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  • 1
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    Topology independent comparison of RNA 3D structures using the CLICK algorithm (2017)
    Oxford University Press
    Details
    Publication Date: 2017-01-10
    Description: RNA molecules are attractive therapeutic targets because non-coding RNA molecules have increasingly been found to play key regulatory roles in the cell. Comparing and classifying RNA 3D structures yields unique insights into RNA evolution and function. With the rapid increase in the number of atomic-resolution RNA structures, it is crucial to have effective tools to classify RNA structures and to investigate them for structural similarities at different resolutions. We previously developed the algorithm CLICK to superimpose a pair of protein 3D structures by clique matching and 3D least squares fitting. In this study, we extend and optimize the CLICK algorithm to superimpose pairs of RNA 3D structures and RNA–protein complexes, independent of the associated topologies. Benchmarking Rclick on four different datasets showed that it is either comparable to or better than other structural alignment methods in terms of the extent of structural overlaps. Rclick also recognizes conformational changes between RNA structures and produces complementary alignments to maximize the extent of detectable similarity. Applying Rclick to study Ribonuclease III protein correctly aligned the RNA binding sites of RNAse III with its substrate. Rclick can be further extended to identify ligand-binding pockets in RNA. A web server is developed at http://mspc.bii.a-star.edu.sg/minhn/rclick.html .
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 2
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    The Financialization of Food? (2017)
    Oxford University Press
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    Publication Date: 2017-01-05
    Description: Commodity-equity return co-movements rose dramatically during the Great Recession. This development took place following what has been dubbed the "financialization" of commodity markets. We first document changes since 1995 in the relative importance of financial institutions’ activity in agricultural futures markets. We then use a structural vector autoregression (VAR) model to ascertain the role of that activity in explaining correlations between weekly grain, livestock, and equity returns from 1995–2015. We provide robust evidence that, accounting for shocks that are idiosyncratic to agricultural markets, world business cycle shocks have a substantial and long-lasting impact on the latter’s co-movements with financial markets. In contrast, changes in the intensity of financial speculation have an impact on cross-market return linkages that is shorter-lived and not statistically significant in all model specifications.
    Keywords: G12 - Asset Pricing ; Trading volume ; Bond Interest Rates, G13 - Contingent Pricing ; Futures Pricing, 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
    Published by Oxford University Press
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  • 3
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    Averting Behaviors of Very Small Radiation Exposure via Food Consumption after the Fukushima Nuclear Power Station Accident (2017)
    Oxford University Press
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    Publication Date: 2017-01-05
    Description: This article considers changes in the perception and avoidance behavior of food risks over time. In Japan, consumers’ concerns about the risks of radiation exposure via food consumption rose rapidly after the accident at the Fukushima Daiichi Nuclear Power Station in 2011. We conducted choice experiment surveys three months, seven months, and eleven months after the Fukushima accident and simulated the conditional means of willingness to pay (WTP) for avoiding radiation exposure via food consumption in each survey period. The results show that although the characteristics of changes in averting behaviors vary depending on the type of food, the heterogeneity in WTP values for avoiding food risk tends to reduce (broaden) when their magnitude decreases (increases).
    Keywords: Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy, Q51 - Valuation of Environmental Effects
    Print ISSN: 0002-9092
    Electronic ISSN: 1467-8276
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
    Published by Oxford University Press
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  • 4
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    Personalized characterization of diseases using sample-specific networks (2016)
    Oxford University Press
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    Publication Date: 2016-12-17
    Description: A complex disease generally results not from malfunction of individual molecules but from dysfunction of the relevant system or network, which dynamically changes with time and conditions. Thus, estimating a condition-specific network from a single sample is crucial to elucidating the molecular mechanisms of complex diseases at the system level. However, there is currently no effective way to construct such an individual-specific network by expression profiling of a single sample because of the requirement of multiple samples for computing correlations. We developed here with a statistical method, i.e. a sample-specific network (SSN) method, which allows us to construct individual-specific networks based on molecular expressions of a single sample. Using this method, we can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information. Extensive analysis by using the Cancer Genome Atlas data not only demonstrated the effectiveness of the method, but also found new individual-specific driver genes and network patterns for various types of cancer. Biological experiments on drug resistance further validated one important advantage of our method over the traditional methods, i.e. we can even identify such drug resistance genes that actually have no clear differential expression between samples with and without the resistance, due to the additional network information.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Order restricted inference for oscillatory systems for detecting rhythmic signals (2016)
    Oxford University Press
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    Publication Date: 2016-12-17
    Description: Motivation: Many biological processes, such as cell cycle, circadian clock, menstrual cycles, are governed by oscillatory systems consisting of numerous components that exhibit rhythmic patterns over time. It is not always easy to identify such rhythmic components. For example, it is a challenging problem to identify circadian genes in a given tissue using time-course gene expression data. There is a great potential for misclassifying non-rhythmic as rhythmic genes and vice versa. This has been a problem of considerable interest in recent years. In this article we develop a constrained inference based methodology called Order Restricted Inference for Oscillatory Systems (ORIOS) to detect rhythmic signals. Instead of using mathematical functions (e.g. sinusoidal) to describe shape of rhythmic signals, ORIOS uses mathematical inequalities. Consequently, it is robust and not limited by the biologist's choice of the mathematical model. We studied the performance of ORIOS using simulated as well as real data obtained from mouse liver, pituitary gland and data from NIH3T3, U2OS cell lines. Our results suggest that, for a broad collection of patterns of gene expression, ORIOS has substantially higher power to detect true rhythmic genes in comparison to some popular methods, while also declaring substantially fewer non-rhythmic genes as rhythmic. Availability and Implementation: A user friendly code implemented in R language can be downloaded from http://www.niehs.nih.gov/research/atniehs/labs/bb/staff/peddada/index.cfm . Contact: peddada@niehs.nih.gov
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    Evaluating Policy Design Choices for the Margin Protection Program for Dairy Producers: An Expected Indemnity Approach (2016)
    Oxford University Press
    Details
    Publication Date: 2016-12-07
    Description: The Agricultural Act of 2014 replaced dairy product price supports and countercyclical income support payments with the Margin Protection Program for Dairy Producers. Using farm-level data, producer decisions and aggregate policy costs under a variety of risk environments and policy design alternatives are simulated. Fixed premium rates may result in budget outlays that are substantially higher than for equivalent variable-rate insurance subsidized at levels observed in revenue-based crop insurance policies. Due to the absence of adjusted gross income or production eligibility constraints, a significant portion of benefits may accrue to a small share of large dairy farms.
    Keywords: Q11 - Aggregate Supply and Demand Analysis ; Prices, 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
    Published by Oxford University Press
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  • 7
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    Localized structural frustration for evaluating the impact of sequence variants (2016)
    Oxford University Press
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    Publication Date: 2016-12-04
    Description: Population-scale sequencing is increasingly uncovering large numbers of rare single-nucleotide variants (SNVs) in coding regions of the genome. The rarity of these variants makes it challenging to evaluate their deleteriousness with conventional phenotype–genotype associations. Protein structures provide a way of addressing this challenge. Previous efforts have focused on globally quantifying the impact of SNVs on protein stability. However, local perturbations may severely impact protein functionality without strongly disrupting global stability (e.g. in relation to catalysis or allostery). Here, we describe a workflow in which localized frustration, quantifying unfavorable local interactions, is employed as a metric to investigate such effects. Using this workflow on the Protein Databank, we find that frustration produces many immediately intuitive results: for instance, disease-related SNVs create stronger changes in localized frustration than non-disease related variants, and rare SNVs tend to disrupt local interactions to a larger extent than common variants. Less obviously, we observe that somatic SNVs associated with oncogenes and tumor suppressor genes (TSGs) induce very different changes in frustration. In particular, those associated with TSGs change the frustration more in the core than the surface (by introducing loss-of-function events), whereas those associated with oncogenes manifest the opposite pattern, creating gain-of-function events.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 8
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    Function-driven discovery of disease genes in zebrafish using an integrated genomics big data resource (2016)
    Oxford University Press
    Details
    Publication Date: 2016-12-01
    Description: Whole exome sequencing (WES) accelerates disease gene discovery using rare genetic variants, but further statistical and functional evidence is required to avoid false-discovery. To complement variant-driven disease gene discovery, here we present function-driven disease gene discovery in zebrafish ( Danio rerio ), a promising human disease model owing to its high anatomical and genomic similarity to humans. To facilitate zebrafish-based function-driven disease gene discovery, we developed a genome-scale co-functional network of zebrafish genes, DanioNet ( www.inetbio.org/danionet ), which was constructed by Bayesian integration of genomics big data. Rigorous statistical assessment confirmed the high prediction capacity of DanioNet for a wide variety of human diseases. To demonstrate the feasibility of the function-driven disease gene discovery using DanioNet, we predicted genes for ciliopathies and performed experimental validation for eight candidate genes. We also validated the existence of heterozygous rare variants in the candidate genes of individuals with ciliopathies yet not in controls derived from the UK10K consortium, suggesting that these variants are potentially involved in enhancing the risk of ciliopathies. These results showed that an integrated genomics big data for a model animal of diseases can expand our opportunity for harnessing WES data in disease gene discovery.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 9
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    A novel method for the identification of conserved structural patterns in RNA: From small scale to high-throughput applications (2016)
    Oxford University Press
    Details
    Publication Date: 2016-10-14
    Description: Functional RNA regions are often related to recurrent secondary structure patterns (or motifs), which can exert their role in several different ways, particularly in dictating the interaction with RNA-binding proteins, and acting in the regulation of a large number of cellular processes. Among the available motif-finding tools, the majority focuses on sequence patterns, sometimes including secondary structure as additional constraints to improve their performance. Nonetheless, secondary structures motifs may be concurrent to their sequence counterparts or even encode a stronger functional signal. Current methods for searching structural motifs generally require long pipelines and/or high computational efforts or previously aligned sequences. Here, we present BEAM (BEAr Motif finder), a novel method for structural motif discovery from a set of unaligned RNAs, taking advantage of a recently developed encoding for RNA secondary structure named BEAR (Brand nEw Alphabet for RNAs) and of evolutionary substitution rates of secondary structure elements. Tested in a varied set of scenarios, from small- to large-scale, BEAM is successful in retrieving structural motifs even in highly noisy data sets, such as those that can arise in CLIP-Seq or other high-throughput experiments.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 10
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    Cuba's Agricultural Transition and Food Security in a Global Perspective (2016)
    Oxford University Press
    Details
    Publication Date: 2016-08-20
    Description: This paper reviews the situation in the agricultural sector and food security in Cuba, and particularly the transformations that have (not) taken place since 1990. We compare the Cuban transition with transitions in other "transition countries" and show that Cuba does not easily fit into one of the transition patterns, and, in a way, has characteristics of "a bit of everything". To conclude, we discuss the (potential) effects of the recent policy changes and the new economic reforms that were announced.
    Keywords: O13 - Agriculture ; Natural Resources ; Energy ; Environment ; Other Primary Products, P21 - Planning, Coordination, and Reform, Q13 - Agricultural Markets and Marketing ; Cooperatives ; Agribusiness, Q18 - Agricultural Policy ; Food Policy
    Print ISSN: 2040-5790
    Electronic ISSN: 2040-5804
    Topics: Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition , Economics
    Published by Oxford University Press
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