bluuebunny/crossref_metadata_2025_split huggingface dataset:
Food Insecurity in Vulnerable Populations: Coping with Food Price Shocks in Afghanistan
Authors: D'Souza Anna , Jolliffe Dean 
Published: December 2013

AbstractBased on data from Afghanistan collected prior to and during the 2007‐2008 food price crisis, this paper illustrates that caloric intake is an ineffectual indicator for monitoring the onset of food insecurity. Unconditional Quantile Regression estimates indicate that the most vulnerable of households, which cannot afford to make substantial cuts to calories, exhibit no decline in caloric intake in response to increasing wheat prices. In contrast, households with high‐calorie diets experience large declines. The estimates also reveal declines in dietary diversity across the entire distribution of households. The most vulnerable households may be sacrificing diet quality to maintain calories, with the potential for serious and long‐term health consequences.
ChAMP: 450k Chip Analysis Methylation Pipeline
Authors: Morris Tiffany J. , Butcher Lee M. , Feber Andrew , Teschendorff Andrew E. , Chakravarthy Ankur R. , Wojdacz Tomasz K. , Beck Stephan 
Published: December 2013

Abstract
The Illumina Infinium HumanMethylation450 BeadChip is a new platform for high-throughput DNA methylation analysis. Several methods for normalization and processing of these data have been published recently. Here we present an integrated analysis pipeline offering a choice of the most popular normalization methods while also introducing new methods for calling differentially methylated regions and detecting copy number aberrations.
Availability and implementation: ChAMP is implemented as a Bioconductor package in R. The package and the vignette can be downloaded at bioconductor.org
Contact: tiffany.morris@ucl.ac.uk
Genes related to differentiation are correlated with the gene regulatory network structure
Authors: Bodaker Matan , Meshorer Eran , Mitrani Eduardo , Louzoun Yoram 
Published: December 2013

AbstractMotivation: Many secondary messengers, receptors and transcription factors are related to cell differentiation. Their role in cell differentiation can be affected by their position in the gene regulatory network. Here, we test whether the properties of the gene regulatory network can highlight which genes and proteins are associated with cell differentiation. We use a previously developed purely theoretical algorithm built to detect nodes that can induce a state change in Boolean gene regulatory networks, and show that most genes predicted to participate in differentiation in the theoretical framework are also experimentally known to be associated with such differentiation. These results show that genes related to differentiation are associated with specific features of the genetic regulatory network. The proposed algorithm produces a better classification than simple network measures such as the nodes degree or centrality. Boolean networks were used in many previous theoretical models. Here, we show a direct application of such networks to the detection of genes and subnetworks related to differentiation. The subnetwork emerging from the genes and edges that are predicted to be associated with differentiation are the most active molecular pathways experimentally described to be involved in cell differentiation.Availability and implementation: http://peptibase.cs.biu.ac.il/homepage/Boolean_network_conversion_code.zip.Contact: louzouy@math.biu.ac.ilSupplementary information: Supplementary data are available at Bioinformatics online.
Causal analysis approaches in Ingenuity Pathway Analysis
Authors: Krämer Andreas , Green Jeff , Pollard Jack , Tugendreich Stuart 
Published: December 2013

Abstract
Motivation: Prior biological knowledge greatly facilitates the meaningful interpretation of gene-expression data. Causal networks constructed from individual relationships curated from the literature are particularly suited for this task, since they create mechanistic hypotheses that explain the expression changes observed in datasets.
Results: We present and discuss a suite of algorithms and tools for inferring and scoring regulator networks upstream of gene-expression data based on a large-scale causal network derived from the Ingenuity Knowledge Base. We extend the method to predict downstream effects on biological functions and diseases and demonstrate the validity of our approach by applying it to example datasets.
Availability: The causal analytics tools ‘Upstream Regulator Analysis', ‘Mechanistic Networks', ‘Causal Network Analysis' and ‘Downstream Effects Analysis' are implemented and available within Ingenuity Pathway Analysis (IPA, http://www.ingenuity.com).
Supplementary information: Supplementary material is available at Bioinformatics online.
HAMMER: automated operation of mass frontier to construct in silico mass spectral fragmentation libraries
Authors: Zhou Jiarui , Weber Ralf J. M. , Allwood J. William , Mistrik Robert , Zhu Zexuan , Ji Zhen , Chen Siping , Dunn Warwick B. , He Shan , Viant Mark R. 
Published: December 2013

Abstract
Summary: Experimental MSn mass spectral libraries currently do not adequately cover chemical space. This limits the robust annotation of metabolites in metabolomics studies of complex biological samples. In silico fragmentation libraries would improve the identification of compounds from experimental multistage fragmentation data when experimental reference data are unavailable. Here, we present a freely available software package to automatically control Mass Frontier software to construct in silico mass spectral libraries and to perform spectral matching. Based on two case studies, we have demonstrated that high-throughput automation of Mass Frontier allows researchers to generate in silico mass spectral libraries in an automated and high-throughput fashion with little or no human intervention required.
Availability and implementation: Documentation, examples, results and source code are available at http://www.biosciences-labs.bham.ac.uk/viant/hammer/.
Contact: m.viant@bham.ac.uk
Supplementary information: Supplementary data are available at Bioinformatics online.
Sequence-based Gaussian network model for protein dynamics
Authors: Zhang Hua , Kurgan Lukasz 
Published: December 2013

Abstract
Motivation: Gaussian network model (GNM) is widely adopted to analyze and understand protein dynamics, function and conformational changes. The existing GNM-based approaches require atomic coordinates of the corresponding protein and cannot be used when only the sequence is known.
Results: We report, first of its kind, GNM model that allows modeling using the sequence. Our linear regression-based, parameter-free, sequence-derived GNM (L-pfSeqGNM) uses contact maps predicted from the sequence and models local, in the sequence, contact neighborhoods with the linear regression. Empirical benchmarking shows relatively high correlations between the native and the predicted with L-pfSeqGNM B-factors and between the cross-correlations of residue fluctuations derived from the structure- and the sequence-based GNM models. Our results demonstrate that L-pfSeqGNM is an attractive platform to explore protein dynamics. In contrast to the highly used GNMs that require protein structures that number in thousands, our model can be used to study motions for the millions of the readily available sequences, which finds applications in modeling conformational changes, protein–protein interactions and protein functions.
Contact: zerozhua@126.com
Supplementary information: Supplementary data are available at Bioinformatics online.
BETASEQ: a powerful novel method to control type-I error inflation in partially sequenced data for rare variant association testing
Authors: Yan Song , Li Yun 
Published: December 2013

Abstract
Summary: Despite its great capability to detect rare variant associations, next-generation sequencing is still prohibitively expensive when applied to large samples. In case-control studies, it is thus appealing to sequence only a subset of cases to discover variants and genotype the identified variants in controls and the remaining cases under the reasonable assumption that causal variants are usually enriched among cases. However, this approach leads to inflated type-I error if analyzed naively for rare variant association. Several methods have been proposed in recent literature to control type-I error at the cost of either excluding some sequenced cases or correcting the genotypes of discovered rare variants. All of these approaches thus suffer from certain extent of information loss and thus are underpowered. We propose a novel method (BETASEQ), which corrects inflation of type-I error by supplementing pseudo-variants while keeps the original sequence and genotype data intact. Extensive simulations and real data analysis demonstrate that, in most practical situations, BETASEQ leads to higher testing powers than existing approaches with guaranteed (controlled or conservative) type-I error.
Availability and implementation: BETASEQ and associated R files, including documentation, examples, are available at http://www.unc.edu/∼yunmli/betaseq
Contact: songyan@unc.edu or yunli@med.unc.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
VIRAPOPS: a forward simulator dedicated to rapidly evolved viral populations
Authors: Petitjean Michel , Vanet Anne 
Published: December 2013

Abstract
Summary: Daily, mutability and recombination of RNA viruses result in the production of million variants. All these rapid genomic changes directly influence the functional sites of the protein, its 3D structure or its drug resistances. Therefore, it is important to simulate these drastic switches to determine their effects on virus populations. Many computer programs are able to simulate specific variations in DNA genomes, but are generally non-adapted to RNA viruses. They simulate site-specific selection pressures, but rarely pressures on covariant or on higher order correlated sites and no at all on synthetic lethal groups. That is why we felt it important to create VIRAPOPS, a forward simulator that models specific RNA virus functions. It was designed for computational biologists, biologists and virologists.
Availability and implementation: Free binaries are available through a software repository at http://petitjeanmichel.free.fr/itoweb.petitjean.freeware.html.
Contact: anne.vanet@univ-paris-diderot.fr
Timing variations in the secondary eclipse of NN Ser
Authors: Parsons S. G. , Marsh T. R. , Bours M. C. P. , Littlefair S. P. , Copperwheat C. M. , Dhillon V. S. , Breedt E. , Caceres C. , Schreiber M. R. 
Published: December 2013

Abstract
The eclipsing white dwarf plus main-sequence binary NN Serpentis provides one of the most convincing cases for the existence of circumbinary planets around evolved binaries. The exquisite timing precision provided by the deep eclipse of the white dwarf has revealed complex variations in the eclipse arrival times over the last few decades. These variations have been interpreted as the influence of two planets in orbit around the binary. Recent studies have proved that such a system is dynamically stable over the current lifetime of the binary. However, the existence of such planets is by no means proven and several alternative mechanisms have been proposed that could drive similar variations. One of these is apsidal precession, which causes the eclipse times of eccentric binaries to vary sinusoidally on many year time-scales. In this Letter, we present timing data for the secondary eclipse of NN Ser and show that they follow the same trend seen in the primary eclipse times, ruling out apsidal precession as a possible cause for the variations. This result leaves no alternatives to the planetary interpretation for the observed period variations, although we still do not consider their existence as proven. Our data limit the eccentricity of NN Ser to e &lt; 10−3. We also detect a 3.3 ± 1.0 s delay in the arrival times of the secondary eclipses relative to the best planetary model. This delay is consistent with the expected 2.84 ± 0.04 s Rømer delay of the binary, and is the first time this effect has been detected in a white dwarf plus M dwarf system.
Systematic discovery and characterization of regulatory motifs in ENCODE TF binding experiments
Authors: Kheradpour Pouya , Kellis Manolis 
Published: December 2013

AbstractRecent advances in technology have led to a dramatic increase in the number of available transcription factor ChIP-seq and ChIP-chip data sets. Understanding the motif content of these data sets is an important step in understanding the underlying mechanisms of regulation. Here we provide a systematic motif analysis for 427 human ChIP-seq data sets using motifs curated from the literature and also discovered de novo using five established motif discovery tools. We use a systematic pipeline for calculating motif enrichment in each data set, providing a principled way for choosing between motif variants found in the literature and for flagging potentially problematic data sets. Our analysis confirms the known specificity of 41 of the 56 analyzed factor groups and reveals motifs of potential cofactors. We also use cell type-specific binding to find factors active in specific conditions. The resource we provide is accessible both for browsing a small number of factors and for performing large-scale systematic analyses. We provide motif matrices, instances and enrichments in each of the ENCODE data sets. The motifs discovered here have been used in parallel studies to validate the specificity of antibodies, understand cooperativity between data sets and measure the variation of motif binding across individuals and species.
Glycogen synthase kinase 3 beta inhibits microRNA-183-96-182 cluster via the β-Catenin/TCF/LEF-1 pathway in gastric cancer cells
Authors: Tang Xiaoli , Zheng Dong , Hu Ping , Zeng Zongyue , Li Ming , Tucker Lynne , Monahan Renee , Resnick Murray B. , Liu Manran , Ramratnam Bharat 
Published: December 2013

Abstract
Glycogen synthase kinase 3 beta (GSK3β) is a critical protein kinase that phosphorylates numerous proteins in cells and thereby impacts multiple pathways including the β-Catenin/TCF/LEF-1 pathway. MicroRNAs (miRs) are a class of noncoding small RNAs of ∼22 nucleotides in length. Both GSK3β and miR play myriad roles in cell functions including stem cell development, apoptosis, embryogenesis and tumorigenesis. Here we show that GSK3β inhibits the expression of miR-96, miR-182 and miR-183 through the β-Catenin/TCF/LEF-1 pathway. Knockout of GSK3β in mouse embryonic fibroblast cells increases expression of miR-96, miR-182 and miR-183, coinciding with increases in the protein level and nuclear translocation of β-Catenin. In addition, overexpression of β-Catenin enhances the expression of miR-96, miR-182 and miR-183 in human gastric cancer AGS cells. GSK3β protein levels are decreased in human gastric cancer tissue compared with surrounding normal gastric tissue, coinciding with increases of β-Catenin protein, miR-96, miR-182, miR-183 and primary miR-183-96-182 cluster (pri-miR-183). Furthermore, suppression of miR-183-96-182 cluster with miRCURY LNA miR inhibitors decreases the proliferation and migration of AGS cells. Knockdown of GSK3β with siRNA increases the proliferation of AGS cells. Mechanistically, we show that β-Catenin/TCF/LEF-1 binds to the promoter of miR-183-96-182 cluster gene and thereby activates the transcription of the cluster. In summary, our findings identify a novel role for GSK3β in the regulation of miR-183-96-182 biogenesis through β-Catenin/TCF/LEF-1 pathway in gastric cancer cells.
Identification of novel methyltransferases, Bmt5 and Bmt6, responsible for the m3U methylations of 25S rRNA in Saccharomyces cerevisiae
Authors: Sharma Sunny , Yang Jun , Düttmann Simon , Watzinger Peter , Kötter Peter , Entian Karl-Dieter 
Published: December 2013

Abstract
RNA contains various chemical modifications that expand its otherwise limited repertoire to mediate complex processes like translation and gene regulation. 25S rRNA of the large subunit of ribosome contains eight base methylations. Except for the methylation of uridine residues, methyltransferases for all other known base methylations have been recently identified. Here we report the identification of BMT5 (YIL096C) and BMT6 (YLR063W), two previously uncharacterized genes, to be responsible for m3U2634 and m3U2843 methylation of the 25S rRNA, respectively. These genes were identified by RP-HPLC screening of all deletion mutants of putative RNA methyltransferases and were confirmed by gene complementation and phenotypic characterization. Both proteins belong to Rossmann-fold–like methyltransferases and the point mutations in the S-adenosyl-l-methionine binding pocket abolish the methylation reaction. Bmt5 localizes in the nucleolus, whereas Bmt6 is localized predominantly in the cytoplasm. Furthermore, we showed that 25S rRNA of yeast does not contain any m5U residues as previously predicted. With Bmt5 and Bmt6, all base methyltransferases of the 25S rRNA have been identified. This will facilitate the analyses of the significance of these modifications in ribosome function and cellular physiology.
A Tale of Two Hypotheses: Genetics and the Ethnogenesis of Ashkenazi Jewry
Authors: Aram Yardumian M.A. 
Published: December 2013

AbstractThe debate over the ethnogenesis of Ashkenazi Jewry is longstanding, and has been hampered by a lack of Jewish historiographical work between the Biblical and the early Modern eras. Most historians, as well as geneticists, situate them as the descendants of Israelite tribes whose presence in Europe is owed to deportations during the Roman conquest of Palestine, as well as migration from Babylonia, and eventual settlement along the Rhine. By contrast, a few historians and other writers, most famously Arthur Koestler, have looked to migrations following the decline of the little-understood Medieval Jewish kingdom of Khazaria as the main source for Ashkenazi Jewry. A recent study of genetic variation in southeastern European populations (Elhaik 2012) also proposed a Khazarian origin for Ashkenazi Jews, eliciting considerable criticism from other scholars investigating Jewish ancestry who favor a Near Eastern origin of Ashkenazi populations. This paper re-examines the genetic data and analytical approaches used in these studies of Jewish ancestry, and situates them in the context of historical, linguistic, and archaeological evidence from the Caucasus, Europe and the Near East. Based on this reanalysis, it appears not only that the Khazar Hypothesis per se is without serious merit, but also the veracity of the ‘Rhineland Hypothesis’ may also be questionable.
Parametric inference in the large data limit using maximally informative models
Authors: Kinney Justin B. , Atwal Gurinder S. 
Published: December 2013

AbstractMotivated by data-rich experiments in transcriptional regulation and sensory neuro-science, we consider the following general problem in statistical inference. When exposed to a high-dimensional signalS, a system of interest computes a representationRof that signal which is then observed through a noisy measurementM. From a large number of signals and measurements, we wish to infer the “filter” that mapsStoR. However, the standard method for solving such problems, likelihood-based inference, requires perfecta prioriknowledge of the “noise function” mappingRtoM. In practice such noise functions are usually known only approximately, if at all, and using an incorrect noise function will typically bias the inferred filter. Here we show that, in the large data limit, this need for a pre-characterized noise function can be circumvented by searching for filters that instead maximize the mutual informationI[M;R] between observed measurements and predicted representations. Moreover, if the correct filter lies within the space of filters being explored, maximizing mutual information becomes equivalent to simultaneously maximizing every dependence measure that satisfies the Data Processing Inequality. It is important to note that maximizing mutual information will typically leave a small number of directions in parameter space unconstrained. We term these directions “diffeomorphic modes” and present an equation that allows these modes to be derived systematically. The presence of diffeomorphic modes reflects a fundamental and nontrivial substructure within parameter space, one that is obscured by standard likelihood-based inference.
Cold-Induced Cysts of the Photosynthetic DinoflagellateLingulodinium polyedrumHave an Arrested Circadian Bioluminescence Rhythm and Lower Levels of Protein Phosphorylation
Authors: Roy Sougata , Letourneau Louis , Morse David 
Published: December 2013

AbstractDinoflagellates are microscopic, eukaryotic, and primarily marine plankton. Temporary cyst formation is a well-known physiological response of dinoflagellate cells to environmental stresses. However, the molecular underpinnings of cold-induced cyst physiology have never been described. Cultures of the photosynthetic dinoflagellate Lingulodinium polyedrum readily form temporary cysts when placed at low (8°C ± 1°C) temperature and excyst to form normal motile cells following a return to normal temperature (18°C ± 1°C). The normal circadian bioluminescence rhythm and the expected changes in Luciferin Binding Protein abundance were arrested in L. polyedrum cysts. Furthermore, after excystment, the bioluminescence rhythm initiates at a time corresponding to zeitgeber 12, independent of the time when the cells encysted. Phosphoprotein staining after two-dimensional polyacrylamide gel electrophoresis, as well as column-based phosphoprotein enrichment followed by liquid chromatography tandem mass spectrometry, showed cyst proteins are hypophosphorylated when compared with those from motile cells, with the most marked decreases found for predicted Casein Kinase2 target sites. In contrast to the phosphoproteome, the cyst proteome is not markedly different from motile cells, as assessed by two-dimensional polyacrylamide gel electrophoresis. In addition to changes in the phosphoproteome, RNA sequencing revealed that cysts show a significant decrease in the levels of 132 RNAs. Of the 42 RNAs that were identified by sequence analysis, 21 correspond to plastid-encoded gene products and 11 to nuclear-encoded cell wall/plasma membrane components. Our data are consistent with a model in which the highly reduced metabolism in cysts is achieved primarily by alterations in the phosphoproteome. The stalling of the circadian rhythm suggests temporary cysts may provide an interesting model to address the circadian system of dinoflagellates.