasons that may cause labeling to produce undesirable side-effects. In contrast to earlier reviews that either concentrate on narrow topics or treat the subject in a more or less informal way, we bring together the main results from all the relevant topics by presenting and discussing the assumptions and model-building techniques that underpin them. The advantage of this approach is that it identifies the origin of the differences between results, thus allowing the synthesis of results that sometimes appear even to be contradictory. We focus on "quality labels" and examine the impact of labeling on market structure, the side-effects of costly certification, issues related to the label's trustworthiness, the rationale for mandatory vs. voluntary labeling, the level at which the label's standard is set according to the agency that selects it, the political economy of labels, that is, pro- or anti-label lobbying, lobbying to affect the label's standard, and lobbying in favor or against the label's mandatory imposition. These topics cover a wide range of applications, including Genetically Modified Organism (GMOs), organic produce, geographic indicators, controlled origin, eco-labels, etc. We conclude by identifying topics that require further research.
    Keywords: L15 - Information and Product Quality ; Standardization and Compatibility, L50 - General, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 62
    Publication Date: 2014-12-13
    Description: Can food prices cause social unrest? Throughout history, riots have frequently broken out, ostensibly as a consequence of high food prices. Using monthly data at the international level, this article studies the impact of food prices – food price levels as well as food price volatility – on social unrest. Because food prices and social unrest are jointly determined, data on natural disasters are used to identify the causal relationship flowing from food price levels to social unrest. Results indicate that for the period 1990–2011, food price increases have led to increases in social unrest, whereas food price volatility has not been associated with increases in social unrest. These results are robust to alternative definitions of social unrest, to using real or nominal prices, to using commodity-specific price indices instead of aggregated price indices, to alternative definitions of the instrumental variable, to alternative definitions of volatility, and to controlling for non-food-related social unrest.
    Keywords: D74 - Conflict ; Conflict Resolution ; Alliances, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 63
    Publication Date: 2014-07-03
    Description: Up to now, most nutritional policies have been set up to inform consumers about the health benefits induced by more balanced diets. Reviews of the impacts of these policies show that the effects are often modest. This has led governments to implement, in more recent times, policies focused on the market environment, especially on the characteristics of the food supply. The goal of this paper is to review theoretical and empirical studies focusing on changes in the food supply induced by alternative policies, and to attempt to draw from them policy guidelines and conjectures to test in future research.
    Keywords: I38 - Government Policy ; Provision and Effects of Welfare Programs, L66 - Food ; Beverages ; Cosmetics ; Tobacco ; Wine and Spirits, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 64
    Publication Date: 2014-07-03
    Description: With the rise of behavioural economics has come the belief that decision-making biases justify paternalistic policies. Such views challenge the notion of consumer sovereignty and the validity of traditional approaches of economic welfare analysis. While behavioural economics might improve the effectiveness of policies that are already justified on some other market-failure grounds, this article argues that the existence of cognitive failures, alone, do not justify government regulation. If one abandons the idea that consumers know what is in their best interest, judging the merits of policies becomes arbitrary and reflects only what a paternalist wants for others. The typical behavioural economic experiment occurs with college students devoid of real-world context. The biases found in such setting may not extrapolate well to conditions where people have more experience and knowledge, and where they can learn from past mistakes. Even when behavioural biases persist in the ‘real world’, consumers face incentives to engage in activities that protect them from the adverse consequences of the biases, and public policies that shield people from such consequences reduce incentives to self-regulate. The article concludes with some ideas for future research and a discussion of the merits of freedom of choice.
    Keywords: D03 - Behavioral Economics ; Underlying Principles, 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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  • 65
    Publication Date: 2014-04-15
    Description: Heterogeneity in genetic networks across different signaling molecular contexts can suggest molecular regulatory mechanisms. Here we describe a comparative chi-square analysis (CP 2 ) method, considerably more flexible and effective than other alternatives, to screen large gene expression data sets for conserved and differential interactions. CP 2 decomposes interactions across conditions to assess homogeneity and heterogeneity. Theoretically, we prove an asymptotic chi-square null distribution for the interaction heterogeneity statistic. Empirically, on synthetic yeast cell cycle data, CP 2 achieved much higher statistical power in detecting differential networks than alternative approaches. We applied CP 2 to Drosophila melanogaster wing gene expression arrays collected under normal conditions, and conditions with overexpressed E2F and Cabut, two transcription factor complexes that promote ectopic cell cycling. The resulting differential networks suggest a mechanism by which E2F and Cabut regulate distinct gene interactions, while still sharing a small core network. Thus, CP 2 is sensitive in detecting network rewiring, useful in comparing related biological systems.
    Keywords: Computational Methods, Genomics
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  • 66
    Publication Date: 2013-07-31
    Description: In consequence of strong changes in general economic conditions, adjustments in the agricultural sector can be expected. To date, however, there are only few policy impact analyses on agricultural investments in a dynamic-stochastic context. The objective of this paper is to develop a real options market model which allows the impact assessment of different political schemes. The model combines genetic algorithms and stochastic simulation. Simulations of the model show that investment subsidies and production ceilings are preferable to price floors because the welfare is less reduced for a given stimulation of the willingness to invest.
    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
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 67
    Publication Date: 2013-07-31
    Description: The aim of this paper is to study farmers' participation in rural development policy (RDP) measures. We investigate to what extent regional RDP priorities are driven by regional characteristics and moreover, whether regional-level policy priorities help to explain farmers' participation in RDP measures. We estimate a multilevel binary choice model that includes both farm-level and regional-level explanatory variables. We conclude that regional governments select RDP priorities based on the specific features of their region. Regional policy priorities play an important role in explaining farmers' participation in agri-environmental schemes but not in measures aimed at improving farmer competitiveness.
    Keywords: 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: 2013-07-31
    Description: The distinction between single farm payments (SFP) and counter-cyclical payments (CCPs) is mainly based on theory. Due to a lack of empirical comparative studies between these payments, it is difficult to confirm the claim that CCPs are more distorting. This paper provides a comparative analysis of these payments and quantifies the impact of such payments in the presence of debt constraints. The main findings are that CCPs are more distorting than SFP. However, the magnitude of the impact estimates is not as large as suggested by the different treatment received by both support programmes in the WTO negotiations.
    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: 2013-09-06
    Description: Protein-binding microarray (PBM) is a high-throughout platform that can measure the DNA-binding preference of a protein in a comprehensive and unbiased manner. A typical PBM experiment can measure binding signal intensities of a protein to all the possible DNA k-mers (k = 8 ~10); such comprehensive binding affinity data usually need to be reduced and represented as motif models before they can be further analyzed and applied. Since proteins can often bind to DNA in multiple modes, one of the major challenges is to decompose the comprehensive affinity data into multimodal motif representations. Here, we describe a new algorithm that uses Hidden Markov Models (HMMs) and can derive precise and multimodal motifs using belief propagations. We describe an HMM-based approach using belief propagations (kmerHMM), which accepts and preprocesses PBM probe raw data into median-binding intensities of individual k-mers. The k-mers are ranked and aligned for training an HMM as the underlying motif representation. Multiple motifs are then extracted from the HMM using belief propagations. Comparisons of kmerHMM with other leading methods on several data sets demonstrated its effectiveness and uniqueness. Especially, it achieved the best performance on more than half of the data sets. In addition, the multiple binding modes derived by kmerHMM are biologically meaningful and will be useful in interpreting other genome-wide data such as those generated from ChIP-seq. The executables and source codes are available at the authors’ websites: e.g. http://www.cs.toronto.edu/~wkc/kmerHMM .
    Keywords: Computational Methods, Genomics
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  • 70
    Publication Date: 2014-04-15
    Description: Sequence similarity search is a fundamental way of analyzing nucleotide sequences. Despite decades of research, this is not a solved problem because there exist many similarities that are not found by current methods. Search methods are typically based on a seed-and-extend approach, which has many variants (e.g. spaced seeds, transition seeds), and it remains unclear how to optimize this approach. This study designs and tests seeding methods for inter-mammal and inter-insect genome comparison. By considering substitution patterns of real genomes, we design sets of multiple complementary transition seeds, which have better performance (sensitivity per run time) than previous seeding strategies. Often the best seed patterns have more transition positions than those used previously. We also point out that recent computer memory sizes (e.g. 60 GB) make it feasible to use multiple (e.g. eight) seeds for whole mammal genomes. Interestingly, the most sensitive settings achieve diminishing returns for human–dog and melanogaster–pseudoobscura comparisons, but not for human–mouse, which suggests that we still miss many human–mouse alignments. Our optimized heuristics find ~20 000 new human–mouse alignments that are missing from the standard UCSC alignments. We tabulate seed patterns and parameters that work well so they can be used in future research.
    Keywords: Computational Methods, Genomics
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  • 71
    Publication Date: 2014-04-15
    Description: Identifying differential features between conditions is a popular approach to understanding molecular features and their mechanisms underlying a biological process of particular interest. Although many tests for identifying differential expression of gene or gene sets have been proposed, there was limited success in developing methods for differential interactions of genes between conditions because of its computational complexity. We present a method for Evaluation of Dependency DifferentialitY (EDDY), which is a statistical test for differential dependencies of a set of genes between two conditions. Unlike previous methods focused on differential expression of individual genes or correlation changes of individual gene–gene interactions, EDDY compares two conditions by evaluating the probability distributions of dependency networks from genes. The method has been evaluated and compared with other methods through simulation studies, and application to glioblastoma multiforme data resulted in informative cancer and glioblastoma multiforme subtype-related findings. The comparison with Gene Set Enrichment Analysis, a differential expression-based method, revealed that EDDY identifies the gene sets that are complementary to those identified by Gene Set Enrichment Analysis. EDDY also showed much lower false positives than Gene Set Co-expression Analysis, a method based on correlation changes of individual gene–gene interactions, thus providing more informative results. The Java implementation of the algorithm is freely available to noncommercial users. Download from: http://biocomputing.tgen.org/software/EDDY .
    Keywords: Computational Methods, Genomics
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  • 72
    Publication Date: 2014-09-02
    Description: We examine enrollment in the U.S. Medicaid and Supplemental Nutrition Assistance Programs (SNAP) and find that while SNAP-eligible adults in poor physical health and with multiple chronic conditions are more likely to jointly enroll in SNAP and Medicaid, they are less likely to enroll in SNAP alone. We also find that the conditional probability of SNAP enrollment given Medicaid participation is higher for individuals with multiple chronic conditions. As a result, the expansion of Medicaid and state policies that promote enrollment coordination between SNAP and Medicaid are expected to increase the number of individuals in SNAP with chronic medical conditions.
    Keywords: I10 - General, I38 - Government Policy ; Provision and Effects of Welfare Programs, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 73
    Publication Date: 2014-09-02
    Description: At odds with a vast body of economic evidence reporting exceptionally high rates of return to investments in agricultural research and development (R&D), growth in public R&D spending for food and agriculture has slowed in numerous, especially rich, countries worldwide. The observed R&D spending behavior is consistent with a determination that the reported rates of return are perceived as implausible by policy makers. We examine this notion by scrutinizing 2,242 investment evaluations reported in 372 separate studies from 1958 to 2011. We find that the internal rate of return (IRR) is the predominant summary measure of investment performance used in the literature despite methodological criticisms dating back more than a half century. The reported IRRs imply rates of return that are implausibly high. We investigate the reasons for these implausibly high estimates by analytically comparing the IRR to the modified internal rate of return (MIRR). The MIRR addresses several methodological concerns with using the IRR, has the intuitive interpretation as the annual compounding interest rate paid by an investment, and is directly related to the benefit–cost ratio. To obtain more credible rate of return estimates, we then develop a novel method for recalibrating previously reported IRR estimates using the MIRR when there is limited information on an investment's stream of benefits and costs. Our recalibrated estimates of the rate of return are more modest (median of 9.8% versus 39% per year); however, they are still substantial enough to question the current scaling back of public agricultural R&D spending in many countries.
    Keywords: O22 - Project Analysis, Q16 - R&D ; Agricultural Technology ; Agricultural Extension Services, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 74
    Publication Date: 2014-09-02
    Description: Inundation of evolutionary markers expedited in Human Genome Project and 1000 Genome Consortium has necessitated pruning of redundant and dependent variables. Various computational tools based on machine-learning and data-mining methods like feature selection/extraction have been proposed to escape the curse of dimensionality in large datasets. Incidentally, evolutionary studies, primarily based on sequentially evolved variations have remained un-facilitated by such advances till date. Here, we present a novel approach of recursive feature selection for hierarchical clustering of Y-chromosomal SNPs/haplogroups to select a minimal set of independent markers, sufficient to infer population structure as precisely as deduced by a larger number of evolutionary markers. To validate the applicability of our approach, we optimally designed MALDI-TOF mass spectrometry-based multiplex to accommodate independent Y-chromosomal markers in a single multiplex and genotyped two geographically distinct Indian populations. An analysis of 105 world-wide populations reflected that 15 independent variations/markers were optimal in defining population structure parameters, such as F ST , molecular variance and correlation-based relationship. A subsequent addition of randomly selected markers had a negligible effect (close to zero, i.e. 1 x 10 –3 ) on these parameters. The study proves efficient in tracing complex population structures and deriving relationships among world-wide populations in a cost-effective and expedient manner.
    Keywords: Computational Methods, Genomics
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  • 75
    Publication Date: 2014-09-17
    Description: Developing a quantitative view of how biological pathways are regulated in response to environmental factors is central for understanding of disease phenotypes. We present a computational framework, named Multivariate Inference of Pathway Activity (MIPA), which quantifies degree of activity induced in a biological pathway by computing five distinct measures from transcriptomic profiles of its member genes. Statistical significance of inferred activity is examined using multiple independent self-contained tests followed by a competitive analysis. The method incorporates a new algorithm to identify a subset of genes that may regulate the extent of activity induced in a pathway. We present an in-depth evaluation of specificity, robustness, and reproducibility of our method. We benchmarked MIPA's false positive rate at less than 1%. Using transcriptomic profiles representing distinct physiological and disease states, we illustrate applicability of our method in (i) identifying gene–gene interactions in autophagy-dependent response to Salmonella infection, (ii) uncovering gene–environment interactions in host response to bacterial and viral pathogens and (iii) identifying driver genes and processes that contribute to wound healing and response to anti-TNFα therapy. We provide relevant experimental validation that corroborates the accuracy and advantage of our method.
    Keywords: Computational Methods, Genomics
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  • 76
    Publication Date: 2014-09-17
    Description: Viral recombination is a key evolutionary mechanism, aiding escape from host immunity, contributing to changes in tropism and possibly assisting transmission across species barriers. The ability to determine whether recombination has occurred and to locate associated specific recombination junctions is thus of major importance in understanding emerging diseases and pathogenesis. This paper describes a method for determining recombinant mosaics (and their proportions) originating from two parent genomes, using high-throughput sequence data. The method involves setting the problem geometrically and the use of appropriately constrained quadratic programming. Recombinants of the honeybee deformed wing virus and the Varroa destructor virus-1 are inferred to illustrate the method from both siRNAs and reads sampling the viral genome population (cDNA library); our results are confirmed experimentally. Matlab software (MosaicSolver) is available.
    Keywords: Computational Methods, Genomics
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  • 77
    Publication Date: 2014-08-02
    Description: We measure impacts of liberalising European agriculture on farm income distribution in western Germany. Unlike previous studies, we do not treat market income and policy support as independent income sources. We jointly apply a partial equilibrium and a programming model and find that liberalisation increases inequality in relative terms though it decreases inequality in absolute terms. In particular, we analyse the relevance of taking into account policy-induced production and market responses in an ex-ante inequality analysis. We find that although their inclusion generally does not affect the direction of distributional effects, it may have considerable impact on their magnitude.
    Keywords: D31 - Personal Income, Wealth, and Their Distributions, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 78
    Publication Date: 2014-08-02
    Description: In the past two decades, there has been an explosion of studies eliciting consumer willingness-to-pay for food attributes; however, this work has largely refrained from drawing a distinction between preferences for health, safety and quality on the one hand and consumers' subjective beliefs that the products studied possess these attributes, on the other. Using data from three experimental studies, along with structural economic models, we show that controlling for subjective beliefs can substantively alter the interpretation of results and the ultimate implications derived from a study. The results suggest the need to measure subjective beliefs in studies of consumer choice and to utilise the measures when making policy and marketing recommendations.
    Keywords: C91 - Laboratory, Individual Behavior, D83 - Search ; Learning ; Information and Knowledge ; Communication ; Belief, 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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  • 79
    Publication Date: 2012-10-30
    Description: We quantify the economic and health effects of a fruit and vegetable (F&V) voucher policy designed for increasing F&V consumption among low-income consumers. The analysis combined two models: an economic model which predicts how F&V consumption is affected by a change in policy, and a health model which evaluates the impact of a change in F&V consumption in terms of death avoided and life-years saved. We find that targeted F&V voucher policies can be more cost-effective than non-targeted policies based on tax decreases, but only when the targeted policy is focused narrowly on the lowest income consumers.
    Keywords: D61 - Allocative Efficiency ; Cost-Benefit Analysis, 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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  • 80
    Publication Date: 2012-10-30
    Description: The adoption of voluntary front-of-pack (FOP) nutrition labels by UK food retailers and manufacturers is explored. These labels highlight key nutrients, facilitating product comparisons. Information for 2,201 products launched between 2007 and 2009 was analysed. Binary and multinomial logistic regression models explore drivers of FOP label use. Products introduced more recently by retailers and certain food categories were more likely to carry FOP labels. Increasing the content of sodium and sugar decreased odds of FOP use in some categories, but with limited significance. Discussion includes policy options to optimise firm response and implications for evolving mandatory FOP labelling proposals.
    Keywords: L66 - Food ; Beverages ; Cosmetics ; Tobacco ; Wine and Spirits, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 81
    Publication Date: 2013-06-08
    Description: An appreciable fraction of introns is thought to have some function, but there is no obvious way to predict which specific intron is likely to be functional. We hypothesize that functional introns experience a different selection regime than non-functional ones and will therefore show distinct evolutionary histories. In particular, we expect functional introns to be more resistant to loss, and that this would be reflected in high conservation of their position with respect to the coding sequence. To test this hypothesis, we focused on introns whose function comes about from microRNAs and snoRNAs that are embedded within their sequence. We built a data set of orthologous genes across 28 eukaryotic species, reconstructed the evolutionary histories of their introns and compared functional introns with the rest of the introns. We found that, indeed, the position of microRNA- and snoRNA-bearing introns is significantly more conserved. In addition, we found that both families of RNA genes settled within introns early during metazoan evolution. We identified several easily computable intronic properties that can be used to detect functional introns in general, thereby suggesting a new strategy to pinpoint non-coding cellular functions.
    Keywords: Computational Methods, Genomics
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  • 82
    Publication Date: 2012-06-28
    Description: Identification of transcriptional regulatory regions and tracing their internal organization are important for understanding the eukaryotic cell machinery. Cis-regulatory modules (CRMs) of higher eukaryotes are believed to possess a regulatory ‘grammar’, or preferred arrangement of binding sites, that is crucial for proper regulation and thus tends to be evolutionarily conserved. Here, we present a method CORECLUST (COnservative REgulatory CLUster STructure) that predicts CRMs based on a set of positional weight matrices. Given regulatory regions of orthologous and/or co-regulated genes, CORECLUST constructs a CRM model by revealing the conserved rules that describe the relative location of binding sites. The constructed model may be consequently used for the genome-wide prediction of similar CRMs, and thus detection of co-regulated genes, and for the investigation of the regulatory grammar of the system. Compared with related methods, CORECLUST shows better performance at identification of CRMs conferring muscle-specific gene expression in vertebrates and early-developmental CRMs in Drosophila .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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    Topics: Biology
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  • 83
    Publication Date: 2012-08-23
    Description: The field of regulatory genomics today is characterized by the generation of high-throughput data sets that capture genome-wide transcription factor (TF) binding, histone modifications, or DNAseI hypersensitive regions across many cell types and conditions. In this context, a critical question is how to make optimal use of these publicly available datasets when studying transcriptional regulation. Here, we address this question in Drosophila melanogaster for which a large number of high-throughput regulatory datasets are available. We developed i-cisTarget (where the ‘ i ’ stands for integrative ), for the first time enabling the discovery of different types of enriched ‘regulatory features’ in a set of co-regulated sequences in one analysis, being either TF motifs or ‘ in vivo ’ chromatin features, or combinations thereof. We have validated our approach on 15 co-expressed gene sets, 21 ChIP data sets, 628 curated gene sets and multiple individual case studies, and show that meaningful regulatory features can be confidently discovered; that bona fide enhancers can be identified, both by in vivo events and by TF motifs; and that combinations of in vivo events and TF motifs further increase the performance of enhancer prediction.
    Keywords: Computational Methods, Genomics
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  • 84
    Publication Date: 2013-11-21
    Description: Traditional methods that aim to identify biomarkers that distinguish between two groups, like Significance Analysis of Microarrays or the t -test, perform optimally when such biomarkers show homogeneous behavior within each group and differential behavior between the groups. However, in many applications, this is not the case. Instead, a subgroup of samples in one group shows differential behavior with respect to all other samples. To successfully detect markers showing such imbalanced patterns of differential signal, a different approach is required. We propose a novel method, specifically designed for the Detection of Imbalanced Differential Signal (DIDS). We use an artificial dataset and a human breast cancer dataset to measure its performance and compare it with three traditional methods and four approaches that take imbalanced signal into account. Supported by extensive experimental results, we show that DIDS outperforms all other approaches in terms of power and positive predictive value. In a mouse breast cancer dataset, DIDS is the only approach that detects a functionally validated marker of chemotherapy resistance. DIDS can be applied to any continuous value data, including gene expression data, and in any context where imbalanced differential signal is manifested.
    Keywords: Computational Methods, Genomics
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  • 85
    Publication Date: 2013-11-22
    Description: We develop a structural econometric model of the vertical contracts between soft drink manufacturers and retailers to assess the impact of taxes or changes in production costs on consumer prices. Using individual data on food purchases from a representative survey of 19,000 French households in 2005, we estimate consumer demand using a random utility approach. Among a set of possible vertical relationships, we select the model that best fits the data. We evaluate the pass-through rate of changes in input costs (sugar) or of taxes and show that the industry over-shifts cost changes or excise taxes to the consumers. This result challenges the belief that firms do not pass on the full extent of cost changes or excise taxes to consumers.
    Keywords: H32 - Firm, I18 - Government Policy ; Regulation ; Public Health, L13 - Oligopoly and Other Imperfect Markets, 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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  • 86
    Publication Date: 2013-11-22
    Description: There is broad debate about including agriculture in greenhouse gas (GHG) reduction efforts such as the European Emissions Trading Scheme. Since most agricultural GHG emissions originate from non-point sources, they cannot be directly measured, and therefore have to be derived by calculation schemes (indicators). We designed five such GHG indicators for dairy farms and analyzed the trade-offs between their feasibility, measurement accuracy, and level of induced abatement costs. Analyses of induced abatement costs and calculation accuracy are based on emission reduction simulations with a highly-detailed single-farm optimization model. Feasibility is discussed in a qualitative manner. Our results indicate that the trade-offs depend on both farm characteristics and the targeted reduction level. In particular, the advantages of detailed indicators decrease for higher abatement levels. Only the least feasible indicator led to abatement costs that would result in emission efforts at given prices in the European Emissions Trading Scheme, although with a rather small potential. Our results thus suggest little potential for including dairy production into market-based reduction policies.
    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
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 87
    Publication Date: 2013-11-22
    Description: Using a lab experiment with 351 adult non-student subjects, we investigate the impact of labels and secondary information on willingness to pay (WTP) for foods that use various ingredients and processes that have been the subject of food policy discussions. We find a distinct asymmetry of WTP sensitivity between "Contains X" and "Free of X" labels with negatively-framed secondary information. The "Free of X" label has an impact only when secondary information is provided, and the negative impact of "Contains X" is mitigated by secondary information. We also consider how the results of our study can inform the ongoing debate about mandatory food labeling regulations in the United States: if mandatory labeling is adopted, providing additional information about what the product contains would significantly lessen the negative impact on demand.
    Keywords: M31 - Marketing, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 88
    Publication Date: 2013-11-22
    Description: Many agricultural support payments are based on past production with restrictions on how land may currently be used. When support payments to field crops are analyzed in a static framework, they do not directly impact current production decisions. However, over time, as relative profits change, these payments affect current output. The payments may keep land in less profitable production of program crops through restrictions prohibiting potentially more profitable endeavors such as cultivating fruits and vegetables. These payments have the potential to lead to production and trade distortions similar in magnitude to the distortions associated with direct production subsidies.
    Keywords: Q15 - Land Ownership and Tenure ; Land Reform ; Land Use ; Irrigation, Q17 - Agriculture in International Trade, 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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  • 89
    Publication Date: 2013-11-22
    Description: The recent reform of the Common Agricultural Policy, which decouples farm subsidies from production, is expected to impact on farmers’ production decisions. We perform a cross-country farm-level empirical analysis of farmers’ production responses to these reforms using a panel dataset for the EU15 countries for the period 2001–2007. We apply quasi-experimental empirical methods and find that the probability of a farm disinvesting decreased due to the policy change for most farms. However, the policy change facilitated exit for farms engaged in livestock production and those that were already in the process of leaving the sector.
    Keywords: D22 - Firm Behavior: Empirical Analysis, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, 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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  • 90
    Publication Date: 2013-11-22
    Description: This study examines the risk management opportunities for fluid milk market participants in the United States through the use of milk futures contracts. We estimate the nature of basis risk from 2002–2011 using modern time-series and econometric techniques. The results of this investigation reveal that at sufficient hedging intervals, using class III manufacturing milk futures contracts to cross-hedge fluid milk has the ability to reduce risk and provide revenue stability to market participants. When used in conjunction with milk futures, prediction algorithms for the closing basis facilitate more direct management of fluid milk price risk.
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q14 - Agricultural Finance, 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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  • 91
    Publication Date: 2014-07-23
    Description: Livestock Gross Margin Insurance for Dairy Cattle (LGM-Dairy) is a risk management tool for protecting milk income over feed cost margins. In this article, we examine the assumptions underpinning the method used to determine LGM-Dairy premiums. Analysis of the milk–feed dependence structure is conducted using copula methods, a rich set of tools that allow modelers to capture nonlinearities in dependence among variables of interest. We find a significant relationship between milk and feed prices that increases with time-to-maturity and severity of negative price shocks. Extremal, or tail, dependence is the propensity of dependence to concentrate in the tails of a distribution. A common theme in financial and actuarial applications and in agricultural crop revenue insurance is that tail dependence increases the risk to the underwriter and results in higher insurance premiums. We present, to our knowledge, the first case in which tail dependence may actually reduce actuarially fair premiums for an agricultural risk insurance product. We examine hedging effectiveness with LGM-Dairy and show that, even in the absence of basis or production risk, hedging horizon plays an important role in the ability of this tool to smooth farm income over feed cost margins over time. Rating methodology that accounts for tail dependence between milk and feed prices extends the optimal hedging horizon and increases hedging effectiveness of the LGM-Dairy program.
    Keywords: G13 - Contingent Pricing ; Futures Pricing, 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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  • 92
    Publication Date: 2014-07-23
    Description: The core of the literature on inter-sectoral labor migration is based on net present value models of investment in which individuals are assumed to migrate to take advantage of positive wage differentials. In this article, we argue that a real options approach, taken together with the adjustment costs associated with sectoral relocation, may provide a basis for explaining the migration of farm labor out of the agricultural sector. Given the irreversibility of migration decisions and uncertainty in the economy, potential migrants might choose to postpone migration, even in the face of positive wage differentials. Using annual U.S. employment data from between 1948 and 2009, our results indicate that large elasticities between economic incentives and out-farm migration are observed after a high threshold of wage differentials between farm and off-farm sectors is surpassed.
    Keywords: J62 - Job, Occupational, and Intergenerational Mobility, 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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  • 93
    Publication Date: 2014-08-01
    Description: Gene set enrichment testing can enhance the biological interpretation of ChIP-seq data. Here, we develop a method, ChIP-Enrich, for this analysis which empirically adjusts for gene locus length (the length of the gene body and its surrounding non-coding sequence). Adjustment for gene locus length is necessary because it is often positively associated with the presence of one or more peaks and because many biologically defined gene sets have an excess of genes with longer or shorter gene locus lengths. Unlike alternative methods, ChIP-Enrich can account for the wide range of gene locus length-to-peak presence relationships (observed in ENCODE ChIP-seq data sets). We show that ChIP-Enrich has a well-calibrated type I error rate using permuted ENCODE ChIP-seq data sets; in contrast, two commonly used gene set enrichment methods, Fisher's exact test and the binomial test implemented in Genomic Regions Enrichment of Annotations Tool (GREAT), can have highly inflated type I error rates and biases in ranking. We identify DNA-binding proteins, including CTCF, JunD and glucocorticoid receptor α (GRα), that show different enrichment patterns for peaks closer to versus further from transcription start sites. We also identify known and potential new biological functions of GRα. ChIP-Enrich is available as a web interface ( http://chip-enrich.med.umich.edu ) and Bioconductor package.
    Keywords: Computational Methods, Genomics
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  • 94
    Publication Date: 2014-08-02
    Description: With focus on seedstock herds selling replacements and a qualified class of diseases, this paper models producers' interdependent incentives to participate in a voluntary livestock disease control programme. Under strategic complementarity among participation decisions, momentum can build such that market premium for participation and participation rate increase sequentially. Non-participation, partial participation and full participation can all be Nash equilibria. Participation cost heterogeneity will dispose the outcome towards incomplete participation. We find plausible conditions under which temporary government subsidies cause tipping towards full participation. Applying parameters from the literature on Johne's disease, we illustrate factors that may affect participation.
    Keywords: D83 - Search ; Learning ; Information and Knowledge ; Communication ; Belief, I15 - Health and Economic Development, 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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  • 95
    Publication Date: 2012-08-03
    Description: The regulation of seasonal foreign farm labour (SFFL) in Germany distorts market outcomes and produces no significant benefits for any of the affected groups. Analysis of the media discourse on this regulation indicates that its persistence can be attributed to the political sensitivity of unemployment and related issues in Germany. To reach these conclusions, we propose a new method for the analysis of discourse data based on a Poisson change point model, and demonstrate that exogenous factors such as unemployment in Germany can explain structural breaks in the media discourse on SFFL in Germany.
    Keywords: J43 - Agricultural Labor Markets, P16 - Political Economy, 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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  • 96
    Publication Date: 2013-01-20
    Description: Identification of differentially expressed subnetworks from protein–protein interaction (PPI) networks has become increasingly important to our global understanding of the molecular mechanisms that drive cancer. Several methods have been proposed for PPI subnetwork identification, but the dependency among network member genes is not explicitly considered, leaving many important hub genes largely unidentified. We present a new method, based on a bagging Markov random field (BMRF) framework, to improve subnetwork identification for mechanistic studies of breast cancer. The method follows a maximum a posteriori principle to form a novel network score that explicitly considers pairwise gene interactions in PPI networks, and it searches for subnetworks with maximal network scores. To improve their robustness across data sets, a bagging scheme based on bootstrapping samples is implemented to statistically select high confidence subnetworks. We first compared the BMRF-based method with existing methods on simulation data to demonstrate its improved performance. We then applied our method to breast cancer data to identify PPI subnetworks associated with breast cancer progression and/or tamoxifen resistance. The experimental results show that not only an improved prediction performance can be achieved by the BMRF approach when tested on independent data sets, but biologically meaningful subnetworks can also be revealed that are relevant to breast cancer and tamoxifen resistance.
    Keywords: Computational Methods, Genomics
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  • 97
    Publication Date: 2013-01-20
    Description: miRDeep and its varieties are widely used to quantify known and novel micro RNA (miRNA) from small RNA sequencing (RNAseq). This article describes miRDeep*, our integrated miRNA identification tool, which is modeled off miRDeep, but the precision of detecting novel miRNAs is improved by introducing new strategies to identify precursor miRNAs. miRDeep* has a user-friendly graphic interface and accepts raw data in FastQ and Sequence Alignment Map (SAM) or the binary equivalent (BAM) format. Known and novel miRNA expression levels, as measured by the number of reads, are displayed in an interface, which shows each RNAseq read relative to the pre-miRNA hairpin. The secondary pre-miRNA structure and read locations for each predicted miRNA are shown and kept in a separate figure file. Moreover, the target genes of known and novel miRNAs are predicted using the TargetScan algorithm, and the targets are ranked according to the confidence score. miRDeep* is an integrated standalone application where sequence alignment, pre-miRNA secondary structure calculation and graphical display are purely Java coded. This application tool can be executed using a normal personal computer with 1.5 GB of memory. Further, we show that miRDeep* outperformed existing miRNA prediction tools using our LNCaP and other small RNAseq datasets. miRDeep* is freely available online at http://www.australianprostatecentre.org/research/software/mirdeep-star .
    Keywords: Computational Methods, Genomics
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  • 98
    Publication Date: 2013-01-20
    Description: The mRNA export complex TREX (TREX) is known to contain Aly, UAP56, Tex1 and the THO complex, among which UAP56 is required for TREX assembly. Here, we systematically investigated the role of each human TREX component in TREX assembly and its association with the mRNA. We found that Tex1 is essentially a subunit of the THO complex. Aly, THO and UAP56 are all required for assembly of TREX, in which Aly directly interacts with THO subunits Thoc2 and Thoc5. Both Aly and THO function in linking UAP56 to the cap-binding protein CBP80. Interestingly, association of UAP56 with the spliced mRNA, but not with the pre-mRNA, requires Aly and THO. Unexpectedly, we found that Aly and THO require each other to associate with the spliced mRNA. Consistent with these biochemical results, similar to Aly and UAP56, THO plays critical roles in mRNA export. Together, we propose that Aly, THO and UAP56 form a highly integrated unit to associate with the spliced mRNA and function in mRNA export.
    Keywords: Computational Methods, Genomics
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  • 99
    Publication Date: 2012-09-27
    Description: Due to advances in high-throughput biotechnologies biological information is being collected in databases at an amazing rate, requiring novel computational approaches that process collected data into new knowledge in a timely manner. In this study, we propose a computational framework for discovering modular structure, relationships and regularities in complex data. The framework utilizes a semantic-preserving vocabulary to convert records of biological annotations of an object, such as an organism, gene, chemical or sequence, into networks (Anets) of the associated annotations. An association between a pair of annotations in an Anet is determined by the similarity of their co-occurrence pattern with all other annotations in the data. This feature captures associations between annotations that do not necessarily co-occur with each other and facilitates discovery of the most significant relationships in the collected data through clustering and visualization of the Anet. To demonstrate this approach, we applied the framework to the analysis of metadata from the Genomes OnLine Database and produced a biological map of sequenced prokaryotic organisms with three major clusters of metadata that represent pathogens, environmental isolates and plant symbionts.
    Keywords: Computational Methods, Genomics
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  • 100
    Publication Date: 2012-09-27
    Description: We describe here a novel method for integrating gene and miRNA expression profiles in cancer using feed-forward loops (FFLs) consisting of transcription factors (TFs), miRNAs and their common target genes. The dChip-GemiNI (Gene and miRNA Network-based Integration) method statistically ranks computationally predicted FFLs by their explanatory power to account for differential gene and miRNA expression between two biological conditions such as normal and cancer. GemiNI integrates not only gene and miRNA expression data but also computationally derived information about TF–target gene and miRNA–mRNA interactions. Literature validation shows that the integrated modeling of expression data and FFLs better identifies cancer-related TFs and miRNAs compared to existing approaches. We have utilized GemiNI for analyzing six data sets of solid cancers (liver, kidney, prostate, lung and germ cell) and found that top-ranked FFLs account for ~20% of transcriptome changes between normal and cancer. We have identified common FFL regulators across multiple cancer types, such as known FFLs consisting of MYC and miR-15/miR-17 families, and novel FFLs consisting of ARNT, CREB1 and their miRNA partners. The results and analysis web server are available at http://www.canevolve.org/dChip-GemiNi .
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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