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  • Computational Methods, Genomics  (24)
  • Cooperatives  (22)
  • Oxford University Press  (46)
  • American Chemical Society
  • American Geophysical Union
  • American Physical Society
  • 2020-2023
  • 2015-2019  (46)
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  • Oxford University Press  (46)
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  • 2015-2019  (46)
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  • 1
    Publication Date: 2015-09-19
    Description: Recent releases of genome three-dimensional (3D) structures have the potential to transform our understanding of genomes. Nonetheless, the storage technology and visualization tools need to evolve to offer to the scientific community fast and convenient access to these data. We introduce simultaneously a database system to store and query 3D genomic data ( 3DBG ), and a 3D genome browser to visualize and explore 3D genome structures ( 3DGB ). We benchmark 3DBG against state-of-the-art systems and demonstrate that it is faster than previous solutions, and importantly gracefully scales with the size of data. We also illustrate the usefulness of our 3D genome Web browser to explore human genome structures. The 3D genome browser is available at http://3dgb.cs.mcgill.ca/ .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
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  • 2
    Publication Date: 2015-05-29
    Description: Identification of transcription units (TUs) encoded in a bacterial genome is essential to elucidation of transcriptional regulation of the organism. To gain a detailed understanding of the dynamically composed TU structures, we have used four strand-specific RNA-seq (ssRNA-seq) datasets collected under two experimental conditions to derive the genomic TU organization of Clostridium thermocellum using a machine-learning approach. Our method accurately predicted the genomic boundaries of individual TUs based on two sets of parameters measuring the RNA-seq expression patterns across the genome: expression-level continuity and variance. A total of 2590 distinct TUs are predicted based on the four RNA-seq datasets. Among the predicted TUs, 44% have multiple genes. We assessed our prediction method on an independent set of RNA-seq data with longer reads. The evaluation confirmed the high quality of the predicted TUs. Functional enrichment analyses on a selected subset of the predicted TUs revealed interesting biology. To demonstrate the generality of the prediction method, we have also applied the method to RNA-seq data collected on Escherichia coli and achieved high prediction accuracies. The TU prediction program named SeqTU is publicly available at https://code.google.com/p/seqtu/ . We expect that the predicted TUs can serve as the baseline information for studying transcriptional and post-transcriptional regulation in C. thermocellum and other bacteria.
    Keywords: Computational Methods, Genomics
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    Topics: Biology
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  • 3
    Publication Date: 2015-05-29
    Description: Detecting genetic variation is one of the main applications of high-throughput sequencing, but is still challenging wherever aligning short reads poses ambiguities. Current state-of-the-art variant calling approaches avoid such regions, arguing that it is necessary to sacrifice detection sensitivity to limit false discovery. We developed a method that links candidate variant positions within repetitive genomic regions into clusters. The technique relies on a resource, a thesaurus of genetic variation, that enumerates genomic regions with similar sequence. The resource is computationally intensive to generate, but once compiled can be applied efficiently to annotate and prioritize variants in repetitive regions. We show that thesaurus annotation can reduce the rate of false variant calls due to mappability by up to three orders of magnitude. We apply the technique to whole genome datasets and establish that called variants in low mappability regions annotated using the thesaurus can be experimentally validated. We then extend the analysis to a large panel of exomes to show that the annotation technique opens possibilities to study variation in hereto hidden and under-studied parts of the genome.
    Keywords: Computational Methods, Genomics
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  • 4
    Publication Date: 2015-05-03
    Description: Inversion polymorphisms have important phenotypic and evolutionary consequences in humans. Two different methodologies have been used to infer inversions from SNP dense data, enabling the use of large cohorts for their study. One approach relies on the differences in linkage disequilibrium across breakpoints; the other one captures the internal haplotype groups that tag the inversion status of chromosomes. In this article, we assessed the convergence of the two methods in the detection of 20 human inversions that have been reported in the literature. The methods converged in four inversions including inv-8p23, for which we studied its association with low-BMI in American children. Using a novel haplotype tagging method with control on inversion ancestry, we computed the frequency of inv-8p23 in two American cohorts and observed inversion haplotype admixture. Accounting for haplotype ancestry, we found that the European inverted allele in children carries a recessive risk of underweight, validated in an independent Spanish cohort (combined: OR= 2.00, P = 0.001). While the footprints of inversions on SNP data are complex, we show that systematic analyses, such as convergence of different methods and controlling for ancestry, can reveal the contribution of inversions to the ancestral composition of populations and to the heritability of human disease.
    Keywords: Computational Methods, Genomics
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  • 5
    Publication Date: 2015-05-03
    Description: The Metabolic Models Reconstruction Using Genome-Scale Information ( merlin ) tool is a user-friendly Java application that aids the reconstruction of genome-scale metabolic models for any organism that has its genome sequenced. It performs the major steps of the reconstruction process, including the functional genomic annotation of the whole genome and subsequent construction of the portfolio of reactions. Moreover, merlin includes tools for the identification and annotation of genes encoding transport proteins, generating the transport reactions for those carriers. It also performs the compartmentalisation of the model, predicting the organelle localisation of the proteins encoded in the genome and thus the localisation of the metabolites involved in the reactions promoted by such enzymes. The gene-proteins-reactions (GPR) associations are automatically generated and included in the model. Finally, merlin expedites the transition from genomic data to draft metabolic models reconstructions exported in the SBML standard format, allowing the user to have a preliminary view of the biochemical network, which can be manually curated within the environment provided by merlin .
    Keywords: Computational Methods, Genomics
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  • 6
    Publication Date: 2015-05-03
    Description: For eukaryotic cells, the biological processes involving regulatory DNA elements play an important role in cell cycle. Understanding 3D spatial arrangements of chromosomes and revealing long-range chromatin interactions are critical to decipher these biological processes. In recent years, chromosome conformation capture (3C) related techniques have been developed to measure the interaction frequencies between long-range genome loci, which have provided a great opportunity to decode the 3D organization of the genome. In this paper, we develop a new Bayesian framework to derive the 3D architecture of a chromosome from 3C-based data. By modeling each chromosome as a polymer chain, we define the conformational energy based on our current knowledge on polymer physics and use it as prior information in the Bayesian framework. We also propose an expectation-maximization (EM) based algorithm to estimate the unknown parameters of the Bayesian model and infer an ensemble of chromatin structures based on interaction frequency data. We have validated our Bayesian inference approach through cross-validation and verified the computed chromatin conformations using the geometric constraints derived from fluorescence in situ hybridization (FISH) experiments. We have further confirmed the inferred chromatin structures using the known genetic interactions derived from other studies in the literature. Our test results have indicated that our Bayesian framework can compute an accurate ensemble of 3D chromatin conformations that best interpret the distance constraints derived from 3C-based data and also agree with other sources of geometric constraints derived from experimental evidence in the previous studies. The source code of our approach can be found in https://github.com/wangsy11/InfMod3DGen .
    Keywords: Computational Methods, Genomics
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  • 7
    Publication Date: 2015-05-03
    Description: Characterization of cell type specific regulatory networks and elements is a major challenge in genomics, and emerging strategies frequently employ high-throughput genome-wide assays of transcription factor (TF) to DNA binding, histone modifications or chromatin state. However, these experiments remain too difficult/expensive for many laboratories to apply comprehensively to their system of interest. Here, we explore the potential of elucidating regulatory systems in varied cell types using computational techniques that rely on only data of gene expression, low-resolution chromatin accessibility, and TF–DNA binding specificities (‘motifs’). We show that static computational motif scans overlaid with chromatin accessibility data reasonably approximate experimentally measured TF–DNA binding. We demonstrate that predicted binding profiles and expression patterns of hundreds of TFs are sufficient to identify major regulators of ~200 spatiotemporal expression domains in the Drosophila embryo. We are then able to learn reliable statistical models of enhancer activity for over 70 expression domains and apply those models to annotate domain specific enhancers genome-wide. Throughout this work, we apply our motif and accessibility based approach to comprehensively characterize the regulatory network of fruitfly embryonic development and show that the accuracy of our computational method compares favorably to approaches that rely on data from many experimental assays.
    Keywords: Computational Methods, Genomics
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  • 8
    Publication Date: 2015-05-12
    Description: The Canadian farm share for five crop-based products and seven livestock-based products from 1997 to 2010 is calculated using a supply chain IO analysis. Significant differences exist in farm shares across food commodities with higher farm shares for livestock products and lower farm shares for grain-based products. The decline in the Canadian farm share for food consumed at home is driven in large part by the food purchasing habits of consumers. This paper also addresses the hypothesis that the decline in the Canadian farm share could be partially driven by rising input costs in post-farmgate processes or rising input costs that have greater impact on downstream sectors than primary agricultural producers. Three experiments were conducted to assess the impact of an increase in the cost of corn, energy, and farm labor would have on commodity output prices, farm returns, food expenditure, and farm share. In all three cases, the overall farm share increases, albeit by a small amount, suggesting that these shocks have a larger relative impact on the prices of agricultural commodities than the prices of marketing commodities used in post-farmgate activities. A two-period comparison of these simulations shows that energy (corn and farm labour) price shocks would have had a greater (lower) impact on the farm share in 2007 than 1997.
    Keywords: Q11 - Aggregate Supply and Demand Analysis ; Prices, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 9
    Publication Date: 2015-05-12
    Description: Farm households in developing countries generally allocate a major portion of their resources to staple food production, mainly for self-consumption. Hence, many of them are more or less delinked from the market. It is well recognized, however, that market participation is crucial for farm households to ensure a flow of cash income, leading to poverty alleviation and improved livelihoods. Thus, it is meaningful to understand what factors affect farm households' decision to sell food crops, which is important for strengthening their linkages with markets. The empirical literature on impacts of market linkages has seldom focused on the determinants of market participation. Using rice farm households in Bangladesh and applying a double-hurdle model, this article demonstrates that the provision of general education and the development of agricultural infrastructure such as irrigation facilities can strengthen the market linkages of farm households by enhancing their marketable surplus through increased production. By contrast, rainfall beyond the optimum level, drought spells, and flood incidences can weaken market linkages by reducing their marketable surplus through decreased production. Specific policies such as investment in general education are drawn up based on the findings.
    Keywords: C24 - Truncated and Censored Models, D01 - Microeconomic Behavior: Underlying Principles, D13 - Household Production and Intrahousehold Allocation, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 10
    Publication Date: 2015-12-29
    Description: This article investigates the collective choice of production standards by farmer and processor groups within a vertical food supply chain, taking into account their competition behaviours. We develop a general model to analyse the strategic motive of using standards to limit supply and shift rents between farmers and processors in the vertical chain. We find that a stringent standard can raise farmers' profit, but at the expense of processors. This is the case when the standard affects more variable costs than fixed cost of production, when the demand for the final product is inelastic, and when processors have a high degree of oligopoly power.
    Keywords: L13 - Oligopoly and Other Imperfect Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 11
    Publication Date: 2015-06-24
    Description: Much of the inter-individual variation in gene expression is triggered via perturbations of signaling networks by DNA variants. We present a novel probabilistic approach for identifying the particular pathways by which DNA variants perturb the signaling network. Our procedure, called PINE, relies on a systematic integration of established biological knowledge of signaling networks with data on transcriptional responses to various experimental conditions. Unlike previous approaches, PINE provides statistical aspects that are critical for prioritizing hypotheses for followup experiments. Using simulated data, we show that higher accuracy is attained with PINE than with existing methods. We used PINE to analyze transcriptional responses of immune dendritic cells to several pathogenic stimulations. PINE identified statistically significant genetic perturbations in the pathogen-sensing signaling network, suggesting previously uncharacterized regulatory mechanisms for functional DNA variants.
    Keywords: Computational Methods, Genomics
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  • 12
    Publication Date: 2015-08-29
    Description: Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package.
    Keywords: Computational Methods, Genomics
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  • 13
    Publication Date: 2015-08-29
    Description: Most mammalian genes have mRNA variants due to alternative promoter usage, alternative splicing, and alternative cleavage and polyadenylation. Expression of alternative RNA isoforms has been found to be associated with tumorigenesis, proliferation and differentiation. Detection of condition-associated transcription variation requires association methods. Traditional association methods such as Pearson chi-square test and Fisher Exact test are single test methods and do not work on count data with replicates. Although the Cochran Mantel Haenszel (CMH) approach can handle replicated count data, our simulations showed that multiple CMH tests still had very low power. To identify condition-associated variation of transcription, we here proposed a ranking analysis of chi-squares (RAX2) for large-scale association analysis. RAX2 is a nonparametric method and has accurate and conservative estimation of FDR profile. Simulations demonstrated that RAX2 performs well in finding condition-associated transcription variants. We applied RAX2 to primary T-cell transcriptomic data and identified 1610 (16.3%) tags associated in transcription with immune stimulation at FDR 〈 0.05. Most of these tags also had differential expression. Analysis of two and three tags within genes revealed that under immune stimulation short RNA isoforms were preferably used.
    Keywords: Computational Methods, Genomics
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  • 14
    Publication Date: 2015-07-10
    Description: In many developing countries, supermarkets are expanding rapidly. This affects farmers’ marketing options. Previous studies have analyzed welfare effects of smallholder participation in supermarket channels from a static perspective, using cross-section data. We develop a conceptual framework and use panel data to better understand participation and impact dynamics. The analysis focuses on vegetable producers in Kenya. Participation in supermarket channels is associated with income gains. However, many farmers have dropped out of the supermarket channel due to various constraints. The initial income gains cannot be sustained when returning to the traditional market. Organizational support may be needed to avoid widening income disparities.
    Keywords: L24 - Contracting Out ; Joint Ventures ; Technology Licensing, O12 - Microeconomic Analyses of Economic Development, O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 15
    Publication Date: 2015-12-16
    Description: To understand how transposon landscapes (TLs) vary across animal genomes, we describe a new method called the Transposon Insertion and Depletion AnaLyzer (TIDAL) and a database of 〉300 TLs in Drosophila melanogaster (TIDAL-Fly). Our analysis reveals pervasive TL diversity across cell lines and fly strains, even for identically named sub-strains from different laboratories such as the ISO1 strain used for the reference genome sequence. On average, 〉500 novel insertions exist in every lab strain, inbred strains of the Drosophila Genetic Reference Panel (DGRP), and fly isolates in the Drosophila Genome Nexus (DGN). A minority (〈25%) of transposon families comprise the majority (〉70%) of TL diversity across fly strains. A sharp contrast between insertion and depletion patterns indicates that many transposons are unique to the ISO1 reference genome sequence. Although TL diversity from fly strains reaches asymptotic limits with increasing sequencing depth, rampant TL diversity causes unsaturated detection of TLs in pools of flies. Finally, we show novel transposon insertions negatively correlate with Piwi-interacting RNA (piRNA) levels for most transposon families, except for the highly-abundant roo retrotransposon. Our study provides a useful resource for Drosophila geneticists to understand how transposons create extensive genomic diversity in fly cell lines and strains.
    Keywords: Computational Methods, Genomics
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  • 16
    Publication Date: 2015-04-21
    Description: Next-generation sequencing (NGS) approaches rapidly produce millions to billions of short reads, which allow pathogen detection and discovery in human clinical, animal and environmental samples. A major limitation of sequence homology-based identification for highly divergent microorganisms is the short length of reads generated by most highly parallel sequencing technologies. Short reads require a high level of sequence similarities to annotated genes to confidently predict gene function or homology. Such recognition of highly divergent homologues can be improved by reference-free ( de novo ) assembly of short overlapping sequence reads into larger contigs. We describe an ensemble strategy that integrates the sequential use of various de Bruijn graph and overlap-layout-consensus assemblers with a novel partitioned sub-assembly approach. We also proposed new quality metrics that are suitable for evaluating metagenome de novo assembly. We demonstrate that this new ensemble strategy tested using in silico spike-in, clinical and environmental NGS datasets achieved significantly better contigs than current approaches.
    Keywords: Computational Methods, Genomics
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  • 17
    Publication Date: 2015-04-21
    Description: Distinguishing between promoter-like sequences in bacteria that belong to true or abortive promoters, or to those that do not initiate transcription at all, is one of the important challenges in transcriptomics. To address this problem, we have studied the genome-reduced bacterium Mycoplasma pneumoniae , for which the RNAs associated with transcriptional start sites have been recently experimentally identified. We determined the contribution to transcription events of different genomic features: the –10, extended –10 and –35 boxes, the UP element, the bases surrounding the –10 box and the nearest-neighbor free energy of the promoter region. Using a random forest classifier and the aforementioned features transformed into scores, we could distinguish between true, abortive promoters and non-promoters with good –10 box sequences. The methods used in this characterization of promoters can be extended to other bacteria and have important applications for promoter design in bacterial genome engineering.
    Keywords: Computational Methods, Genomics
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  • 18
    Publication Date: 2015-05-21
    Description: Mobile phone coverage has expanded considerably throughout the developing world, particularly within sub-Saharan Africa. Existing evidence suggests that increased access to information technology has improved agricultural market efficiency for consumer markets and certain commodities, but there is less evidence of its impact on producer markets. Building on the work of Aker (2010) , we estimate the impact of mobile phone coverage on producer price dispersion for three commodities in Niger. Our results suggest that mobile phone coverage reduces spatial producer price dispersion by 6 percent for cowpea, a semi-perishable commodity. These effects are strongest for remote markets and during certain periods of the year. The introduction of mobile phone coverage has no effect on producer price dispersion for millet and sorghum, two staple grains that are less perishable and are commonly stored by farmers. There are no impacts of mobile phone coverage on producer price levels, but mobile phone coverage is associated with a reduction in the intra-annual price variation for cowpea.
    Keywords: O30 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0258-6770
    Electronic ISSN: 1564-698X
    Topics: Economics
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  • 19
    Publication Date: 2015-05-26
    Description: We modify the behavioural postulate of self-centred inequity aversion to explain producers' reluctance to fund generic fruit and vegetable advertising as a result of experiencing negative utility when others benefit more from a public good than themselves, but positive utility when they earn more than others. We find that higher variability in returns decreases the probability of a favourable vote. Conversely, if information about payoffs is incomplete, if subjects are allowed to experience a trial run of a generic advertising programme, if returns are equal across producers, or if there is government support for the programme, the likelihood of approval rises.
    Keywords: H41 - Public Goods, M37 - Advertising, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 20
    Publication Date: 2015-04-21
    Description: MicroRNAs (miRNAs) are involved in the regulation of gene expression at a post-transcriptional level. As such, monitoring miRNA expression has been increasingly used to assess their role in regulatory mechanisms of biological processes. In large scale studies, once miRNAs of interest have been identified, the target genes they regulate are often inferred using algorithms or databases. A pathway analysis is then often performed in order to generate hypotheses about the relevant biological functions controlled by the miRNA signature. Here we show that the method widely used in scientific literature to identify these pathways is biased and leads to inaccurate results. In addition to describing the bias and its origin we present an alternative strategy to identify potential biological functions specifically impacted by a miRNA signature. More generally, our study exemplifies the crucial need of relevant negative controls when developing, and using, bioinformatics methods.
    Keywords: Computational Methods, Genomics
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  • 21
    Publication Date: 2015-07-10
    Description: We argue that farm survival is influenced by neighboring farmers’ characteristics and, in particular, by the direct payments neighboring farmers receive. The article shows empirically that these interdependencies are crucial for an assessment of the effects of direct payments on farm survival. Using spatially explicit farm-level data for nearly all Norwegian farms, a spatial probit model is estimated to explain farm survival from 1999 to 2009 controlling for spatial farm interdependence. We show that ignoring spatial interdependencies between farms leads to a substantial overestimation of the effects of direct payments on farm survival. To our knowledge, this article is the first attempt to empirically analyze the importance of neighboring interdependencies for the effects of direct payments on farm survival.
    Keywords: C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models, C25 - Discrete Regression and Qualitative Choice Models, Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 22
    Publication Date: 2015-07-10
    Description: Existing analyses of market participation are based on a "double-hurdle" modeling approach. Such models are appropriate only when all members of the population of interest actually produce the good. In some contexts, however (e.g., smallholder farmers), many members of the population do not produce particular goods that they could produce and that their neighbors do produce. Policies influencing market participation among producers may thus also induce additional farmers to become producers. Previous double-hurdle approaches do not allow explicitly for this possibility. To address these limitations, this article presents a "triple-hurdle" approach with an initial stage that includes nonproducers. The model is used to identify the factors associated with Kenyan smallholder farmers choosing to participate in dairy production, and the role that these producers choose to play (or not) in the marketplace. In the midst of debates underway over the privatization of the parastatal Kenya Creameries Company, new knowledge about smallholder participation in dairy could be an important contribution. Results suggest the importance of rural electrification, training, and improved grazing practices. We find that expected net sales are significantly higher when farmers have access to informal private markets. We also describe a version of the ordered tobit model that includes nonproducers and is nested in our triple-hurdle model. A likelihood ratio test shows the latter to be a significantly better fit to our data. We discuss how insights gained from this study differ from the insights that would come from a double-hurdle ordered tobit that also includes nonproducers.
    Keywords: C51 - Model Construction and Estimation, C81 - Methodology for Collecting, Estimating, and Organizing Microeconomic Data, O12 - Microeconomic Analyses of Economic Development, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 23
    Publication Date: 2015-07-10
    Description: The dimensions that define a food product have expanded rapidly to include characteristics of the production process, marketing arrangements, and implications that production and consumption of the product have for the environment. Some market intermediaries have responded by requiring that their suppliers abide by restrictive production practices. We examine the economic effects of such restrictions and apply this analysis to limitations on the use of antibiotics in U.S. pork production. Results from conceptual and simulation analyses show that, in the absence of demand growth, less pork is sold due to higher costs in the restricted segment, and both pork consumers (on average) and producers are harmed. Demand growth of between 6–11% from adding new consumers who will consume the restricted (antibiotic-free) product but not the conventional product is needed to return consumer surplus to the level in the base case, and between 2–4% demand growth was required to return producer surplus to base. When restricted and conventional products are modeled using a vertical differentiation framework, results depend importantly on the ease with which consumers can switch to a seller who offers their desired product type. Significant distributional impacts among consumers are present when switching costs are prohibitive.
    Keywords: I18 - Government Policy ; Regulation ; Public Health, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 24
    Publication Date: 2015-09-12
    Description: Community Supported Agriculture (CSA) contracts allow consumers to buy claims on a farm's future production. In turn, the consumer provides working capital to the farm during the growing season. CSA contracts also provide risk management for farmers with limited access to Federal crop insurance by transferring part of the farm's risk to the consumer. We derive a theory of CSA contract pricing for the two most prevalent types of CSA contracts: yield contracts, in which consumers receive a percentage of the farm's production, and weight contracts, in which consumers receive fixed quantities. We develop a two-period model in which expected utility maximizing producers and consumers engage in CSA contracting in the first period based on anticipation of yields and spot prices in the second period. Using the model, we generate several testable hypotheses to be explored in future research. Additionally, we present an overview of the data necessary to test the propositions and potential challenges that might arise in related empirical work.
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q14 - Agricultural Finance
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 25
    Publication Date: 2015-09-30
    Description: In cancer research, background models for mutation rates have been extensively calibrated in coding regions, leading to the identification of many driver genes, recurrently mutated more than expected. Noncoding regions are also associated with disease; however, background models for them have not been investigated in as much detail. This is partially due to limited noncoding functional annotation. Also, great mutation heterogeneity and potential correlations between neighboring sites give rise to substantial overdispersion in mutation count, resulting in problematic background rate estimation. Here, we address these issues with a new computational framework called LARVA. It integrates variants with a comprehensive set of noncoding functional elements, modeling the mutation counts of the elements with a β-binomial distribution to handle overdispersion. LARVA, moreover, uses regional genomic features such as replication timing to better estimate local mutation rates and mutational hotspots. We demonstrate LARVA's effectiveness on 760 whole-genome tumor sequences, showing that it identifies well-known noncoding drivers, such as mutations in the TERT promoter. Furthermore, LARVA highlights several novel highly mutated regulatory sites that could potentially be noncoding drivers. We make LARVA available as a software tool and release our highly mutated annotations as an online resource ( larva.gersteinlab.org ).
    Keywords: Computational Methods, Genomics
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  • 26
    Publication Date: 2015-10-31
    Description: We consider how cost heterogeneity and market power affect voting power in producer referenda for mandatory agricultural marketing organisations with generic promotion programmes in the United States. We measure voting power using the Banzhaf Power Index and propose a new version of this index based on the profit-maximising theory of the firm that provides an improved estimate of voting power. Examining several types of demand shifts and voting rules, we find that both Banzhaf Power and our new measure vary considerably depending on the market structure and level of cost heterogeneity.
    Keywords: D71 - Social Choice ; Clubs ; Committees ; Associations, D72 - Models of Political Processes: Rent-Seeking, Elections, Legislatures, and Voting Behavior, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 27
    Publication Date: 2015-12-02
    Description: Alu insertions have contributed to 〉11% of the human genome and ~30–35 Alu subfamilies remain actively mobile, yet the characterization of polymorphic Alu insertions from short-read data remains a challenge. We build on existing computational methods to combine Alu detection and de novo assembly of WGS data as a means to reconstruct the full sequence of insertion events from Illumina paired end reads. Comparison with published calls obtained using PacBio long-reads indicates a false discovery rate below 5%, at the cost of reduced sensitivity due to the colocation of reference and non-reference repeats. We generate a highly accurate call set of 1614 completely assembled Alu variants from 53 samples from the Human Genome Diversity Project (HGDP) panel. We utilize the reconstructed alternative insertion haplotypes to genotype 1010 fully assembled insertions, obtaining 〉99% agreement with genotypes obtained by PCR. In our assembled sequences, we find evidence of premature insertion mechanisms and observe 5' truncation in 16% of Alu Ya5 and Alu Yb8 insertions. The sites of truncation coincide with stem-loop structures and SRP9/14 binding sites in the Alu RNA, implicating L1 ORF2p pausing in the generation of 5' truncations. Additionally, we identified variable Alu J and Alu S elements that likely arose due to non-retrotransposition mechanisms.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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  • 28
    Publication Date: 2015-03-14
    Description: A milk scandal erupted in China in 2008 when the industrial chemical melamine was found in dairy products nationwide. While many Chinese dairy companies faced huge losses or bankruptcy as a result, one small firm, Dairy United, accelerated its development. Dairy United is one of the fastest-growing and most innovative Chinese dairy producers, one that features an unusual organizational structure and business model. Unlike most corporate and cooperative dairies that purchase cows on the market, Dairy United leases dairy cows from local farmers, giving it access to its primary asset without a large up-front investment, and letting the firm grow its dairy herds with newborn heifers. In return, farmers receive fixed payments biannually, but relinquish control rights and residual claims to the firm. Thus, Dairy United's leasing is helping transform Chinese milk production from a backyard, labor-intensive activity to a more industrialized mode of farming. The case is particularly interesting for understanding applications of agency theory in agribusiness.
    Keywords: A22 - Undergraduate, A23 - Graduate, D23 - Organizational Behavior ; Transaction Costs ; Property Rights, M10 - General, M20 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 29
    Publication Date: 2015-03-14
    Description: Hoover Seeds is a fictional case study written to illustrate the challenges faced by food and agribusiness firms that are transitioning from small, entrepreneurial businesses to larger, more professionally managed enterprises. Though fictional, the competitive and financial situation of Hoover Seeds is based on realistic facts. The case introduces Dan Hoover, the Chief Executive Officer of Hoover Seeds, Inc., a small, family-owned and operated seed company in Ohio. Founded by his grandfather, Dan has worked his way up the ranks of the company and, now leading the company, has worked to expand market share. The case study details the sales, production, administration, and finances of the firm. Exhibit A includes a full set of financial statements over four years. The case also has industry context with market, customer, and competitor details.
    Keywords: Q10 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 30
    Publication Date: 2015-03-14
    Description: Organic Valley is the largest organic cooperative in North America, one of two national buyers of organic milk, and one of two national organic dairy manufacturers. The cooperative's official name is Cooperative of Regional Organic Producers, and it is organized as a new generation cooperative, owned and controlled by patron-members who also transact with the business. Organic Valley has a unique policy of sustainable and stable producer pay-pricing for organic milk in the emerging organic dairy industry. This case presents challenges faced by the leadership of Organic Valley cooperative to maintain a stable and economically sustainable pay price for its farmer members. This case also introduces students to a new organizational form of cooperative, including its governance, the industry, and the market structure in which the cooperative operates. The objective of this case study is to improve student understanding of economic concepts such as theories of the imperfect market, demand and supply, and organizational design. The case also aims to help students improve their critical thinking and analytical skills by exploring the possibility of maintaining a unique sustainable and stable pricing method through the data provided. Additionally, the story introduces the economic role that organic dairy operation might play for small and medium-size dairy farmers as they attempt to maintain an economically sustainable family farm lifestyle.
    Keywords: A22 - Undergraduate, A23 - Graduate, Q01 - Sustainable Development, Q11 - Aggregate Supply and Demand Analysis ; Prices, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 31
    Publication Date: 2015-03-14
    Description: Mutual information (MI), a quantity describing the nonlinear dependence between two random variables, has been widely used to construct gene regulatory networks (GRNs). Despite its good performance, MI cannot separate the direct regulations from indirect ones among genes. Although the conditional mutual information (CMI) is able to identify the direct regulations, it generally underestimates the regulation strength, i.e. it may result in false negatives when inferring gene regulations. In this work, to overcome the problems, we propose a novel concept, namely conditional mutual inclusive information (CMI2), to describe the regulations between genes. Furthermore, with CMI2, we develop a new approach, namely CMI2NI (CMI2-based network inference), for reverse-engineering GRNs. In CMI2NI, CMI2 is used to quantify the mutual information between two genes given a third one through calculating the Kullback–Leibler divergence between the postulated distributions of including and excluding the edge between the two genes. The benchmark results on the GRNs from DREAM challenge as well as the SOS DNA repair network in Escherichia coli demonstrate the superior performance of CMI2NI. Specifically, even for gene expression data with small sample size, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the regulation strength between genes. As a case study, CMI2NI was also used to reconstruct cancer-specific GRNs using gene expression data from The Cancer Genome Atlas (TCGA). CMI2NI is freely accessible at http://www.comp-sysbio.org/cmi2ni .
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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  • 32
    Publication Date: 2015-04-02
    Description: High-throughput sequencing of DNA coding regions has become a common way of assaying genomic variation in the study of human diseases. Copy number variation (CNV) is an important type of genomic variation, but detecting and characterizing CNV from exome sequencing is challenging due to the high level of biases and artifacts. We propose CODEX, a normalization and CNV calling procedure for whole exome sequencing data. The Poisson latent factor model in CODEX includes terms that specifically remove biases due to GC content, exon capture and amplification efficiency, and latent systemic artifacts. CODEX also includes a Poisson likelihood-based recursive segmentation procedure that explicitly models the count-based exome sequencing data. CODEX is compared to existing methods on a population analysis of HapMap samples from the 1000 Genomes Project, and shown to be more accurate on three microarray-based validation data sets. We further evaluate performance on 222 neuroblastoma samples with matched normals and focus on a well-studied rare somatic CNV within the ATRX gene. We show that the cross-sample normalization procedure of CODEX removes more noise than normalizing the tumor against the matched normal and that the segmentation procedure performs well in detecting CNVs with nested structures.
    Keywords: Computational Methods, Genomics
    Print ISSN: 0305-1048
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  • 33
    Publication Date: 2015-01-10
    Description: Comprehensive motif discovery under experimental conditions is critical for the global understanding of gene regulation. To generate a nearly complete list of human DNA motifs under given conditions, we employed a novel approach to de novo discover significant co-occurring DNA motifs in 349 human DNase I hypersensitive site datasets. We predicted 845 to 1325 motifs in each dataset, for a total of 2684 non-redundant motifs. These 2684 motifs contained 54.02 to 75.95% of the known motifs in seven large collections including TRANSFAC. In each dataset, we also discovered 43 663 to 2 013 288 motif modules, groups of motifs with their binding sites co-occurring in a significant number of short DNA regions. Compared with known interacting transcription factors in eight resources, the predicted motif modules on average included 84.23% of known interacting motifs. We further showed new features of the predicted motifs, such as motifs enriched in proximal regions rarely overlapped with motifs enriched in distal regions, motifs enriched in 5' distal regions were often enriched in 3' distal regions, etc. Finally, we observed that the 2684 predicted motifs classified the cell or tissue types of the datasets with an accuracy of 81.29%. The resources generated in this study are available at http://server.cs.ucf.edu/predrem/ .
    Keywords: Computational Methods, Genomics
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  • 34
    Publication Date: 2015-11-17
    Description: The prediction of novel pre-microRNA (miRNA) from genomic sequence has received considerable attention recently. However, the majority of studies have focused on the human genome. Previous studies have demonstrated that sensitivity (correctly detecting true miRNA) is sustained when human-trained methods are applied to other species, however they have failed to report the dramatic drop in specificity (the ability to correctly reject non-miRNA sequences) in non-human genomes. Considering the ratio of true miRNA sequences to pseudo-miRNA sequences is on the order of 1:1000, such low specificity prevents the application of most existing tools to non-human genomes, as the number of false positives overwhelms the true predictions. We here introduce a framework (SMIRP) for creating species-specific miRNA prediction systems, leveraging sequence conservation and phylogenetic distance information. Substantial improvements in specificity and precision are obtained for four non-human test species when our framework is applied to three different prediction systems representing two types of classifiers (support vector machine and Random Forest), based on three different feature sets, with both human-specific and taxon-wide training data. The SMIRP framework is potentially applicable to all miRNA prediction systems and we expect substantial improvement in precision and specificity, while sustaining sensitivity, independent of the machine learning technique chosen.
    Keywords: Computational Methods, Genomics
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  • 35
    Publication Date: 2015-08-29
    Description: Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool ( cancerlandscapes.org ), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets.
    Keywords: Computational Methods, Genomics
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  • 36
    Publication Date: 2015-07-25
    Description: Transposable elements (TEs) are mobile genomic DNA sequences found in most organisms. They so densely populate the genomes of many eukaryotic species that they are often the major constituents. With the rapid generation of many plant genome sequencing projects over the past few decades, there is an urgent need for improved TE annotation as a prerequisite for genome-wide studies. Analogous to the use of RNA-seq for gene annotation, we propose a new method for de novo TE annotation that uses as a guide 24 nt-siRNAs that are a part of TE silencing pathways. We use this new approach, called TASR (for Transposon Annotation using Small RNAs), for de novo annotation of TEs in Arabidopsis , rice and soybean and demonstrate that this strategy can be successfully applied for de novo TE annotation in plants. Executable PERL is available for download from: http://tasr-pipeline.sourceforge.net/
    Keywords: Computational Methods, Genomics
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  • 37
    Publication Date: 2015-07-29
    Description: Models describing the development of collective reputation have focused on the impact of past performance measures, but ignore the role of various marketing efforts for food and beverage products that highlight appellation information. We designed a laboratory experiment and used auction data to estimate consumer response to information tying US wine regions to famous wine production regions in France, a phenomenon we define as reputation tapping. Results show that reputation tapping increases bids for the wines produced in burgeoning US wine regions. Our findings also suggest that full protection of geographical indications may require monitoring of activities beyond those by individual firms.
    Keywords: C91 - Laboratory, Individual Behavior, L14 - Transactional Relationships ; Contracts and Reputation ; Networks, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 38
    Publication Date: 2015-10-31
    Description: Many cooperatives and related organisations use revenue pooling wherein products across multiple quality levels are commingled. Recent work showed that pooling ensures farmers against risks due to stochastic product quality and counteracts farmers' tendency to overproduce high-quality product. We extend their analysis to incorporate farmers who are heterogeneous in ability to produce high-quality products. We show that the revenue-pooling benefits of cooperation may be sufficient to cause high-quality producers to join a cooperative and pool revenues, at least partially, with lower-quality producers. We explore the producer and market characteristics conducive to the emergence of stable revenue-pooling cooperatives.
    Keywords: P13 - Cooperative Enterprises, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 39
    Publication Date: 2015-10-31
    Description: What causes firms to behave the way they do when they face different investment opportunities? We argue that both people and processes are behind the decision-making of project implementation. Member and professional CEOs of cooperatives differ regarding their managerial vision towards upstream and downstream projects. Cooperatives with member CEOs are upstream focused and it is reflected by the cascading effect of negative vision bias towards downstream projects. When downstream activities become more important, cooperatives need to replace the member CEOs with professional CEOs. However, a cooperative with a professional CEO may still be in a disadvantageous position if the member-dominated Board of Directors' negative bias towards downstream projects is too strong, which may result in an investor owned firm being the efficient governance structure.
    Keywords: D21 - Firm Behavior, L23 - Organization of Production, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 40
    Publication Date: 2015-02-06
    Description: We analyse the effects of geographical indication labelling on quality choices and welfare in a vertical differentiation framework with two attributes of goods, gustatory quality and geographical origin. We investigate two extreme cases of the protected designation of origin (PDO) label: a denomination standard, which guarantees only the origin of the product without any requirement on production specifications, and a minimum quality requirement, which guarantees both the origin and the quality of the product. We find that as long the PDO good is the high-quality good, binding production specifications on the quality level adversely affect the PDO producer(s).
    Keywords: D21 - Firm Behavior, L13 - Oligopoly and Other Imperfect Markets, L15 - Information and Product Quality ; Standardization and Compatibility, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 41
    Publication Date: 2015-02-28
    Description: A mixed effects model is used to estimate intercepts, price and expenditure elasticities for vegetables, meat and fish in different cohorts. Results from Wald tests reveal that intercepts for fish are higher for older cohorts than for younger cohorts, and expenditure elasticities for meat are higher for older cohorts than for younger cohorts. The implication is that over time, when younger cohorts replace older cohorts, the total expenditure share for fish is likely to decrease contributing to a negative trend in fish consumption. For meat, the total expenditure elasticity is likely to decrease.
    Keywords: D12 - Consumer Economics: Empirical Analysis, J10 - General, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
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    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 42
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    Oxford University Press
    Publication Date: 2015-02-28
    Description: Pricing and selling strategies in the retail sector are hotly debated in policy circles. This article analyses the impact of sales below cost on the negotiation outcomes in intermediate goods markets. Assuming that consumers have a sufficiently strong preference for one-stop shopping, we model below-cost pricing as the result of a profit-maximising cross-subsidisation strategy of a multi-product retailer. We find that below-cost pricing improves the supplier's bargaining position vis-à-vis the retailer. Correspondingly, the supplier of the loss-leader benefits from the retailer's below-cost pricing strategy, though the retailer is better off under a ban of sales below cost. These results disprove the often expressed fear that retailers use sales at a loss to squeeze wholesale prices.
    Keywords: L22 - Firm Organization and Market Structure, L42 - Vertical Restraints ; Resale Price Maintenance ; Quantity Discounts, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 43
    Publication Date: 2015-02-28
    Description: This article investigates member deliveries in agricultural marketing cooperatives. Since cooperatives depend on members’ contributions to achieve efficiency in processing and marketing, side-selling by members poses a threat to the economic viability of cooperatives in the long run. We develop a model for the farmers’ marketing decision that relates farm size to the share of produce delivered to the cooperative. Based on survey data from cooperatively organised coffee farmers in Costa Rica, we find that the share delivered to cooperatives decreases with farm size, albeit at a decreasing rate. The empirical results thus confirm the theoretical model prediction of a u-shaped relationship between farm size and member deliveries.
    Keywords: Q12 - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 0165-1587
    Electronic ISSN: 1464-3618
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 44
    Publication Date: 2015-03-01
    Description: RNA-Seq is gradually becoming the standard tool for transcriptomic expression studies in biological research. Although considerable progress has been recorded in the development of statistical algorithms for the detection of differentially expressed genes using RNA-Seq data, the list of detected genes can differ significantly between algorithms. We present a new method (PANDORA) that combines multiple algorithms toward a summarized result, more efficiently reflecting true experimental outcomes. This is achieved through the systematic combination of several analysis algorithms, by weighting their outcomes according to their performance with realistically simulated data sets generated from real data. Results supported by the analysis of both simulated and real data from different organisms as well as correlation with PolII occupancy demonstrate that PANDORA improves the detection of differential expression. It accomplishes this by optimizing the tradeoff between standard performance measurements, such as precision and sensitivity.
    Keywords: Computational Methods, Genomics
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  • 45
    Publication Date: 2015-02-11
    Description: We analyze the inclusiveness and effectiveness of agricultural cooperatives in Rwanda. We estimate mean income and poverty effects of cooperative membership using propensity score matching techniques. We analyze heterogeneous treatment effects across farmers by analyzing how estimated treatment effects vary over farm and farmer characteristics and over the estimated propensity score. We find that cooperative membership in general increases income and reduces poverty and that these effects are largest for larger farms and in more remote areas. We find evidence of a negative selection because impact is largest for farmers with the lowest propensity to be a cooperative member .
    Keywords: I32 - Measurement and Analysis of Poverty, J54 - Producer Cooperatives ; Labor Managed Firms, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
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  • 46
    Publication Date: 2015-02-18
    Description: We define a new category of candidate tumor drivers in cancer genome evolution: ‘selected expression regulators’ (SERs)—genes driving dysregulated transcriptional programs in cancer evolution. The SERs are identified from genome-wide tumor expression data with a novel method, namely SPARROW ( SPAR se selected exp R essi O n regulators identified W ith penalized regression). SPARROW uncovers a previously unknown connection between cancer expression variation and driver events, by using a novel sparse regression technique. Our results indicate that SPARROW is a powerful complementary approach to identify candidate genes containing driver events that are hard to detect from sequence data, due to a large number of passenger mutations and lack of comprehensive sequence information from a sufficiently large number of samples. SERs identified by SPARROW reveal known driver mutations in multiple human cancers, along with known cancer-associated processes and survival-associated genes, better than popular methods for inferring gene expression networks. We demonstrate that when applied to acute myeloid leukemia expression data, SPARROW identifies an apoptotic biomarker ( PYCARD ) for an investigational drug obatoclax. The PYCARD and obatoclax association is validated in 30 AML patient samples.
    Keywords: Computational Methods, Genomics
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