INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77425, 2013, 'bio', 'APoc: large-scale identification of similar protein pockets', 'Gao, Mu|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA 30076, USA.', 'Georgia|Georgia', 67, 'Algorithms|Bacteria|Bacterial Proteins|Binding Sites|GTP Phosphohydrolases|Ligands|Models, Molecular|Models, Statistical|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt024', '23335017', 'Most proteins interact with small-molecule ligands such as metabolites or drug compounds. Over the past several decades, many of these interactions have been captured in high-resolution atomic structures. From a geometric point of view, most interaction sites for grasping these small-molecule ligands, as revealed in these structures, form concave shapes, or pockets, on the proteins surface. An efficient method for comparing these pockets could greatly assist the classification of ligand-binding sites, prediction of protein molecular function and design of novel drug compounds.'),
(77426, 2013, 'bio', 'Improving the reuse of computational models through version control', 'Waltemath, Dagmar|Henkel, Ron|Hälke, Robert|Scharm, Martin|Wolkenhauer, Olaf', 'Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany. dagmar.waltemath@uni-rostock.de|Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany. dagmar.waltemath@uni-rostock.de|Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany. dagmar.waltemath@uni-rostock.de|Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany. dagmar.waltemath@uni-rostock.de|Department of Systems Biology and Bioinformatics, University of Rostock, 18051 Rostock, Germany. dagmar.waltemath@uni-rostock.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt018', '23335018', 'Only models that are accessible to researchers can be reused. As computational models evolve over time, a number of different but related versions of a model exist. Consequently, tools are required to manage not only well-curated models but also their associated versions.'),
(77427, 2013, 'bio', 'Extracting 3D cell parameters from dense tissue environments: application to the development of the mouse heart', 'Pop, Sorin|Dufour, Alexandre C|Le Garrec, Jean-François|Ragni, Chiara V|Cimper, Clémire|Meilhac, Sigolène M|Olivo-Marin, Jean-Christophe', 'Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.|Quantitative Image Analysis Unit, Institut Pasteur, 75015 Paris, France.', 'France|France|France|France|France|France|France', 0, 'Animals|Cell Cycle|Cell Division|Cell Nucleus|Centrosome|Heart|Imaging, Three-Dimensional|Mice|Microscopy, Fluorescence|Myocardium', 'Journal Article', '10.1093/bioinformatics/btt027', '23337749', 'In developmental biology, quantitative tools to extract features from fluorescence microscopy images are becoming essential to characterize organ morphogenesis at the cellular level. However, automated image analysis in this context is a challenging task, owing to perturbations induced by the acquisition process, especially in organisms where the tissue is dense and opaque.'),
(77428, 2013, 'bio', 'TACTICS, an interactive platform for customized high-content bioimaging analysis', 'Shimoni, Raz|Pham, Kim|Yassin, Mohammed|Gu, Min|Russell, Sarah M', 'Immune Signalling Laboratory, Peter MacCallum Cancer Centre, East Melbourne 3002, Australia.|Immune Signalling Laboratory, Peter MacCallum Cancer Centre, East Melbourne 3002, Australia.|Immune Signalling Laboratory, Peter MacCallum Cancer Centre, East Melbourne 3002, Australia.|Immune Signalling Laboratory, Peter MacCallum Cancer Centre, East Melbourne 3002, Australia.|Immune Signalling Laboratory, Peter MacCallum Cancer Centre, East Melbourne 3002, Australia.', 'Australia|Australia|Australia|Australia|Australia', 0, 'Image Processing, Computer-Assisted|Software|Time-Lapse Imaging', 'Journal Article', '10.1093/bioinformatics/btt035', '23341500', 'We describe a modular MATLAB® Toolbox named TACTICS for time-lapse image analysis that meets several requirements not generally offered by currently available software packages: (i) the ability to assess quality of extracted imaging information by directly linking data end points to the original position, (ii) massively parallel analysis of each parameter, for flow cytometry-like assessment of possible relationships between parameters within sub-populations of the images, (iii) options for user control of the tracking such as an interface to restrict the analysis region, (iv) manual correction of automated processes and (v) user interfaces for post-tracking analysis that is linked to the original images, including options to view cell pedigrees and normalized polarization ratios based on fluorescence ratiometric measurements.'),
(77429, 2013, 'bio', 'Composition and abstraction of logical regulatory modules: application to multicellular systems', 'Mendes, Nuno D|Lang, Frédéric|Le Cornec, Yves-Stan|Mateescu, Radu|Batt, Gregory|Chaouiya, Claudine', 'IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.|IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.|IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.|IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.|IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.|IGC, Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, P-2780-156 Oeiras, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|Body Patterning|Cell Communication|Computational Biology|Intracellular Signaling Peptides and Proteins|Membrane Proteins|Models, Biological|Receptors, Notch|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btt033', '23341501', 'Logical (Boolean or multi-valued) modelling is widely used to study regulatory or signalling networks. Even though these discrete models constitute a coarse, yet useful, abstraction of reality, the analysis of large networks faces a classical combinatorial problem. Here, we propose to take advantage of the intrinsic modularity of inter-cellular networks to set up a compositional procedure that enables a significant reduction of the dynamics, yet preserving the reachability of stable states. To that end, we rely on process algebras, a well-established computational technique for the specification and verification of interacting systems.'),
(77430, 2013, 'bio', 'Genome Fusion Detection: a novel method to detect fusion genes from SNP-array data', 'Thieme, Sebastian|Groth, Philip', 'Department of Theoretical Biophysics, Humboldt-University of Berlin, 10115 Berlin, Germany and Therapeutic Research Group Oncology, Bayer Pharma AG, 13353 Berlin, Germany.|Department of Theoretical Biophysics, Humboldt-University of Berlin, 10115 Berlin, Germany and Therapeutic Research Group Oncology, Bayer Pharma AG, 13353 Berlin, Germany.', 'Germany|Germany', 5, 'Algorithms|Cell Line, Tumor|Chromosome Breakpoints|DNA Copy Number Variations|Fusion Proteins, bcr-abl|Gene Fusion|Genome|Humans|Male|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Prostatic Neoplasms', 'Journal Article', '10.1093/bioinformatics/btt028', '23341502', 'Fusion genes result from genomic rearrangements, such as deletions, amplifications and translocations. Such rearrangements can also frequently be observed in cancer and have been postulated as driving event in cancer development. to detect them, one needs to analyze the transition region of two segments with different copy number, the location where fusions are known to occur. Finding fusion genes is essential to understanding cancer development and may lead to new therapeutic approaches.'),
(77431, 2013, 'bio', 'Computational phosphorylation site prediction in plants using random forests and organism-specific instance weights', 'Trost, Brett|Kusalik, Anthony', 'Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca', 'Canada|Canada', 37, 'Animals|Artificial Intelligence|Cattle|Computational Biology|Humans|Mice|Phosphorylation|Plant Proteins|Protein Processing, Post-Translational|Sequence Alignment|Sequence Analysis, Protein|Software|Soybeans', 'Journal Article', '10.1093/bioinformatics/btt031', '23341503', 'Phosphorylation is the most important post-translational modification in eukaryotes. Although many computational phosphorylation site prediction tools exist for mammals, and a few were created specifically for Arabidopsis thaliana, none are currently available for other plants.'),
(77432, 2013, 'bio', 'SwarmDock: a server for flexible protein-protein docking', 'Torchala, Mieczyslaw|Moal, Iain H|Chaleil, Raphael A G|Fernandez-Recio, Juan|Bates, Paul A', 'Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.|Biomolecular Modelling Laboratory, Cancer Research UK London Research Institute, London WC2A 3LY, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Cluster Analysis|Internet|Molecular Docking Simulation|Multiprotein Complexes|Protein Conformation|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt038', '23343604', 'Protein-protein interactions are central to almost all biological functions, and the atomic details of such interactions can yield insights into the mechanisms that underlie these functions. We present a web server that wraps and extends the SwarmDock flexible protein-protein docking algorithm. After uploading PDB files of the binding partners, the server generates low energy conformations and returns a ranked list of clustered docking poses and their corresponding structures. The user can perform full global docking, or focus on particular residues that are implicated in binding. The server is validated in the CAPRI blind docking experiment, against the most current docking benchmark, and against the ClusPro docking server, the highest performing server currently available.'),
(77433, 2013, 'bio', 'Graphlet-based measures are suitable for biological network comparison', 'Hayes, Wayne|Sun, Kai|Pržulj, Nataša', 'Department of Computer Science, University of California, Irvine, CA 92697-3435, USA.|Department of Computer Science, University of California, Irvine, CA 92697-3435, USA.|Department of Computer Science, University of California, Irvine, CA 92697-3435, USA.', 'United States|United States|United States', 50, 'Models, Biological|Protein Interaction Mapping|Protein Interaction Maps|Statistics, Nonparametric|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/bts729', '23349212', 'Large amounts of biological network data exist for many species. Analogous to sequence comparison, network comparison aims to provide biological insight. Graphlet-based methods are proving to be useful in this respect. Recently some doubt has arisen concerning the applicability of graphlet-based measures to low edge density networks-in particular that the methods are unstable-and further that no existing network model matches the structure found in real biological networks.'),
(77434, 2013, 'bio', 'essaMEM: finding maximal exact matches using enhanced sparse suffix arrays', 'Vyverman, Michaël|De Baets, Bernard|Fack, Veerle|Dawyndt, Peter', 'Department of Applied Mathematics and Computer Science and Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent B-9000, Belgium. Michael.Vyverman@UGent.be|Department of Applied Mathematics and Computer Science and Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent B-9000, Belgium. Michael.Vyverman@UGent.be|Department of Applied Mathematics and Computer Science and Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent B-9000, Belgium. Michael.Vyverman@UGent.be|Department of Applied Mathematics and Computer Science and Department of Mathematical Modelling, Statistics and Bioinformatics, Ghent University, Ghent B-9000, Belgium. Michael.Vyverman@UGent.be', 'Belgium|Belgium|Belgium|Belgium', 26, 'Algorithms|Animals|Drosophila|Genome|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btt042', '23349213', 'We have developed essaMEM, a tool for finding maximal exact matches that can be used in genome comparison and read mapping. essaMEM enhances an existing sparse suffix array implementation with a sparse child array. Tests indicate that the enhanced algorithm for finding maximal exact matches is much faster, while maintaining the same memory footprint. In this way, sparse suffix arrays remain competitive with the more complex compressed suffix arrays.'),
(77435, 2013, 'bio', 'Bellmans GAP--a language and compiler for dynamic programming in sequence analysis', 'Sauthoff, Georg|Möhl, Mathias|Janssen, Stefan|Giegerich, Robert', 'Center of Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany.|Center of Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany.|Center of Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany.|Center of Biotechnology and Faculty of Technology, Bielefeld University, 33615 Bielefeld, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Programming Languages|RNA Folding|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btt022', '23355290', 'Dynamic programming is ubiquitous in bioinformatics. Developing and implementing non-trivial dynamic programming algorithms is often error prone and tedious. Bellmans GAP is a new programming system, designed to ease the development of bioinformatics tools based on the dynamic programming technique.'),
(77436, 2013, 'bio', 'mRNAStab--a web application for mRNA stability analysis', 'Alic, Andrei|Pérez-Ortín, José E|Moreno, Joaquín|Arnau, Vicente', 'Department of Informatics and Department of Biochemistry and Molecular Biology, Universitat de València, 46100 Burjassot, Spain.|Department of Informatics and Department of Biochemistry and Molecular Biology, Universitat de València, 46100 Burjassot, Spain.|Department of Informatics and Department of Biochemistry and Molecular Biology, Universitat de València, 46100 Burjassot, Spain.|Department of Informatics and Department of Biochemistry and Molecular Biology, Universitat de València, 46100 Burjassot, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Genomics|Humans|Internet|RNA Stability|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btt040', '23355291', 'Eukaryotic gene expression is regulated both at the transcription and the mRNA degradation levels. The implementation of functional genomics methods that allow the simultaneous measurement of transcription (TR) and degradation (DR) rates for thousands of mRNAs is a huge improvement in this field. One of the best established methods for mRNA stability determination is genomic run-on (GRO). It allows the measurement of DR, TR and mRNA levels during cell dynamic responses. Here, we offer a software package that provides improved algorithms for determination of mRNA stability during dynamic GRO experiments.'),
(77437, 2013, 'bio', 'MetaNetXorg: a website and repository for accessing, analysing and manipulating metabolic networks', 'Ganter, Mathias|Bernard, Thomas|Moretti, Sébastien|Stelling, Joerg|Pagni, Marco', 'Department of Biosystems Science and Engineering, SIB Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, SIB Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, SIB Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, SIB Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.|Department of Biosystems Science and Engineering, SIB Swiss Institute of Bioinformatics, ETH Zurich, 4058 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Genomics|Humans|Internet|Metabolic Networks and Pathways|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btt036', '23357920', 'MetaNetX.org is a website for accessing, analysing and manipulating genome-scale metabolic networks (GSMs) as well as biochemical pathways. It consistently integrates data from various public resources and makes the data accessible in a standardized format using a common namespace. Currently, it provides access to hundreds of GSMs and pathways that can be interactively compared (two or more), analysed (e.g. detection of dead-end metabolites and reactions, flux balance analysis or simulation of reaction and gene knockouts), manipulated and exported. Users can also upload their own metabolic models, choose to automatically map them into the common namespace and subsequently make use of the websites functionality.'),
(77438, 2013, 'bio', 'AbCD: arbitrary coverage design for sequencing-based genetic studies', 'Kang, Jian|Huang, Kuan-Chieh|Xu, Zheng|Wang, Yunfei|Abecasis, Gonçalo R|Li, Yun', 'Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.|Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.|Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.|Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.|Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.|Faculty of Kinesiology, University of Calgary, Calgary, AB T2N1N4, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 8, 'Gene Frequency|Genomics|Genotyping Techniques|High-Throughput Nucleotide Sequencing|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt041', '23357921', 'Recent advances in sequencing technologies have revolutionized genetic studies. Although high-coverage sequencing can uncover most variants present in the sequenced sample, low-coverage sequencing is appealing for its cost effectiveness. Here, we present AbCD (arbitrary coverage design) to aid the design of sequencing-based studies. AbCD is a user-friendly interface providing pre-estimated effective sample sizes, specific to each minor allele frequency category, for designs with arbitrary coverage (0.5-30×) and sample size (20-10 000), and for four major ethnic groups (Europeans, Africans, Asians and African Americans). In addition, we also present two software tools: ShotGun and DesignPlanner, which were used to generate the estimates behind AbCD. ShotGun is a flexible short-read simulator for arbitrary user-specified read length and average depth, allowing cycle-specific sequencing error rates and realistic read depth distributions. DesignPlanner is a full pipeline that uses ShotGun to generate sequence data and performs initial SNP discovery, uses our previously presented linkage disequilibrium-aware method to call genotypes, and, finally, provides minor allele frequency-specific effective sample sizes. ShotGun plus DesignPlanner can accommodate effective sample size estimate for any combination of high-depth and low-depth data (for example, whole-genome low-depth plus exonic high-depth) or combination of sequence and genotype data [for example, whole-exome sequencing plus genotyping from existing Genomewide Association Study (GWAS)].'),
(77439, 2013, 'bio', 'ScalaBLAST 20: rapid and robust BLAST calculations on multiprocessor systems', 'Oehmen, Christopher S|Baxter, Douglas J', 'Pacific Northwest National Laboratory, Richland, WA 99352, USA. christopher.oehmen@pnl.gov|Pacific Northwest National Laboratory, Richland, WA 99352, USA. christopher.oehmen@pnl.gov', 'United States|United States', 26, 'Algorithms|Computational Biology|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btt013', '23361326', 'BLAST remains one of the most widely used tools in computational biology. The rate at which new sequence data is available continues to grow exponentially, driving the emergence of new fields of biological research. At the same time, multicore systems and conventional clusters are more accessible. ScalaBLAST has been designed to run on conventional multiprocessor systems with an eye to extreme parallelism, enabling parallel BLAST calculations using >16 000 processing cores with a portable, robust, fault-resilient design that introduces little to no overhead with respect to serial BLAST.'),
(77440, 2013, 'bio', 'The majority of endogenous microRNA targets within Alu elements avoid the microRNA machinery', 'Hoffman, Yonit|Dahary, Dvir|Bublik, Debora Rosa|Oren, Moshe|Pilpel, Yitzhak', 'Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot 76100, Israel.', 'Israel|Israel|Israel|Israel|Israel', 0, '3 Untranslated Regions|Alu Elements|Animals|Binding Sites|Gene Expression Regulation|Genome, Human|Humans|Mice|MicroRNAs|Nucleic Acid Conformation|RNA Editing|RNA, Messenger|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt044', '23361327', 'The massive spread of repetitive elements in the human genome presents a substantial challenge to the organism, as such elements may accidentally contain seemingly functional motifs. A striking example is offered by the roughly one million copies of Alu repeats in the genome, of which xe2x88xbc0.5% reside within genes untranslated regions (UTRs), presenting xe2x88xbc30 000 novel potential targets for highly conserved microRNAs (miRNAs). Here, we examine the functionality of miRNA targets within Alu elements in 3UTRs in the human genome.'),
(77441, 2013, 'bio', 'Bayesian analysis of gene essentiality based on sequencing of transposon insertion libraries', 'DeJesus, Michael A|Zhang, Yanjia J|Sassetti, Christopher M|Rubin, Eric J|Sacchettini, James C|Ioerger, Thomas R', 'Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843, USA. michael.dejesus@tamu.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|DNA Transposable Elements|Gene Library|Genes, Bacterial|Genes, Essential|Genomics|High-Throughput Nucleotide Sequencing|Models, Statistical|Mutagenesis, Insertional|Mycobacterium tuberculosis|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btt043', '23361328', 'Next-generation sequencing affords an efficient analysis of transposon insertion libraries, which can be used to identify essential genes in bacteria. To analyse this high-resolution data, we present a formal Bayesian framework for estimating the posterior probability of essentiality for each gene, using the extreme-value distribution to characterize the statistical significance of the longest region lacking insertions within a gene. We describe a sampling procedure based on the Metropolis-Hastings algorithm to calculate posterior probabilities of essentiality while simultaneously integrating over unknown internal parameters.'),
(77442, 2013, 'bio', 'BioGranat-IG: a network analysis tool to suggest mechanisms of genetic heterogeneity from exome-sequencing data', 'Dand, Nick|Sprengel, Frauke|Ahlers, Volker|Schlitt, Thomas', 'Department of Medical and Molecular Genetics, Kings College London, London SE1 9RT, UK.|Department of Medical and Molecular Genetics, Kings College London, London SE1 9RT, UK.|Department of Medical and Molecular Genetics, Kings College London, London SE1 9RT, UK.|Department of Medical and Molecular Genetics, Kings College London, London SE1 9RT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 5, 'Disease|Exome|Genes|Genetic Heterogeneity|Hidradenitis Suppurativa|Humans|Pseudohypoaldosteronism|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt045', '23361329', 'Recent exome-sequencing studies have successfully identified disease-causing sequence variants for several rare monogenic diseases by examining variants common to a group of patients. However, the current data analysis strategies are only insufficiently able to deal with confounding factors such as genetic heterogeneity, incomplete penetrance, individuals lacking data and involvement of several genes.'),
(77443, 2013, 'bio', 'Inferring microRNA-mRNA causal regulatory relationships from expression data', 'Le, Thuc Duy|Liu, Lin|Tsykin, Anna|Goodall, Gregory J|Liu, Bing|Sun, Bing-Yu|Li, Jiuyong', 'School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au|School of Information Technology and Mathematical Sciences, University of South Australia, Mawson Lakes, South Australia 5095. thuc_duy.le@mymail.unisa.edu.au', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Animals|Cell Line, Tumor|Epithelial-Mesenchymal Transition|Gene Expression Profiling|Gene Expression Regulation|MicroRNAs|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/btt048', '23365408', 'microRNAs (miRNAs) are known to play an essential role in the post-transcriptional gene regulation in plants and animals. Currently, several computational approaches have been developed with a shared aim to elucidate miRNA-mRNA regulatory relationships. Although these existing computational methods discover the statistical relationships, such as correlations and associations between miRNAs and mRNAs at data level, such statistical relationships are not necessarily the real causal regulatory relationships that would ultimately provide useful insights into the causes of gene regulations. The standard method for determining causal relationships is randomized controlled perturbation experiments. In practice, however, such experiments are expensive and time consuming. Our motivation for this study is to discover the miRNA-mRNA causal regulatory relationships from observational data.'),
(77444, 2013, 'bio', 'Bayesian parentage analysis with systematic accountability of genotyping error, missing data and false matching', 'Christie, Mark R|Tennessen, Jacob A|Blouin, Michael S', 'Department of Zoology, Oregon State University, Corvallis, OR 97331-2914, USA. christim@science.oregonstate.edu|Department of Zoology, Oregon State University, Corvallis, OR 97331-2914, USA. christim@science.oregonstate.edu|Department of Zoology, Oregon State University, Corvallis, OR 97331-2914, USA. christim@science.oregonstate.edu', 'United States|United States|United States', 0, 'Animals|Bayes Theorem|Gene Frequency|Genotype|Genotyping Techniques|Likelihood Functions|Microsatellite Repeats|Polymorphism, Single Nucleotide|Salmon', 'Journal Article', '10.1093/bioinformatics/btt039', '23365409', 'The goal of any parentage analysis is to identify as many parent-offspring relationships as possible, while minimizing incorrect assignments. Existing methods can achieve these ends, but they require additional information in the form of demographic data, thousands of markers and/or estimates of genotyping error rates. For many non-model systems, it is simply not practical, cost-effective or logistically feasible to obtain this information. Here, we develop a Bayesian parentage method that only requires the sampled genotypes to account for genotyping error, missing data and false matches.'),
(77445, 2013, 'bio', 'MosaicFinder: identification of fused gene families in sequence similarity networks', 'Jachiet, Pierre-Alain|Pogorelcnik, Romain|Berry, Anne|Lopez, Philippe|Bapteste, Eric', 'UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, 75005 Paris, France.|UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, 75005 Paris, France.|UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, 75005 Paris, France.|UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, 75005 Paris, France.|UMR CNRS 7138 Systématique, Adaptation, Evolution, Université Pierre et Marie Curie, 75005 Paris, France.', 'France|France|France|France|France', 22, 'Algorithms|Gene Fusion|Multigene Family|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btt049', '23365410', 'Gene fusion is an important evolutionary process. It can yield valuable information to infer the interactions and functions of proteins. Fused genes have been identified as non-transitive patterns of similarity in triplets of genes. To be computationally tractable, this approach usually imposes an a priori distinction between a dataset in which fused genes are searched for, and a dataset that may have provided genetic material for fusion. This reduces the genetic space in which fusion can be discovered, as only a subset of triplets of genes is investigated. Moreover, this approach may have a high-false-positive rate, and it does not identify gene families descending from a common fusion event.'),
(77446, 2013, 'bio', 'MSMExplorer: visualizing Markov state models for biomolecule folding simulations', 'Cronkite-Ratcliff, Bryce|Pande, Vijay', 'Department of Computer Science, Stanford University, Stanford, CA 94305, USA.|Department of Computer Science, Stanford University, Stanford, CA 94305, USA.', 'United States|United States', 0, 'Computer Graphics|Computer Simulation|Markov Chains|Molecular Conformation|Software', 'Journal Article', '10.1093/bioinformatics/btt051', '23365411', 'Markov state models (MSMs) for the study of biomolecule folding simulations have emerged as a powerful tool for computational study of folding dynamics. MSMExplorer is a visualization application purpose-built to visualize these MSMs with an aim to increase the efficacy and reach of MSM science.'),
(77447, 2013, 'bio', 'RepeatExplorer: a Galaxy-based web server for genome-wide characterization of eukaryotic repetitive elements from next-generation sequence reads', 'Novxc3xa1k, Petr|Neumann, Pavel|Pech, Jixc5x99xc3xad|Steinhaisl, Jaroslav|Macas, Jixc5x99xc3xad', 'Institute of Plant Molecular Biology, Biology Centre ASCR, Branixc5xa1ovskxc3xa1 31, xc4x8ceskxc3xa9 Budxc4x9bjovice, CZ-37005, Czech Republic.|Institute of Plant Molecular Biology, Biology Centre ASCR, Branixc5xa1ovskxc3xa1 31, xc4x8ceskxc3xa9 Budxc4x9bjovice, CZ-37005, Czech Republic.|Institute of Plant Molecular Biology, Biology Centre ASCR, Branixc5xa1ovskxc3xa1 31, xc4x8ceskxc3xa9 Budxc4x9bjovice, CZ-37005, Czech Republic.|Institute of Plant Molecular Biology, Biology Centre ASCR, Branixc5xa1ovskxc3xa1 31, xc4x8ceskxc3xa9 Budxc4x9bjovice, CZ-37005, Czech Republic.|Institute of Plant Molecular Biology, Biology Centre ASCR, Branixc5xa1ovskxc3xa1 31, xc4x8ceskxc3xa9 Budxc4x9bjovice, CZ-37005, Czech Republic.', '-|-|-|-|-', 0, 'Algorithms|Cluster Analysis|DNA|Eukaryota|Genome|High-Throughput Nucleotide Sequencing|Internet|Phylogeny|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt054', '23376349', 'Repetitive DNA makes up large portions of plant and animal nuclear genomes, yet it remains the least-characterized genome component in most species studied so far. Although the recent availability of high-throughput sequencing data provides necessary resources for in-depth investigation of genomic repeats, its utility is hampered by the lack of specialized bioinformatics tools and appropriate computational resources that would enable large-scale repeat analysis to be run by biologically oriented researchers.'),
(77448, 2013, 'bio', 'Filtering duplicate reads from 454 pyrosequencing data', 'Balzer, Susanne|Malde, Ketil|Grohme, Markus A|Jonassen, Inge', 'Norwegian Marine Data Centre, Institute of Marine Research, P.O. Box 1870, N-5817 Bergen, Norway.|Norwegian Marine Data Centre, Institute of Marine Research, P.O. Box 1870, N-5817 Bergen, Norway.|Norwegian Marine Data Centre, Institute of Marine Research, P.O. Box 1870, N-5817 Bergen, Norway.|Norwegian Marine Data Centre, Institute of Marine Research, P.O. Box 1870, N-5817 Bergen, Norway.', 'Norway|Norway|Norway|Norway', 14, 'Algorithms|Bayes Theorem|Chromosome Mapping|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt047', '23376350', 'Throughout the recent years, 454 pyrosequencing has emerged as an efficient alternative to traditional Sanger sequencing and is widely used in both de novo whole-genome sequencing and metagenomics. Especially the latter application is extremely sensitive to sequencing errors and artificially duplicated reads. Both are common in 454 pyrosequencing and can create a strong bias in the estimation of diversity and composition of a sample. To date, there are several tools that aim to remove both sequencing noise and duplicates. Nevertheless, duplicate removal is often based on nucleotide sequences rather than on the underlying flow values, which contain additional information.'),
(77449, 2013, 'bio', 'Comparative study of RNA-seq- and microarray-derived coexpression networks in Arabidopsis thaliana', 'Giorgi, Federico M|Del Fabbro, Cristian|Licausi, Francesco', 'Institute of Applied Genomics, Udine 33100, Italy. fgiorgi@appliedgenomics.org|Institute of Applied Genomics, Udine 33100, Italy. fgiorgi@appliedgenomics.org|Institute of Applied Genomics, Udine 33100, Italy. fgiorgi@appliedgenomics.org', 'Italy|Italy|Italy', 0, 'Arabidopsis|Gene Expression Profiling|Gene Expression Regulation, Plant|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/btt053', '23376351', 'Coexpression networks are data-derived representations of genes behaving in a similar way across tissues and experimental conditions. They have been used for hypothesis generation and guilt-by-association approaches for inferring functions of previously unknown genes. So far, the main platform for expression data has been DNA microarrays, however, the recent development of RNA-seq allows for higher accuracy and coverage of transcript populations. It is therefore important to assess the potential for biological investigation of coexpression networks derived from this novel technique in a condition-independent dataset.'),
(77450, 2013, 'bio', 'BION web server: predicting non-specifically bound surface ions', 'Petukh, Marharyta|Kimmet, Taylor|Alexov, Emil', 'Computational Biophysics and Bioinformatics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA.|Computational Biophysics and Bioinformatics, Department of Physics and Astronomy, Clemson University, Clemson, SC 29634, USA.', 'United States|United States|United States', 10, 'Algorithms|Binding Sites|Internet|Ions|Proteins|Software|Static Electricity', 'Journal Article', '10.1093/bioinformatics/btt032', '23380591', 'Ions are essential component of the cell and frequently are found bound to various macromolecules, in particular to proteins. A binding of an ion to a protein greatly affects proteins biophysical characteristics and needs to be taken into account in any modeling approach. However, ions bounded positions cannot be easily revealed experimentally, especially if they are loosely bound to macromolecular surface.'),
(77451, 2013, 'bio', 'ELECANS--an integrated model development environment for multiscale cancer systems biology', 'Chaudhary, Safee Ullah|Shin, Sung-Young|Lee, Daewon|Song, Je-Hoon|Cho, Kwang-Hyun', 'Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, 291 Daehak-ro, Yuseong-gu, Daejeon 305-701, Republic of Korea.', '-|-|-|-|-', 0, 'Computer Simulation|Humans|Models, Biological|Neoplasms|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt063', '23390137', 'Computational multiscale models help cancer biologists to study the spatiotemporal dynamics of complex biological systems and to reveal the underlying mechanism of emergent properties.'),
(77452, 2013, 'bio', 'Fast thermodynamically constrained flux variability analysis', 'Müller, Arne C|Bockmayr, Alexander', 'Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany. arne.mueller@fu-berlin.de|Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany. arne.mueller@fu-berlin.de', 'Germany|Germany', 28, 'Algorithms|Genome|Metabolic Networks and Pathways|Models, Biological|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btt059', '23390138', 'Flux variability analysis (FVA) is an important tool to further analyse the results obtained by flux balance analysis (FBA) on genome-scale metabolic networks. For many constraint-based models, FVA identifies unboundedness of the optimal flux space. This reveals that optimal flux solutions with net flux through internal biochemical loops are feasible, which violates the second law of thermodynamics. Such unbounded fluxes may be eliminated by extending FVA with thermodynamic constraints.'),
(77453, 2013, 'bio', 'Coalescent simulation in continuous space', 'Kelleher, Jerome|Barton, Nicholas H|Etheridge, Alison M', 'Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, West Mains Road, EH9 3JT, UK. jerome.kelleher@ed.ac.uk|Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, West Mains Road, EH9 3JT, UK. jerome.kelleher@ed.ac.uk|Institute of Evolutionary Biology, University of Edinburgh, Kings Buildings, West Mains Road, EH9 3JT, UK. jerome.kelleher@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Algorithms|Computer Simulation|Evolution, Molecular|Genes|Genetics, Population|Models, Genetic|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/btt067', '23391497', 'Coalescent simulation has become an indispensable tool in population genetics, and many complex evolutionary scenarios have been incorporated into the basic algorithm. Despite many years of intense interest in spatial structure, however, there are no available methods to simulate the ancestry of a sample of genes that occupy a spatial continuum. This is mainly due to the severe technical problems encountered by the classical model of isolation by distance. A recently introduced model solves these technical problems and provides a solid theoretical basis for the study of populations evolving in continuous space. We present a detailed algorithm to simulate the coalescent process in this model, and provide an efficient implementation of a generalized version of this algorithm as a freely available Python module.'),
(77454, 2013, 'bio', 'A new algorithm for context-based biomedical diagram similarity estimation', 'Xu, Songhua|Sheng, Jianqiang|Luo, Xiaonan', 'Information Systems Department, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA. songhua.xu@njit.edu|Information Systems Department, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA. songhua.xu@njit.edu|Information Systems Department, College of Computing Sciences, New Jersey Institute of Technology, University Heights, Newark, NJ 07102, USA. songhua.xu@njit.edu', 'Jersey|Jersey|Jersey', 0, 'Algorithms|Computer Graphics|Data Mining|Humans|Image Processing, Computer-Assisted|Information Storage and Retrieval', 'Journal Article', '10.1093/bioinformatics/btt030', '23391498', 'Diagrams embedded in the biomedical literature convey rich contents, which often concisely and intuitively highlight key thesis of a research article. Despite their vital importance and informative clues for biomedical literature navigation and retrieval, currently, we miss an effective computational method for automatically understanding and accessing these valuable resources.'),
(77455, 2013, 'bio', 'displayHTS: a R package for displaying data and results from high-throughput screening experiments', 'Zhang, Xiaohua Douglas|Zhang, Zhaozhi', 'Early Development Statistics, BARDS, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com|Early Development Statistics, BARDS, Merck Research Laboratories, West Point, PA 19486, USA. xiaohua_zhang@merck.com', 'United States|United States', 0, 'High-Throughput Screening Assays|Software', 'Journal Article', '10.1093/bioinformatics/btt060', '23396118', 'The R package displayHTS implements recently developed methods and figures for displaying data and hit selection results in high-throughput screening (HTS) experiments. It generates not only certain useful distinctive graphics such as the plate-well series plot, plate image and dual-flashlight plot but also other commonly used figures such as volcano plot and plate correlation plot. These figures are critical for visualizing the data and displaying important features of HTS data and hit selection results.'),
(77456, 2013, 'bio', 'aCSM: noise-free graph-based signatures to large-scale receptor-based ligand prediction', 'Pires, Douglas E V|de Melo-Minardi, Raquel C|da Silveira, Carlos H|Campos, Frederico F|Meira, Wagner', 'Department of Computer Science, Universidade Federal de Minas Gerais, Av. Antxc3xb4nio Carlos, 6627, Pampulha Belo Horizonte - MG, 31270-901, Brazil. dpires@dcc.ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Av. Antxc3xb4nio Carlos, 6627, Pampulha Belo Horizonte - MG, 31270-901, Brazil. dpires@dcc.ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Av. Antxc3xb4nio Carlos, 6627, Pampulha Belo Horizonte - MG, 31270-901, Brazil. dpires@dcc.ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Av. Antxc3xb4nio Carlos, 6627, Pampulha Belo Horizonte - MG, 31270-901, Brazil. dpires@dcc.ufmg.br|Department of Computer Science, Universidade Federal de Minas Gerais, Av. Antxc3xb4nio Carlos, 6627, Pampulha Belo Horizonte - MG, 31270-901, Brazil. dpires@dcc.ufmg.br', 'Brazil|Brazil|Brazil|Brazil|Brazil', 32, 'Algorithms|Binding Sites|Enzymes|Humans|Ligands|Models, Molecular|Molecular Conformation|Molecular Docking Simulation|Protein Binding|Protein Conformation|Proteins|Protozoan Proteins|Trypanosoma cruzi', 'Journal Article', '10.1093/bioinformatics/btt058', '23396119', 'Receptor-ligand interactions are a central phenomenon in most biological systems. They are characterized by molecular recognition, a complex process mainly driven by physicochemical and structural properties of both receptor and ligand. Understanding and predicting these interactions are major steps towards protein ligand prediction, target identification, lead discovery and drug design.'),
(77457, 2013, 'bio', 'Oxfold: kinetic folding of RNA using stochastic context-free grammars and evolutionary information', 'Anderson, James W J|Haas, Pierre A|Mathieson, Leigh-Anne|Volynkin, Vladimir|Lyngsø, Rune|Tataru, Paula|Hein, Jotun', 'Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk|Department of Statistics, Oxford University, 1 South Parks Road, Oxford OX1 3TG, UK. anderson@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Bayes Theorem|Evolution, Molecular|Kinetics|Models, Molecular|RNA|RNA Folding|Sequence Alignment|Sequence Analysis, RNA|Stochastic Processes|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btt050', '23396120', 'Many computational methods for RNA secondary structure prediction, and, in particular, for the prediction of a consensus structure of an alignment of RNA sequences, have been developed. Most methods, however, ignore biophysical factors, such as the kinetics of RNA folding, no current implementation considers both evolutionary information and folding kinetics, thus losing information that, when considered, might lead to better predictions.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77458, 2013, 'bio', 'RNA-eXpress annotates novel transcript features in RNA-seq data', 'Forster, Samuel C|Finkel, Alexander M|Gould, Jodee A|Hertzog, Paul J', 'Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia, 3168.|Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia, 3168.|Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia, 3168.|Centre for Innate Immunity and Infectious Diseases, Monash Institute of Medical Research, Monash University, Clayton, Victoria, Australia, 3168.', 'Australia|Australia|Australia|Australia', 14, 'Algorithms|Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Molecular Sequence Annotation|RNA Isoforms|RNA Splicing|RNA, Untranslated|Sequence Analysis, RNA|Software|Transcription Initiation Site|Untranslated Regions', 'Journal Article', '10.1093/bioinformatics/btt034', '23396121', 'Next-generation sequencing is rapidly becoming the approach of choice for transcriptional analysis experiments. Substantial advances have been achieved in computational approaches to support these technologies. These approaches typically rely on existing transcript annotations, introducing a bias towards known genes, require specific experimental design and computational resources, or focus only on identification of splice variants (ignoring other biologically relevant transcribed features contained within the data that may be important for downstream analysis). Biologically relevant transcribed features also include large and small non-coding RNA, new transcription start sites, alternative promoters, RNA editing and processing of coding transcripts. Also, many existing solutions lack accessible interfaces required for wide scale adoption. We present a user-friendly, rapid and computation-efficient feature annotation framework (RNA-eXpress) that enables identification of transcripts and other genomic and transcriptional features independently of current annotations. RNA-eXpress accepts mapped reads in the standard binary alignment (BAM) format and produces a study-specific feature annotation in GTF format, comparison statistics, sequence extraction and feature counts. The framework is designed to be easily accessible while allowing advanced users to integrate new feature-identification algorithms through simple class extension, thus facilitating expansion to novel feature types or identification of study-specific feature types.'),
(77459, 2013, 'bio', 'Phylogenomic clustering for selecting non-redundant genomes for comparative genomics', 'Moreno-Hagelsieb, Gabriel|Wang, Zilin|Walsh, Stephanie|ElSherbiny, Aisha', 'Department of Biology and Department of Mathematics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada. gmoreno@wlu.ca|Department of Biology and Department of Mathematics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada. gmoreno@wlu.ca|Department of Biology and Department of Mathematics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada. gmoreno@wlu.ca|Department of Biology and Department of Mathematics, Wilfrid Laurier University, Waterloo, ON N2L 3C5, Canada. gmoreno@wlu.ca', 'Canada|Canada|Canada|Canada', 23, 'Genome|Genomics|Internet|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btt064', '23396122', 'Analyses in comparative genomics often require non-redundant genome datasets. Eliminating redundancy is not as simple as keeping one strain for each named species because genomes might be redundant at a higher taxonomic level than that of species for some analyses, some strains with different species names can be as similar as most strains sharing a species name, whereas some strains sharing a species name can be so different that they should be put into different groups, and some genomes lack a species name.'),
(77460, 2013, 'bio', 'MODexplorer: an integrated tool for exploring protein sequence, structure and function relationships', 'Kosinski, Jan|Barbato, Alessandro|Tramontano, Anna', 'Department of Physics, Sapienza University, 00185 Rome, Italy.|Department of Physics, Sapienza University, 00185 Rome, Italy.|Department of Physics, Sapienza University, 00185 Rome, Italy.', 'Italy|Italy|Italy', 12, 'Amino Acid Sequence|Binding Sites|Conserved Sequence|Internet|Ligands|Models, Molecular|Molecular Sequence Annotation|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structural Homology, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btt062', '23396123', 'MODexplorer is an integrated tool aimed at exploring the sequence, structural and functional diversity in protein families useful in homology modeling and in analyzing protein families in general. It takes as input either the sequence or the structure of a protein and provides alignments with its homologs along with a variety of structural and functional annotations through an interactive interface. The annotations include sequence conservation, similarity scores, ligand-, DNA- and RNA-binding sites, secondary structure, disorder, crystallographic structure resolution and quality scores of models implied by the alignments to the homologs of known structure. MODexplorer can be used to analyze sequence and structural conservation among the structures of similar proteins, to find structures of homologs solved in different conformational state or with different ligands and to transfer functional annotations. Furthermore, if the structure of the query is not known, MODexplorer can be used to select the modeling templates taking all this information into account and to build a comparative model.'),
(77461, 2013, 'bio', 'Quantifying spatial relationships from whole retinal images', 'Ruttenberg, Brian E|Luna, Gabriel|Lewis, Geoffrey P|Fisher, Steven K|Singh, Ambuj K', 'Department of Computer Science, University of California, Santa Barbara, CA 93106, USA. bruttenberg@cra.com|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA. bruttenberg@cra.com|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA. bruttenberg@cra.com|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA. bruttenberg@cra.com|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA. bruttenberg@cra.com', 'United States|United States|United States|United States|United States', 0, 'Animals|Astrocytes|Image Processing, Computer-Assisted|Mice|Retina|Retinal Vessels', 'Journal Article', '10.1093/bioinformatics/btt052', '23396124', 'Microscopy advances have enabled the acquisition of large-scale biological images that capture whole tissues in situ. This in turn has fostered the study of spatial relationships between cells and various biological structures, which has proved enormously beneficial toward understanding organ and organism function. However, the unique nature of biological images and tissues precludes the application of many existing spatial mining and quantification methods necessary to make inferences about the data. Especially difficult is attempting to quantify the spatial correlation between heterogeneous structures and point objects, which often occurs in many biological tissues.'),
(77462, 2013, 'bio', 'GROMACS 45: a high-throughput and highly parallel open source molecular simulation toolkit', 'Pronk, Sander|Páll, Szilárd|Schulz, Roland|Larsson, Per|Bjelkmar, Pär|Apostolov, Rossen|Shirts, Michael R|Smith, Jeremy C|Kasson, Peter M|van der Spoel, David|Hess, Berk|Lindahl, Erik', 'Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.|Science for Life Laboratory, Stockholm and Uppsala, 171 21 Stockholm, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 3796, 'Algorithms|Molecular Dynamics Simulation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt055', '23407358', 'Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources.'),
(77463, 2013, 'bio', 'A dynamic Bayesian Markov model for phasing and characterizing haplotypes in next-generation sequencing', 'Zhang, Yu', 'Department of Statistics, The Pennsylvania State University, 325 Thomas, University Park, PA 16802, USA. yuzhang@stat.psu.edu', 'United States', 7, 'Algorithms|Bayes Theorem|Genotype|Genotyping Techniques|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Markov Chains|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btt065', '23407359', 'Next-generation sequencing (NGS) technologies have enabled whole-genome discovery and analysis of genetic variants in many species of interest. Individuals are often sequenced at low coverage for detecting novel variants, phasing haplotypes and inferring population structures. Although several tools have been developed for SNP and genotype calling in NGS data, haplotype phasing is often done separately on the called genotypes.'),
(77464, 2013, 'bio', 'Hybrid regulatory models: a statistically tractable approach to model regulatory network dynamics', 'Ocone, Andrea|Millar, Andrew J|Sanguinetti, Guido', 'School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Chlorophyta|Circadian Clocks|Computer Simulation|Gene Regulatory Networks|Humans|Models, Statistical|Protein Biosynthesis|Saccharomyces cerevisiae|Systems Biology|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btt069', '23407360', 'Computational modelling of the dynamics of gene regulatory networks is a central task of systems biology. For networks of small/medium scale, the dominant paradigm is represented by systems of coupled non-linear ordinary differential equations (ODEs). ODEs afford great mechanistic detail and flexibility, but calibrating these models to data is often an extremely difficult statistical problem.'),
(77465, 2013, 'bio', 'An approximate Bayesian approach for mapping paired-end DNA reads to a reference genome', 'Shrestha, Anish Man Singh|Frith, Martin C', 'Computational Biology Research Center, National Institute for Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan.|Computational Biology Research Center, National Institute for Advanced Industrial Science and Technology (AIST), Koto-ku, Tokyo, Japan.', 'Japan|Japan', 0, 'Animals|Bayes Theorem|Chromosome Mapping|Chromosomes, Human, X|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Macaca mulatta|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt073', '23413433', 'Many high-throughput sequencing experiments produce paired DNA reads. Paired-end DNA reads provide extra positional information that is useful in reliable mapping of short reads to a reference genome, as well as in downstream analyses of structural variations. Given the importance of paired-end alignments, it is surprising that there have been no previous publications focusing on this topic. In this article, we present a new probabilistic framework to predict the alignment of paired-end reads to a reference genome. Using both simulated and real data, we compare the performance of our method with six other read-mapping tools that provide a paired-end option. We show that our method provides a good combination of accuracy, error rate and computation time, especially in more challenging and practical cases, such as when the reference genome is incomplete or unavailable for the sample, or when there are large variations between the reference genome and the source of the reads. An open-source implementation of our method is available as part of Last, a multi-purpose alignment program freely available at http://last.cbrc.jp.'),
(77466, 2013, 'bio', 'Wessim: a whole-exome sequencing simulator based on in silico exome capture', 'Kim, Sangwoo|Jeong, Kyowon|Bafna, Vineet', 'Department of Computer Science and Engineering and Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093, USA. sak042@cs.ucsd.edu|Department of Computer Science and Engineering and Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093, USA. sak042@cs.ucsd.edu|Department of Computer Science and Engineering and Department of Electrical and Computer Engineering, University of California at San Diego, La Jolla, CA 92093, USA. sak042@cs.ucsd.edu', 'United States|United States|United States', 0, 'Computer Simulation|Exome|Genome, Human|Genomics|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt074', '23413434', 'We propose a targeted re-sequencing simulator Wessim that generates synthetic exome sequencing reads from a given sample genome. Wessim emulates conventional exome capture technologies, including Agilents SureSelect and NimbleGens SeqCap, to generate DNA fragments from genomic target regions. The target regions can be either specified by genomic coordinates or inferred from in silico probe hybridization. Coupled with existing next-generation sequencing simulators, Wessim generates a realistic artificial exome sequencing data, which is essential for developing and evaluating exome-targeted variant callers.'),
(77467, 2013, 'bio', 'A new way to protect privacy in large-scale genome-wide association studies', 'Kamm, Liina|Bogdanov, Dan|Laur, Sven|Vilo, Jaak', 'Institute of Computer Science, University of Tartu, Liivi 2, Tartu 50409, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2, Tartu 50409, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2, Tartu 50409, Estonia.|Institute of Computer Science, University of Tartu, Liivi 2, Tartu 50409, Estonia.', 'Estonia|Estonia|Estonia|Estonia', 0, 'Case-Control Studies|Data Interpretation, Statistical|Genome-Wide Association Study|Genotyping Techniques|Humans|Privacy', 'Journal Article', '10.1093/bioinformatics/btt066', '23413435', 'Increased availability of various genotyping techniques has initiated a race for finding genetic markers that can be used in diagnostics and personalized medicine. Although many genetic risk factors are known, key causes of common diseases with complex heritage patterns are still unknown. Identification of such complex traits requires a targeted study over a large collection of data. Ideally, such studies bring together data from many biobanks. However, data aggregation on such a large scale raises many privacy issues.'),
(77468, 2013, 'bio', 'SPINAL: scalable protein interaction network alignment', 'Aladag, Ahmet E|Erten, Cesim', 'Department of Computer Engineering, Bogaziçi University, Bebek, Istanbul 34342, Turkey.|Department of Computer Engineering, Bogaziçi University, Bebek, Istanbul 34342, Turkey.', 'Turkey|Turkey', 70, 'Algorithms|Animals|Humans|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btt071', '23413436', 'Given protein-protein interaction (PPI) networks of a pair of species, a pairwise global alignment corresponds to a one-to-one mapping between their proteins. Based on the presupposition that such a mapping provides pairs of functionally orthologous proteins accurately, the results of the alignment may then be used in comparative systems biology problems such as function prediction/verification or construction of evolutionary relationships.'),
(77469, 2013, 'bio', 'GalaxyGemini: a web server for protein homo-oligomer structure prediction based on similarity', 'Lee, Hasup|Park, Hahnbeom|Ko, Junsu|Seok, Chaok', 'Department of Chemistry, Seoul National University, Seoul, Republic of Korea.|Department of Chemistry, Seoul National University, Seoul, Republic of Korea.|Department of Chemistry, Seoul National University, Seoul, Republic of Korea.|Department of Chemistry, Seoul National University, Seoul, Republic of Korea.', '-|-|-|-', 0, 'Internet|Protein Multimerization|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btt079', '23413437', 'A large number of proteins function as homo-oligomers, therefore, predicting homo-oligomeric structure of proteins is of primary importance for understanding protein function at the molecular level. Here, we introduce a web server for prediction of protein homo-oligomer structure. The server takes a protein monomer structure as input and predicts its homo-oligomer structure from oligomer templates selected based on sequence and tertiary/quaternary structure similarity. Using protein model structures as input, the server shows clear improvement over the best methods of CASP9 in predicting oligomeric structures from amino acid sequences.'),
(77470, 2013, 'bio', 'Efficient comparison of sets of intervals with NC-lists', 'Zytnicki, Matthias|Luo, YuFei|Quesneville, Hadi', 'URGI, INRA Versailles, Plant Biology and Breeding Division, 78026 Versailles Cedex, France. matthias.zytnicki@versailles.inra.fr|URGI, INRA Versailles, Plant Biology and Breeding Division, 78026 Versailles Cedex, France. matthias.zytnicki@versailles.inra.fr|URGI, INRA Versailles, Plant Biology and Breeding Division, 78026 Versailles Cedex, France. matthias.zytnicki@versailles.inra.fr', 'France|France|France', 0, 'Algorithms|Genome|Genomics|High-Throughput Nucleotide Sequencing|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btt070', '23413438', 'High-throughput sequencing produces in a small amount of time a large amount of data, which are usually difficult to analyze. Mapping the reads to the transcripts they originate from, to quantify the expression of the genes, is a simple, yet time demanding, example of analysis. Fast genomic comparison algorithms are thus crucial for the analysis of the ever-expanding number of reads sequenced.'),
(77471, 2013, 'bio', 'A powerful Bayesian meta-analysis method to integrate multiple gene set enrichment studies', 'Chen, Min|Zang, Miao|Wang, Xinlei|Xiao, Guanghua', 'Quantitative Biomedical Research Center, Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. Min.Chen@UTSouthwestern.edu|Quantitative Biomedical Research Center, Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. Min.Chen@UTSouthwestern.edu|Quantitative Biomedical Research Center, Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. Min.Chen@UTSouthwestern.edu|Quantitative Biomedical Research Center, Department of Clinical Sciences, The University of Texas Southwestern Medical Center, Dallas, TX 75390, USA. Min.Chen@UTSouthwestern.edu', 'United States|United States|United States|United States', 0, 'Bayes Theorem|Gene Expression Profiling|Humans|Lung Neoplasms|Meta-Analysis as Topic|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btt068', '23418184', 'Much research effort has been devoted to the identification of enriched gene sets for microarray experiments. However, identified gene sets are often found to be inconsistent among independent studies. This is probably owing to the noisy data of microarray experiments coupled with small sample sizes of individual studies. Therefore, combining information from multiple studies is likely to improve the detection of truly enriched gene classes. As more and more data become available, it calls for statistical methods to integrate information from multiple studies, also known as meta-analysis, to improve the power of identifying enriched gene sets.'),
(77472, 2013, 'bio', 'eMZed: an open source framework in Python for rapid and interactive development of LC/MS data analysis workflows', 'Kiefer, Patrick|Schmitt, Uwe|Vorholt, Julia A', 'ETH Zurich, Institute of Microbiology, 8093 Zurich, Switzerland. kiefer@micro.biol.ethz.ch|ETH Zurich, Institute of Microbiology, 8093 Zurich, Switzerland. kiefer@micro.biol.ethz.ch|ETH Zurich, Institute of Microbiology, 8093 Zurich, Switzerland. kiefer@micro.biol.ethz.ch', 'Switzerland|Switzerland|Switzerland', 31, 'Chromatography, Liquid|Mass Spectrometry|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btt080', '23418185', 'The Python-based, open-source eMZed framework was developed for mass spectrometry (MS) users to create tailored workflows for liquid chromatography (LC)/MS data analysis. The goal was to establish a unique framework with comprehensive basic functionalities that are easy to apply and allow for the extension and modification of the framework in a straightforward manner. eMZed supports the iterative development and prototyping of individual evaluation strategies by providing a computing environment and tools for inspecting and modifying underlying LC/MS data. The framework specifically addresses non-expert programmers, as it requires only basic knowledge of Python and relies largely on existing successful open-source software, e.g. OpenMS.'),
(77473, 2013, 'bio', 'Prediction of contact matrix for protein-protein interaction', 'González, Alvaro J|Liao, Li|Wu, Cathy H', 'Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.|Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.|Department of Computer and Information Sciences, University of Delaware, Newark, DE 19716, USA.', 'United States|United States|United States', 10, 'Computational Biology|Markov Chains|Models, Molecular|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Sensitivity and Specificity|Sequence Alignment|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btt076', '23418186', 'Prediction of protein-protein interaction has become an important part of systems biology in reverse engineering the biological networks for better understanding the molecular biology of the cell. Although significant progress has been made in terms of prediction accuracy, most computational methods only predict whether two proteins interact but not their interacting residues-the information that can be very valuable for understanding the interaction mechanisms and designing modulation of the interaction. In this work, we developed a computational method to predict the interacting residue pairs-contact matrix for interacting protein domains, whose rows and columns correspond to the residues in the two interacting domains respectively and whose values (1 or 0) indicate whether the corresponding residues (do or do not) interact.'),
(77474, 2013, 'bio', 'Protein signature-based estimation of metagenomic abundances including all domains of life and viruses', 'Klingenberg, Heiner|Aßhauer, Kathrin Petra|Lingner, Thomas|Meinicke, Peter', 'Department of Bioinformatics, Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.|Department of Bioinformatics, Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.|Department of Bioinformatics, Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.|Department of Bioinformatics, Institute for Microbiology and Genetics, University of Göttingen, Göttingen, Germany.', 'Germany|Germany|Germany|Germany', 0, 'DNA, Archaeal|DNA, Viral|Humans|Metagenome|Metagenomics|Phylogeny|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btt077', '23418187', 'Metagenome analysis requires tools that can estimate the taxonomic abundances in anonymous sequence data over the whole range of biological entities. Because there is usually no prior knowledge about the data composition, not only all domains of life but also viruses have to be included in taxonomic profiling. Such a full-range approach, however, is difficult to realize owing to the limited coverage of available reference data. In particular, archaea and viruses are generally not well represented by current genome databases.'),
(77475, 2013, 'bio', 'Chemical rule-based filtering of MS/MS spectra', 'Reiz, Bexc3xa1ta|Kertxc3xa9sz-Farkas, Attila|Pongor, Sxc3xa1ndor|Myers, Michael P', 'Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy.|Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy.|Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy.|Protein Structure and Bioinformatics Group, International Centre for Genetic Engineering and Biotechnology, 34149 Trieste, Italy.', 'Italy|Italy|Italy|Italy', 4, 'Algorithms|Humans|Peptides|Protein Processing, Post-Translational|Proteins|Proteomics|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btt061', '23418188', 'Identification of proteins by mass spectrometry-based proteomics requires automated interpretation of peptide tandem mass spectrometry spectra. The effectiveness of peptide identification can be greatly improved by filtering out extraneous noise peaks before the subsequent database searching steps.'),
(77476, 2013, 'bio', 'Classification of mislabelled microarrays using robust sparse logistic regression', 'Bootkrajang, Jakramate|Kabxc3xa1n, Ata', 'School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. J.Bootkrajang@cs.bham.ac.uk|School of Computer Science, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK. J.Bootkrajang@cs.bham.ac.uk', 'United Kingdom|United Kingdom', 27, 'Algorithms|Bayes Theorem|Breast Neoplasms|Colonic Neoplasms|Female|Gene Expression Profiling|Humans|Logistic Models|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btt078', '23418189', 'Previous studies reported that labelling errors are not uncommon in microarray datasets. In such cases, the training set may become misleading, and the ability of classifiers to make reliable inferences from the data is compromised. Yet, few methods are currently available in the bioinformatics literature to deal with this problem. The few existing methods focus on data cleansing alone, without reference to classification, and their performance crucially depends on some tuning parameters.'),
(77477, 2013, 'bio', 'Drug-SNPing: an integrated drug-based, protein interaction-based tagSNP-based pharmacogenomics platform for SNP genotyping', 'Yang, Cheng-Hong|Cheng, Yu-Huei|Chuang, Li-Yeh|Chang, Hsueh-Wei', 'Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.|Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.|Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.|Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan.', '-|-|-|-', 11, 'Databases, Genetic|Genotyping Techniques|HapMap Project|Humans|Internet|Pharmacogenetics|Polymerase Chain Reaction|Polymorphism, Restriction Fragment Length|Polymorphism, Single Nucleotide|Protein Interaction Mapping|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt037', '23418190', 'Many drug or single nucleotide polymorphism (SNP)-related resources and tools have been developed, but connecting and integrating them is still a challenge. Here, we describe a user-friendly web-based software package, named Drug-SNPing, which provides a platform for the integration of drug information (DrugBank and PharmGKB), protein-protein interactions (STRING), tagSNP selection (HapMap) and genotyping information (dbSNP, REBASE and SNP500Cancer). DrugBank-based inputs include the following: (i) common name of the drug, (ii) synonym or drug brand name, (iii) gene name (HUGO) and (iv) keywords. PharmGKB-based inputs include the following: (i) gene name (HUGO), (ii) drug name and (iii) disease-related keywords. The output provides drug-related information, metabolizing enzymes and drug targets, as well as protein-protein interaction data. Importantly, tagSNPs of the selected genes are retrieved for genotyping analyses. All drug-based and protein-protein interaction-based SNP genotyping information are provided with PCR-RFLP (PCR-restriction enzyme length polymorphism) and TaqMan probes. Thus, users can enter any drug keywords/brand names to obtain immediate information that is highly relevant to genotyping for pharmacogenomics research.'),
(77478, 2013, 'bio', 'Non-parametric Bayesian approach to post-translational modification refinement of predictions from tandem mass spectrometry', 'Chung, Clement|Emili, Andrew|Frey, Brendan J', 'Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 2E4, Canada.', 'Canada|Canada|Canada', 7, 'Algorithms|Bayes Theorem|Cluster Analysis|Fungal Proteins|Humans|Phosphopeptides|Protein Interaction Mapping|Protein Processing, Post-Translational|Proteome|Proteomics|Statistics, Nonparametric|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btt056', '23419374', 'Tandem mass spectrometry (MS/MS) is a dominant approach for large-scale high-throughput post-translational modification (PTM) profiling. Although current state-of-the-art blind PTM spectral analysis algorithms can predict thousands of modified peptides (PTM predictions) in an MS/MS experiment, a significant percentage of these predictions have inaccurate modification mass estimates and false modification site assignments. This problem can be addressed by post-processing the PTM predictions with a PTM refinement algorithm. We developed a novel PTM refinement algorithm, iPTMClust, which extends a recently introduced PTM refinement algorithm PTMClust and uses a non-parametric Bayesian model to better account for uncertainties in the quantity and identity of PTMs in the input data. The use of this new modeling approach enables iPTMClust to provide a confidence score per modification site that allows fine-tuning and interpreting resulting PTM predictions.'),
(77479, 2013, 'bio', 'PLRS: a flexible tool for the joint analysis of DNA copy number and mRNA expression data', 'Leday, Gwenaël G R|van de Wiel, Mark A', 'Department of Mathematics, VU University, De Boelelaan 1081a, Amsterdam, The Netherlands. g.g.r.leday@vu.nl|Department of Mathematics, VU University, De Boelelaan 1081a, Amsterdam, The Netherlands. g.g.r.leday@vu.nl', 'Netherlands|Netherlands', 2, 'DNA Copy Number Variations|Gene Dosage|Glioblastoma|Humans|Models, Genetic|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btt082', '23419375', 'DNA copy number and mRNA expression are commonly used data types in cancer studies. Available software for integrative analysis arbitrarily fixes the parametric form of the association between the two molecular levels and hence offers no opportunities for modelling it. We present a new tool for flexible modelling of this association. PLRS uses a wide class of interpretable models including popular ones and incorporates prior biological knowledge. It is capable to identify the gene-specific type of relationship between gene copy number and mRNA expression. Moreover, it tests the strength of the association and provides confidence intervals. We illustrate PLRS using glioblastoma data from The Cancer Genome Atlas.'),
(77480, 2013, 'bio', 'Nozzle: a report generation toolkit for data analysis pipelines', 'Gehlenborg, Nils|Noble, Michael S|Getz, Gad|Chin, Lynda|Park, Peter J', 'Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.|Center for Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States', 11, 'Computational Biology|Genomics|Humans|Neoplasms|Programming Languages|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btt085', '23419376', 'We have developed Nozzle, an R package that provides an Application Programming Interface to generate HTML reports with dynamic user interface elements. Nozzle was designed to facilitate summarization and rapid browsing of complex results in data analysis pipelines where multiple analyses are performed frequently on big datasets. The package can be applied to any project where user-friendly reports need to be created.'),
(77481, 2013, 'bio', 'Accounting for non-genetic factors by low-rank representation and sparse regression for eQTL mapping', 'Yang, Can|Wang, Lin|Zhang, Shuqin|Zhao, Hongyu', 'Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.|Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.|Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.|Department of Biostatistics, Yale School of Public Health, New Haven, CT 06520, USA.', 'United States|United States|United States|United States', 23, 'Algorithms|Gene Expression|Models, Statistical|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Regression Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btt075', '23419377', 'Expression quantitative trait loci (eQTL) studies investigate how gene expression levels are affected by DNA variants. A major challenge in inferring eQTL is that a number of factors, such as unobserved covariates, experimental artifacts and unknown environmental perturbations, may confound the observed expression levels. This may both mask real associations and lead to spurious association findings.'),
(77482, 2013, 'bio', 'PleioGRiP: genetic risk prediction with pleiotropy', 'Hartley, Stephen W|Sebastiani, Paola', 'National Institutes of Health/National Human Genome Research Institute, 5625 Fishers Lane, Rockville, MD 20850, USA. stephen.hartley@nih.gov|National Institutes of Health/National Human Genome Research Institute, 5625 Fishers Lane, Rockville, MD 20850, USA. stephen.hartley@nih.gov', 'United States|United States', 6, 'Bayes Theorem|Genome-Wide Association Study|Humans|Phenotype|Polymorphism, Single Nucleotide|Risk|Software', 'Journal Article', '10.1093/bioinformatics/btt081', '23419378', 'Although several studies have used Bayesian classifiers for risk prediction using genome-wide single nucleotide polymorphism (SNP) datasets, no software can efficiently perform these analyses on massive genetic datasets and can accommodate multiple traits.'),
(77483, 2013, 'bio', 'QUAST: quality assessment tool for genome assemblies', 'Gurevich, Alexey|Saveliev, Vladislav|Vyahhi, Nikolay|Tesler, Glenn', 'Algorithmic Biology Laboratory, St. Petersburg Academic University, Russian Academy of Sciences, St. Petersburg, Russia. gurevich@bioinf.spbau.ru|Algorithmic Biology Laboratory, St. Petersburg Academic University, Russian Academy of Sciences, St. Petersburg, Russia. gurevich@bioinf.spbau.ru|Algorithmic Biology Laboratory, St. Petersburg Academic University, Russian Academy of Sciences, St. Petersburg, Russia. gurevich@bioinf.spbau.ru|Algorithmic Biology Laboratory, St. Petersburg Academic University, Russian Academy of Sciences, St. Petersburg, Russia. gurevich@bioinf.spbau.ru', '-|-|-|-', 1879, 'Algorithms|Animals|Chromosome Mapping|Contig Mapping|Escherichia coli|Genome|Genomic Structural Variation|Genomics|Humans|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt086', '23422339', 'Limitations of genome sequencing techniques have led to dozens of assembly algorithms, none of which is perfect. A number of methods for comparing assemblers have been developed, but none is yet a recognized benchmark. Further, most existing methods for comparing assemblies are only applicable to new assemblies of finished genomes, the problem of evaluating assemblies of previously unsequenced species has not been adequately considered. Here, we present QUAST-a quality assessment tool for evaluating and comparing genome assemblies. This tool improves on leading assembly comparison software with new ideas and quality metrics. QUAST can evaluate assemblies both with a reference genome, as well as without a reference. QUAST produces many reports, summary tables and plots to help scientists in their research and in their publications. In this study, we used QUAST to compare several genome assemblers on three datasets. QUAST tables and plots for all of them are available in the Supplementary Material, and interactive versions of these reports are on the QUAST website.'),
(77484, 2013, 'bio', 'IRootLab: a free and open-source MATLAB toolbox for vibrational biospectroscopy data analysis', 'Trevisan, Júlio|Angelov, Plamen P|Scott, Andrew D|Carmichael, Paul L|Martin, Francis L', 'School of Computing and Communications, Infolab21, Lancaster University, Lancaster, UK. juliotrevisan@gmail.com|School of Computing and Communications, Infolab21, Lancaster University, Lancaster, UK. juliotrevisan@gmail.com|School of Computing and Communications, Infolab21, Lancaster University, Lancaster, UK. juliotrevisan@gmail.com|School of Computing and Communications, Infolab21, Lancaster University, Lancaster, UK. juliotrevisan@gmail.com|School of Computing and Communications, Infolab21, Lancaster University, Lancaster, UK. juliotrevisan@gmail.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 86, 'Software|Spectrophotometry, Infrared|Spectrum Analysis, Raman|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt084', '23422340', 'IRootLab is a free and open-source MATLAB toolbox for vibrational biospectroscopy (VBS) data analysis. It offers an object-oriented programming class library, graphical user interfaces (GUIs) and automatic MATLAB code generation. The class library contains a large number of methods, concepts and visualizations for VBS data analysis, some of which are introduced in the toolbox. The GUIs provide an interface to the class library, including a module to merge several spectral files into a dataset. Automatic code allows developers to quickly write VBS data analysis scripts and is a unique resource among tools for VBS. Documentation includes a manual, tutorials, Doxygen-generated reference and a demonstration showcase. IRootLab can handle some of the most popular file formats used in VBS. License: GNU-LGPL.'),
(77485, 2013, 'bio', 'Systematic parameter estimation in data-rich environments for cell signalling dynamics', 'Nim, Tri Hieu|Luo, Le|Clément, Marie-Véronique|White, Jacob K|Tucker-Kellogg, Lisa', 'Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.|Computational Systems Biology Programme, Singapore-MIT Alliance, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 6, 'Algorithms|Computer Simulation|Models, Biological|Proteomics|Proto-Oncogene Proteins c-akt|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btt083', '23426255', 'Computational models of biological signalling networks, based on ordinary differential equations (ODEs), have generated many insights into cellular dynamics, but the model-building process typically requires estimating rate parameters based on experimentally observed concentrations. New proteomic methods can measure concentrations for all molecular species in a pathway, this creates a new opportunity to decompose the optimization of rate parameters.'),
(77486, 2013, 'bio', 'propy: a tool to generate various modes of Chous PseAAC', 'Cao, Dong-Sheng|Xu, Qing-Song|Liang, Yi-Zeng', 'Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, Peoples Republic of China.|Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, Peoples Republic of China.|Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, Peoples Republic of China.', 'China|China|China', 283, 'Amino Acids|Peptides|Protein Conformation|Proteins|Sequence Analysis, Protein|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt072', '23426256', 'Sequence-derived structural and physiochemical features have been frequently used for analysing and predicting structural, functional, expression and interaction profiles of proteins and peptides. To facilitate extensive studies of proteins and peptides, we developed a freely available, open source python package called protein in python (propy) for calculating the widely used structural and physicochemical features of proteins and peptides from amino acid sequence. It computes five feature groups composed of 13 features, including amino acid composition, dipeptide composition, tripeptide composition, normalized Moreau-Broto autocorrelation, Moran autocorrelation, Geary autocorrelation, sequence-order-coupling number, quasi-sequence-order descriptors, composition, transition and distribution of various structural and physicochemical properties and two types of pseudo amino acid composition (PseAAC) descriptors. These features could be generally regarded as different Chous PseAAC modes. In addition, it can also easily compute the previous descriptors based on user-defined properties, which are automatically available from the AAindex database.'),
(77487, 2013, 'bio', 'Planform: an application and database of graph-encoded planarian regenerative experiments', 'Lobo, Daniel|Malone, Taylor J|Levin, Michael', 'Department of Biology, Center for Regenerative and Developmental Biology, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA.|Department of Biology, Center for Regenerative and Developmental Biology, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA.|Department of Biology, Center for Regenerative and Developmental Biology, Tufts University, 200 Boston Avenue, Medford, MA 02155, USA.', 'United States|United States|United States', 16, 'Animals|Computer Graphics|Databases, Factual|Planarians|Regeneration|Software', 'Journal Article', '10.1093/bioinformatics/btt088', '23426257', 'Understanding the mechanisms governing the regeneration capabilities of many organisms is a fundamental interest in biology and medicine. An ever-increasing number of manipulation and molecular experiments are attempting to discover a comprehensive model for regeneration, with the planarian flatworm being one of the most important model species. Despite much effort, no comprehensive, constructive, mechanistic models exist yet, and it is now clear that computational tools are needed to mine this huge dataset. However, until now, there is no database of regenerative experiments, and the current genotype-phenotype ontologies and databases are based on textual descriptions, which are not understandable by computers. To overcome these difficulties, we present here Planform (Planarian formalization), a manually curated database and software tool for planarian regenerative experiments, based on a mathematical graph formalism. The database contains more than a thousand experiments from the main publications in the planarian literature. The software tool provides the user with a graphical interface to easily interact with and mine the database. The presented system is a valuable resource for the regeneration community and, more importantly, will pave the way for the application of novel artificial intelligence tools to extract knowledge from this dataset.'),
(77488, 2013, 'bio', 'The prediction of organelle-targeting peptides in eukaryotic proteins with Grammatical-Restrained Hidden Conditional Random Fields', 'Indio, Valentina|Martelli, Pier Luigi|Savojardo, Castrense|Fariselli, Piero|Casadio, Rita', 'Biocomputing Group, and Giorgio Prodi Interdepartmental Center for Cancer Research, University of Bologna, Bologna, Italy.|Biocomputing Group, and Giorgio Prodi Interdepartmental Center for Cancer Research, University of Bologna, Bologna, Italy.|Biocomputing Group, and Giorgio Prodi Interdepartmental Center for Cancer Research, University of Bologna, Bologna, Italy.|Biocomputing Group, and Giorgio Prodi Interdepartmental Center for Cancer Research, University of Bologna, Bologna, Italy.|Biocomputing Group, and Giorgio Prodi Interdepartmental Center for Cancer Research, University of Bologna, Bologna, Italy.', 'Italy|Italy|Italy|Italy|Italy', 12, 'Arabidopsis Proteins|Chloroplast Proteins|Eukaryota|Humans|Mitochondria|Mitochondrial Proteins|Peptides|Plastids|Position-Specific Scoring Matrices|Protein Sorting Signals|Proteome|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btt089', '23428638', 'Targeting peptides are the most important signal controlling the import of nuclear encoded proteins into mitochondria and plastids. In the lack of experimental information, their prediction is an essential step when proteomes are annotated for inferring both the localization and the sequence of mature proteins.'),
(77489, 2013, 'bio', 'Poisson factor models with applications to non-normalized microRNA profiling', 'Lee, Seonjoo|Chugh, Pauline E|Shen, Haipeng|Eberle, R|Dittmer, Dirk P', 'Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20892, USA.|Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20892, USA.|Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20892, USA.|Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20892, USA.|Center for Neuroscience and Regenerative Medicine, The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD 20892, USA.', 'United States|United States|United States|United States|United States', 12, 'Algorithms|Cluster Analysis|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|MicroRNAs|Models, Statistical|Poisson Distribution|Software', 'Journal Article', '10.1093/bioinformatics/btt091', '23428639', 'Next-generation (NextGen) sequencing is becoming increasingly popular as an alternative for transcriptional profiling, as is the case for micro RNAs (miRNA) profiling and classification. miRNAs are a new class of molecules that are regulated in response to differentiation, tumorigenesis or infection. Our primary motivating application is to identify different viral infections based on the induced change in the host miRNA profile. Statistical challenges are encountered because of special features of NextGen sequencing data: the data are read counts that are extremely skewed and non-negative, the total number of reads varies dramatically across samples that require appropriate normalization. Statistical tools developed for microarray expression data, such as principal component analysis, are sub-optimal for analyzing NextGen sequencing data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77490, 2013, 'bio', 'Making automated multiple alignments of very large numbers of protein sequences', 'Sievers, Fabian|Dineen, David|Wilm, Andreas|Higgins, Desmond G', 'School of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin 4, Ireland. fabian.sievers@ucd.ie|School of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin 4, Ireland. fabian.sievers@ucd.ie|School of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin 4, Ireland. fabian.sievers@ucd.ie|School of Medicine and Medical Science, Conway Institute, University College Dublin, Dublin 4, Ireland. fabian.sievers@ucd.ie', 'Ireland|Ireland|Ireland|Ireland', 38, 'Algorithms|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btt093', '23428640', 'Recent developments in sequence alignment software have made possible multiple sequence alignments (MSAs) of >100 000 sequences in reasonable times. At present, there are no systematic analyses concerning the scalability of the alignment quality as the number of aligned sequences is increased.'),
(77491, 2013, 'bio', 'EBSeq: an empirical Bayes hierarchical model for inference in RNA-seq experiments', 'Leng, Ning|Dawson, John A|Thomson, James A|Ruotti, Victor|Rissman, Anna I|Smits, Bart M G|Haag, Jill D|Gould, Michael N|Stewart, Ron M|Kendziorski, Christina', 'Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.|Department of Statistics, University of Wisconsin, Madison, WI 53706, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Bayes Theorem|Cell Line|Embryonic Stem Cells|Gene Expression Profiling|Genome|Models, Statistical|RNA Isoforms|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt087', '23428641', 'Messenger RNA expression is important in normal development and differentiation, as well as in manifestation of disease. RNA-seq experiments allow for the identification of differentially expressed (DE) genes and their corresponding isoforms on a genome-wide scale. However, statistical methods are required to ensure that accurate identifications are made. A number of methods exist for identifying DE genes, but far fewer are available for identifying DE isoforms. When isoform DE is of interest, investigators often apply gene-level (count-based) methods directly to estimates of isoform counts. Doing so is not recommended. In short, estimating isoform expression is relatively straightforward for some groups of isoforms, but more challenging for others. This results in estimation uncertainty that varies across isoform groups. Count-based methods were not designed to accommodate this varying uncertainty, and consequently, application of them for isoform inference results in reduced power for some classes of isoforms and increased false discoveries for others.'),
(77492, 2013, 'bio', 'DeconRNASeq: a statistical framework for deconvolution of heterogeneous tissue samples based on mRNA-Seq data', 'Gong, Ting|Szustakowski, Joseph D', 'Biomarker Development, Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA. tinggong@gmail.com|Biomarker Development, Translational Medicine, Novartis Institutes for BioMedical Research, Cambridge, MA 02139, USA. tinggong@gmail.com', 'United States|United States', 83, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Linear Models|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt090', '23428642', 'For heterogeneous tissues, measurements of gene expression through mRNA-Seq data are confounded by relative proportions of cell types involved. In this note, we introduce an efficient pipeline: DeconRNASeq, an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It adopts a globally optimized non-negative decomposition algorithm through quadratic programming for estimating the mixing proportions of distinctive tissue types in next-generation sequencing data. We demonstrated the feasibility and validity of DeconRNASeq across a range of mixing levels and sources using mRNA-Seq data mixed in silico at known concentrations. We validated our computational approach for various benchmark data, with high correlation between our predicted cell proportions and the real fractions of tissues. Our study provides a rigorous, quantitative and high-resolution tool as a prerequisite to use mRNA-Seq data. The modularity of package design allows an easy deployment of custom analytical pipelines for data from other high-throughput platforms.'),
(77493, 2013, 'bio', 'An improved constraint filtering technique for inferring hidden states and parameters of a biological model', 'Murtuza Baker, Syed|Poskar, C Hart|Schreiber, Falk|Junker, Björn H', 'Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. baker@ipk-gatersleben.de|Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. baker@ipk-gatersleben.de|Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. baker@ipk-gatersleben.de|Systems Biology Group, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. baker@ipk-gatersleben.de', 'Germany|Germany|Germany|Germany', 8, 'Algorithms|Gene Regulatory Networks|Glycolysis|Kinetics|Models, Biological|Nonlinear Dynamics|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt097', '23434837', 'In systems biology, kinetic models represent the biological system using a set of ordinary differential equations (ODEs). The correct values of the parameters within these ODEs are critical for a reliable study of the dynamic behaviour of such systems. Typically, it is only possible to experimentally measure a fraction of these parameter values. The rest must be indirectly determined from measurements of other quantities. In this article, we propose a novel statistical inference technique to computationally estimate these unknown parameter values. By characterizing the ODEs with non-linear state-space equations, this inference technique models the unknown parameters as hidden states, which can then be estimated from noisy measurement data.'),
(77494, 2013, 'bio', 'Measuring guide-tree dependency of inferred gaps in progressive aligners', 'Capella-Gutiérrez, Salvador|Gabaldón, Toni', 'Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Doctor Aiguader 88 and Universitat Pompeu Fabra, Barcelona, Spain.|Bioinformatics and Genomics Programme, Centre for Genomic Regulation (CRG), Doctor Aiguader 88 and Universitat Pompeu Fabra, Barcelona, Spain.', 'Spain|Spain', 0, 'Phylogeny|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btt095', '23435067', 'Multiple sequence alignments are generally reconstructed using a progressive approach that follows a guide-tree. During this process, gaps are introduced at a cost to maximize residue pairing, but it is unclear whether inferred gaps reflect actual past events of sequence insertions or deletions. It has been found that patterns of inferred gaps in alignments contain information towards the true phylogeny, but it is as yet unknown whether gaps are simply reflecting information that was already present in the guide-tree.'),
(77495, 2013, 'bio', 'Genetic Simulation Resources: a website for the registration and discovery of genetic data simulators', 'Peng, Bo|Chen, Huann-Sheng|Mechanic, Leah E|Racine, Ben|Clarke, John|Clarke, Lauren|Gillanders, Elizabeth|Feuer, Eric J', 'Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 17, 'Computer Simulation|Evolution, Molecular|Genome, Human|Humans|Internet|Models, Genetic|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btt094', '23435068', 'Many simulation methods and programs have been developed to simulate genetic data of the human genome. These data have been widely used, for example, to predict properties of populations retrospectively or prospectively according to mathematically intractable genetic models, and to assist the validation, statistical inference and power analysis of a variety of statistical models. However, owing to the differences in type of genetic data of interest, simulation methods, evolutionary features, input and output formats, terminologies and assumptions for different applications, choosing the right tool for a particular study can be a resource-intensive process that usually involves searching, downloading and testing many different simulation programs. Genetic Simulation Resources (GSR) is a website provided by the National Cancer Institute (NCI) that aims to help researchers compare and choose the appropriate simulation tools for their studies. This website allows authors of simulation software to register their applications and describe them with well-defined attributes, thus allowing site users to search and compare simulators according to specified features.'),
(77496, 2013, 'bio', 'BioJS: an open source JavaScript framework for biological data visualization', 'Gómez, John|García, Leyla J|Salazar, Gustavo A|Villaveces, Jose|Gore, Swanand|García, Alexander|Martín, Maria J|Launay, Guillaume|Alcántara, Rafael|Del-Toro, Noemi|Dumousseau, Marine|Orchard, Sandra|Velankar, Sameer|Hermjakob, Henning|Zong, Chenggong|Ping, Peipei|Corpas, Manuel|Jiménez, Rafael C', 'European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.|European Bioinformatics Institute, Hinxton, Cambridge, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|', 0, 'Computer Graphics|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btt100', '23435069', 'BioJS is an open-source project whose main objective is the visualization of biological data in JavaScript. BioJS provides an easy-to-use consistent framework for bioinformatics application programmers. It follows a community-driven standard specification that includes a collection of components purposely designed to require a very simple configuration and installation. In addition to the programming framework, BioJS provides a centralized repository of components available for reutilization by the bioinformatics community.'),
(77497, 2013, 'bio', 'Improvements on bicriteria pairwise sequence alignment: algorithms and applications', 'Abbasi, Maryam|Paquete, Luís|Liefooghe, Arnaud|Pinheiro, Miguel|Matias, Pedro', 'CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, Coimbra, Portugal.|CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, Coimbra, Portugal.|CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, Coimbra, Portugal.|CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, Coimbra, Portugal.|CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, Coimbra, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|Animals|Genes, Fungal|Humans|Likelihood Functions|Phylogeny|Primates|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btt098', '23435070', 'In this article, we consider the bicriteria pairwise sequence alignment problem and propose extensions of dynamic programming algorithms for several problem variants with a novel pruning technique that efficiently reduces the number of states to be processed. Moreover, we present a method for the construction of phylogenetic trees based on this bicriteria framework. Two exemplary cases are discussed.'),
(77498, 2013, 'bio', 'Effectively addressing complex proteomic search spaces with peptide spectrum matching', 'Borges, Diogo|Perez-Riverol, Yasset|Nogueira, Fabio C S|Domont, Gilberto B|Noda, Jesus|da Veiga Leprevost, Felipe|Besada, Vladimir|França, Felipe M G|Barbosa, Valmir C|Sánchez, Aniel|Carvalho, Paulo C', 'Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.|Systems Engineering and Computer Science Program, Federal University of Rio de Janeiro, 21941-972 Rio de Janeiro, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 13, 'Algorithms|Amino Acid Sequence|Escherichia coli|Escherichia coli Proteins|Mass Spectrometry|Peptides|Protein Processing, Post-Translational|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btt106', '23446294', 'Protein identification by mass spectrometry is commonly accomplished using a peptide sequence matching search algorithm, whose sensitivity varies inversely with the size of the sequence database and the number of post-translational modifications considered. We present the Spectrum Identification Machine, a peptide sequence matching tool that capitalizes on the high-intensity b1-fragment ion of tandem mass spectra of peptides coupled in solution with phenylisotiocyanate to confidently sequence the first amino acid and ultimately reduce the search space. We demonstrate that in complex search spaces, a gain of some 120% in sensitivity can be achieved.'),
(77499, 2013, 'bio', 'SplicingCompass: differential splicing detection using RNA-seq data', 'Aschoff, Moritz|Hotz-Wagenblatt, Agnes|Glatting, Karl-Heinz|Fischer, Matthias|Eils, Roland|König, Rainer', 'Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de|Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de|Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de|Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de|Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de|Bioinformatics HUSAR, Genomics Proteomics Core Facility, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. m.aschoff@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 37, 'Algorithms|Alternative Splicing|Exons|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Neuroblastoma|RNA Splice Sites|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt101', '23449093', 'Alternative splicing is central for cellular processes and substantially increases transcriptome and proteome diversity. Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types. The emergence of next-generation RNA sequencing (RNA-seq) provides an exciting new technology to analyse alternative splicing on a large scale. However, algorithms that enable the analysis of alternative splicing from short-read sequencing are not fully established yet and there are still no standard solutions available for a variety of data analysis tasks.'),
(77500, 2013, 'bio', 'Using tertiary structure for the computation of highly accurate multiple RNA alignments with the SARA-Coffee package', 'Kemena, Carsten|Bussotti, Giovanni|Capriotti, Emidio|Marti-Renom, Marc A|Notredame, Cedric', 'Bioinformatics and Genomics Program, Centre for Genomic Regulation, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation, 08003 Barcelona, Spain.|Bioinformatics and Genomics Program, Centre for Genomic Regulation, 08003 Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain', 0, 'Algorithms|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt096', '23449094', 'Aligning RNAs is useful to search for homologous genes, study evolutionary relationships, detect conserved regions and identify any patterns that may be of biological relevance. Poor levels of conservation among homologs, however, make it difficult to compare RNA sequences, even when considering closely evolutionary related sequences.'),
(77501, 2013, 'bio', 'EBARDenovo: highly accurate de novo assembly of RNA-Seq with efficient chimera-detection', 'Chu, Hsueh-Ting|Hsiao, William W L|Chen, Jen-Chih|Yeh, Tze-Jung|Tsai, Mong-Hsun|Lin, Han|Liu, Yen-Wenn|Lee, Sheng-An|Chen, Chaur-Chin|Tsao, Theresa T H|Kao, Cheng-Yan', 'Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw|Department of Biomedical informatics, Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan. htchu@asia.edu.tw', '-|-|-|-|-|-|-|-|-|-|-', 0, 'Algorithms|Gene Expression Profiling|RNA|Repetitive Sequences, Nucleic Acid|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt092', '23457040', 'High-accuracy de novo assembly of the short sequencing reads from RNA-Seq technology is very challenging. We introduce a de novo assembly algorithm, EBARDenovo, which stands for Extension, Bridging And Repeat-sensing Denovo. This algorithm uses an efficient chimera-detection function to abrogate the effect of aberrant chimeric reads in RNA-Seq data.'),
(77502, 2013, 'bio', 'ChIP-PED enhances the analysis of ChIP-seq and ChIP-chip data', 'Wu, George|Yustein, Jason T|McCall, Matthew N|Zilliox, Michael|Irizarry, Rafael A|Zeller, Karen|Dang, Chi V|Ji, Hongkai', 'Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.|Department of Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD 21205, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 13, 'Animals|Binding Sites|Cell Line, Tumor|Chromatin Immunoprecipitation|Gene Expression Regulation|High-Throughput Nucleotide Sequencing|Humans|Mice|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Transcription Factors|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt108', '23457041', 'Although chromatin immunoprecipitation coupled with high-throughput sequencing (ChIP-seq) or tiling array hybridization (ChIP-chip) is increasingly used to map genome-wide-binding sites of transcription factors (TFs), it still remains difficult to generate a quality ChIPx (i.e. ChIP-seq or ChIP-chip) dataset because of the tremendous amount of effort required to develop effective antibodies and efficient protocols. Moreover, most laboratories are unable to easily obtain ChIPx data for one or more TF(s) in more than a handful of biological contexts. Thus, standard ChIPx analyses primarily focus on analyzing data from one experiment, and the discoveries are restricted to a specific biological context.'),
(77503, 2013, 'bio', 'RCPedia: a database of retrocopied genes', 'Navarro, Fábio C P|Galante, Pedro A F', 'Centro de Oncologia Molecular, Hospital Sírio-Libanês, São Paulo 01308-060, Brazil.|Centro de Oncologia Molecular, Hospital Sírio-Libanês, São Paulo 01308-060, Brazil.', 'Brazil|Brazil', 15, 'Animals|Databases, Genetic|Exons|Genes|Genome|Humans|Primates', 'Journal Article', '10.1093/bioinformatics/btt104', '23457042', 'Retrocopies are copies of mature RNAs that are usually devoid of regulatory sequences and introns. They have routinely been classified as processed pseudo-genes with little or no biological relevance. However, recent findings have revealed functional roles for retrocopies, as well as their high frequency in some organisms, such as primates. Despite their increasing importance, there is no user-friendly and publicly available resource for the study of retrocopies.'),
(77504, 2013, 'bio', 'A rate-distortion theory for gene regulatory networks and its application to logic gate consistency', 'Facchetti, Giuseppe|Iacono, Giovanni|De Palo, Giovanna|Altafini, Claudio', 'SISSA, Int. School for Advanced Studies, via Bonomea 265, 34136 Trieste, Italy.|SISSA, Int. School for Advanced Studies, via Bonomea 265, 34136 Trieste, Italy.|SISSA, Int. School for Advanced Studies, via Bonomea 265, 34136 Trieste, Italy.|SISSA, Int. School for Advanced Studies, via Bonomea 265, 34136 Trieste, Italy.', 'Italy|Italy|Italy|Italy', 1, 'Escherichia coli|Gene Expression Regulation|Gene Regulatory Networks|Information Theory|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/btt116', '23471299', 'A gene regulatory network in which the modes (activation/inhibition) of the transcriptional regulations are known and in which gene expression assumes boolean values can be treated as a system of linear equations over a binary field, i.e. as a constraint satisfaction problem for an information code.'),
(77505, 2013, 'bio', 'freeIbis: an efficient basecaller with calibrated quality scores for Illumina sequencers', 'Renaud, Gabriel|Kircher, Martin|Stenzel, Udo|Kelso, Janet', 'Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.|Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D-04103 Leipzig, Germany.', 'Germany|Germany|Germany|Germany', 49, 'Calibration|Genotyping Techniques|Reproducibility of Results|Sequence Analysis, DNA|Software|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btt117', '23471300', 'The conversion of the raw intensities obtained from next-generation sequencing platforms into nucleotide sequences with well-calibrated quality scores is a critical step in the generation of good sequence data. While recent model-based approaches can yield highly accurate calls, they require a substantial amount of processing time and/or computational resources. We previously introduced Ibis, a fast and accurate basecaller for the Illumina platform. We have continued active development of Ibis to take into account developments in the Illumina technology, as well as to make Ibis fully open source.'),
(77506, 2013, 'bio', 'MitoSeek: extracting mitochondria information and performing high-throughput mitochondria sequencing analysis', 'Guo, Yan|Li, Jiang|Li, Chung-I|Shyr, Yu|Samuels, David C', 'Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu|Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu|Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu|Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu|Center for Quantitative Sciences, Vanderbilt University, Nashville, TN 37232, USA. yan.guo@vanderbilt.edu', 'United States|United States|United States|United States|United States', 0, 'Chromosome Mapping|DNA, Mitochondrial|Data Mining|Exome|Genome, Mitochondrial|High-Throughput Nucleotide Sequencing|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt118', '23471301', 'Exome capture kits have capture efficiencies that range from 40 to 60%. A significant amount of off-target reads are from the mitochondrial genome. These unintentionally sequenced mitochondrial reads provide unique opportunities to study the mitochondria genome.'),
(77507, 2013, 'bio', 'PLncDB: plant long non-coding RNA database', 'Jin, Jingjing|Liu, Jun|Wang, Huan|Wong, Limsoon|Chua, Nam-Hai', 'Laboratory of Plant Molecular Biology, Rockefeller University, New York, NY 10065, USA.|Laboratory of Plant Molecular Biology, Rockefeller University, New York, NY 10065, USA.|Laboratory of Plant Molecular Biology, Rockefeller University, New York, NY 10065, USA.|Laboratory of Plant Molecular Biology, Rockefeller University, New York, NY 10065, USA.|Laboratory of Plant Molecular Biology, Rockefeller University, New York, NY 10065, USA.', 'United States|United States|United States|United States|United States', 0, 'Arabidopsis|Databases, Nucleic Acid|Epigenesis, Genetic|Gene Expression Profiling|Genetic Loci|Genome, Plant|Genomics|RNA, Long Noncoding|RNA, Plant|RNA, Small Interfering', 'Journal Article', '10.1093/bioinformatics/btt107', '23476021', 'Plant long non-coding RNA database (PLncDB) attempts to provide the following functions related to long non-coding RNAs (lncRNAs): (i) Genomic information for a large number of lncRNAs collected from various resources, (ii) an online genome browser for plant lncRNAs based on a platform similar to that of the UCSC Genome Browser, (iii) Integration of transcriptome datasets derived from various samples including different tissues, developmental stages, mutants and stress treatments, and (iv) A list of epigenetic modification datasets and small RNA datasets. Currently, our PLncDB provides a comprehensive genomic view of Arabidopsis lncRNAs for the plant research community. This database will be regularly updated with new plant genome when available so as to greatly facilitate future investigations on plant lncRNAs.'),
(77508, 2013, 'bio', 'FTFlex: accounting for binding site flexibility to improve fragment-based identification of druggable hot spots', 'Grove, Laurie E|Hall, David R|Beglov, Dmitri|Vajda, Sandor|Kozakov, Dima', 'Department of Sciences, Wentworth Institute of Technology, Boston, MA 01746, USA.|Department of Sciences, Wentworth Institute of Technology, Boston, MA 01746, USA.|Department of Sciences, Wentworth Institute of Technology, Boston, MA 01746, USA.|Department of Sciences, Wentworth Institute of Technology, Boston, MA 01746, USA.|Department of Sciences, Wentworth Institute of Technology, Boston, MA 01746, USA.', 'United States|United States|United States|United States|United States', 21, 'Algorithms|Binding Sites|Drug Design|Ligands|Models, Molecular|Protein Conformation|Proteins|Software|Solvents', 'Journal Article', '10.1093/bioinformatics/btt102', '23476022', 'Computational solvent mapping finds binding hot spots, determines their druggability and provides information for drug design. While mapping of a ligand-bound structure yields more accurate results, usually the apo structure serves as the starting point in design. The FTFlex algorithm, implemented as a server, can modify an apo structure to yield mapping results that are similar to those of the respective bound structure. Thus, FTFlex is an extension of our FTMap server, which only considers rigid structures. FTFlex identifies flexible residues within the binding site and determines alternative conformations using a rotamer library. In cases where the mapping results of the apo structure were in poor agreement with those of the bound structure, FTFlex was able to yield a modified apo structure, which lead to improved FTMap results. In cases where the mapping results of the apo and bound structures were in good agreement, no new structure was predicted.'),
(77509, 2013, 'bio', 'Specificity and affinity quantification of protein-protein interactions', 'Yan, Zhiqiang|Guo, Liyong|Hu, Liang|Wang, Jin', 'Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY 11794-3400, USA.|Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY 11794-3400, USA.|Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY 11794-3400, USA.|Department of Chemistry and Physics, State University of New York at Stony Brook, Stony Brook, NY 11794-3400, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Molecular Docking Simulation|Multiprotein Complexes|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt121', '23476023', 'Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones.'),
(77510, 2013, 'bio', 'EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats', 'Ison, Jon|Kalas, Matús|Jonassen, Inge|Bolser, Dan|Uludag, Mahmut|McWilliam, Hamish|Malone, James|Lopez, Rodrigo|Pettifer, Steve|Rice, Peter', 'EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk|EMBL European Bioinformatics Institute, Hinxton, Cambridge CB10 1SD, UK. jison@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 92, 'Algorithms|Computational Biology|Databases, Factual|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btt113', '23479348', 'Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required.'),
(77511, 2013, 'bio', 'Galaxy LIMS for next-generation sequencing', 'Scholtalbers, Jelle|Rößler, Jasmin|Sorn, Patrick|de Graaf, Jos|Boisguérin, Valesca|Castle, John|Sahin, Ugur', 'Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de|Computational Medicine, TRON - Translational Oncology at the Johannes Gutenberg University of Mainz Medicine, 55131 Mainz, Germany. jelle.scholtalbers@tron-mainz.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'High-Throughput Nucleotide Sequencing|Information Systems|Software|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btt115', '23479349', 'We have developed a laboratory information management system (LIMS) for a next-generation sequencing (NGS) laboratory within the existing Galaxy platform. The system provides lab technicians standard and customizable sample information forms, barcoded submission forms, tracking of input sample quality, multiplex-capable automatic flow cell design and automatically generated sample sheets to aid physical flow cell preparation. In addition, the platform provides the researcher with a user-friendly interface to create a request, submit accompanying samples, upload sample quality measurements and access to the sequencing results. As the LIMS is within the Galaxy platform, the researcher has access to all Galaxy analysis tools and workflows. The system reports requests and associated information to a message queuing system, such that information can be posted and stored in external systems, such as a wiki. Through an API, raw sequencing results can be automatically pre-processed and uploaded to the appropriate request folder. Developed for the Illumina HiSeq 2000 instrument, many features are directly applicable to other instruments.'),
(77512, 2013, 'bio', 'NTFD--a stand-alone application for the non-targeted detection of stable isotope-labeled compounds in GC/MS data', 'Hiller, Karsten|Wegner, André|Weindl, Daniel|Cordes, Thekla|Metallo, Christian M|Kelleher, Joanne K|Stephanopoulos, Gregory', 'Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-Belval, Luxembourg.', 'Luxembourg|Luxembourg|Luxembourg|Luxembourg|Luxembourg|Luxembourg|Luxembourg', 0, 'Gas Chromatography-Mass Spectrometry|Isotope Labeling|Metabolic Networks and Pathways|Metabolomics|Software', 'Journal Article', '10.1093/bioinformatics/btt119', '23479350', 'Most current stable isotope-based methodologies are targeted and focus only on the well-described aspects of metabolic networks. Here, we present NTFD (non-targeted tracer fate detection), a software for the non-targeted analysis of all detectable compounds derived from a stable isotope-labeled tracer present in a GC/MS dataset. In contrast to traditional metabolic flux analysis approaches, NTFD does not depend on any a priori knowledge or library information. To obtain dynamic information on metabolic pathway activity, NTFD determines mass isotopomer distributions for all detected and labeled compounds. These data provide information on relative fluxes in a metabolic network. The graphical user interface allows users to import GC/MS data in netCDF format and export all information into a tab-separated format.'),
(77513, 2013, 'bio', 'A temporal switch model for estimating transcriptional activity in gene expression', 'Jenkins, Dafyd J|Finkenstädt, Bärbel|Rand, David A', 'Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK.|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK.|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK.', 'United Kingdom|United Kingdom|United Kingdom', 8, 'Algorithms|Arabidopsis|Bayes Theorem|Circadian Rhythm|Kinetics|Markov Chains|Models, Genetic|Monte Carlo Method|Promoter Regions, Genetic|RNA Stability|RNA, Messenger|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btt111', '23479351', 'The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription-polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states.'),
(77514, 2013, 'bio', 'HExpoChem: a systems biology resource to explore human exposure to chemicals', 'Taboureau, Olivier|Jacobsen, Ulrik Plesner|Kalhauge, Christian|Edsgärd, Daniel|Rigina, Olga|Gupta, Ramneek|Audouze, Karine', 'Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.|Department of Systems Biology, Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Lyngby, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 0, 'Computational Biology|Disease|Environmental Exposure|Hazardous Substances|Humans|Multiprotein Complexes|Protein Interaction Mapping|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt112', '23479352', 'Humans are exposed to diverse hazardous chemicals daily. Although an exposure to these chemicals is suspected to have adverse effects on human health, mechanistic insights into how they interact with the human body are still limited. Therefore, acquisition of curated data and development of computational biology approaches are needed to assess the health risks of chemical exposure. Here we present HExpoChem, a tool based on environmental chemicals and their bioactivities on human proteins with the objective of aiding the qualitative exploration of human exposure to chemicals. The chemical-protein interactions have been enriched with a quality-scored human protein-protein interaction network, a protein-protein association network and a chemical-chemical interaction network, thus allowing the study of environmental chemicals through formation of protein complexes and phenotypic outcomes enrichment.'),
(77515, 2013, 'bio', 'JAWAMix5: an out-of-core HDF5-based java implementation of whole-genome association studies using mixed models', 'Long, Quan|Zhang, Qingrun|Vilhjalmsson, Bjarni J|Forai, Petar|Seren, Ümit|Nordborg, Magnus', 'Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at|Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at|Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at|Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at|Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at|Gregor Mendel Institute, Austrian Academy of Sciences, Vienna 1030, Austria. quan.long@gmi.oeaw.ac.at', 'Austria|Austria|Austria|Austria|Austria|Austria', 0, 'Bayes Theorem|Genome-Wide Association Study|Genotype|High-Throughput Nucleotide Sequencing|Linear Models|Software', 'Journal Article', '10.1093/bioinformatics/btt122', '23479353', 'We present JAWAMix5, an out-of-core open-source toolkit for association mapping using high-throughput sequence data. Taking advantage of its HDF5-based implementation, JAWAMix5 stores genotype data on disk and accesses them as though stored in main memory. Therefore, it offers a scalable and fast analysis without concerns about memory usage, whatever the size of the dataset. We have implemented eight functions for association studies, including standard methods (linear models, linear mixed models, rare variants test, analysis in nested association mapping design and local variance component analysis), as well as a novel Bayesian local variance component analysis. Application to real data demonstrates that JAWAMix5 is reasonably fast compared with traditional solutions that load the complete dataset into memory, and that the memory usage is efficient regardless of the dataset size.'),
(77516, 2013, 'bio', 'Modeling risk stratification in human cancer', 'Rème, Thierry|Hose, Dirk|Theillet, Charles|Klein, Bernard', 'INSERM-UM1, U1040, Institut de Recherche en Biothérapie, 34295 Montpellier, France. thierry.reme@inserm.fr|INSERM-UM1, U1040, Institut de Recherche en Biothérapie, 34295 Montpellier, France. thierry.reme@inserm.fr|INSERM-UM1, U1040, Institut de Recherche en Biothérapie, 34295 Montpellier, France. thierry.reme@inserm.fr|INSERM-UM1, U1040, Institut de Recherche en Biothérapie, 34295 Montpellier, France. thierry.reme@inserm.fr', 'France|France|France|France', 33, 'Algorithms|Breast Neoplasms|Female|Gene Expression Profiling|Glioma|Humans|Models, Statistical|Multiple Myeloma|Neoplasms|Prognosis|Risk Assessment|Survival Analysis', 'Journal Article', '10.1093/bioinformatics/btt124', '23493321', 'Despite huge prognostic promises, gene expression-based survival assessment is rarely used in clinical routine. Main reasons include difficulties in performing and reporting analyses and restriction in most methods to one high-risk group with the vast majority of patients being unassessed. The present study aims at limiting these difficulties by (i) mathematically defining the number of risk groups without any a priori assumption, (ii) computing the risk of an independent cohort by considering each patient as a new patient incorporated to the validation cohort and (iii) providing an open-access Web site to freely compute risk for every new patient.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77517, 2013, 'bio', 'Peakr: simulating solid-state NMR spectra of proteins', 'Schneider, Robert|Odronitz, Florian|Hammesfahr, Björn|Hellkamp, Marcel|Kollmar, Martin', 'Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany. robert.schneider@ibs.fr|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany. robert.schneider@ibs.fr|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany. robert.schneider@ibs.fr|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany. robert.schneider@ibs.fr|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany. robert.schneider@ibs.fr', 'Germany|Germany|Germany|Germany|Germany', 3, 'Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt125', '23493322', 'When analyzing solid-state nuclear magnetic resonance (NMR) spectra of proteins, assignment of resonances to nuclei and derivation of restraints for 3D structure calculations are challenging and time-consuming processes. Simulated spectra that have been calculated based on, for example, chemical shift predictions and structural models can be of considerable help. Existing solutions are typically limited in the type of experiment they can consider and difficult to adapt to different settings.'),
(77518, 2013, 'bio', 'BRANCH: boosting RNA-Seq assemblies with partial or related genomic sequences', 'Bao, Ergude|Jiang, Tao|Girke, Thomas', 'Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.|Department of Computer Science and Engineering, University of California, Riverside, CA 92521, USA.', 'United States|United States|United States', 0, 'Algorithms|Animals|Caenorhabditis elegans|Genomics|Mice|Molecular Sequence Annotation|Rats|Saccharomyces cerevisiae|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt127', '23493323', 'De novo transcriptome assemblies of RNA-Seq data are important for genomics applications of unsequenced organisms. Owing to the complexity and often incomplete representation of transcripts in sequencing libraries, the assembly of high-quality transcriptomes can be challenging. However, with the rapidly growing number of sequenced genomes, it is now feasible to improve RNA-Seq assemblies by guiding them with genomic sequences.'),
(77519, 2013, 'bio', 'ChemoPy: freely available python package for computational biology and chemoinformatics', 'Cao, Dong-Sheng|Xu, Qing-Song|Hu, Qian-Nan|Liang, Yi-Zeng', 'Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha, P. R. China.|Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha, P. R. China.|Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha, P. R. China.|Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha, P. R. China.', 'China|China|China|China', 77, 'Computational Biology|Databases, Chemical|Drug Design|Ligands|Pharmaceutical Preparations|Software', 'Journal Article', '10.1093/bioinformatics/btt105', '23493324', 'Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently.'),
(77520, 2013, 'bio', 'Brain: biomedical knowledge manipulation', 'Croset, Samuel|Overington, John P|Rebholz-Schuhmann, Dietrich', 'EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. croset@ebi.ac.uk|EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. croset@ebi.ac.uk|EMBL European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. croset@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 6, 'Internet|Knowledge Bases|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btt109', '23505292', 'Brain is a Java software library facilitating the manipulation and creation of ontologies and knowledge bases represented with the Web Ontology Language (OWL).'),
(77521, 2013, 'bio', 'Sorad: a systems biology approach to predict and modulate dynamic signaling pathway response from phosphoproteome time-course measurements', 'xc3x84ijxc3xb6, Tarmo|Granberg, Kirsi|Lxc3xa4hdesmxc3xa4ki, Harri', 'Department of Information and Computer Science, Aalto University, FI-00076 AALTO, Finland. tarmo.aijo@aalto.fi|Department of Information and Computer Science, Aalto University, FI-00076 AALTO, Finland. tarmo.aijo@aalto.fi|Department of Information and Computer Science, Aalto University, FI-00076 AALTO, Finland. tarmo.aijo@aalto.fi', 'Finland|Finland|Finland', 0, 'Carcinoma, Hepatocellular|Cell Line, Tumor|Humans|Liver Neoplasms|Phosphoproteins|Phosphorylation|Proto-Oncogene Proteins c-akt|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt130', '23505293', 'Signaling networks mediate responses to different stimuli using a multitude of feed-forward, feedback and cross-talk mechanisms, and malfunctions in these mechanisms have an important role in various diseases. To understand a disease and to help discover novel therapeutic approaches, we have to reveal the molecular mechanisms underlying signal transduction and use that information to design targeted perturbations.'),
(77522, 2013, 'bio', 'Identification of cancer fusion drivers using network fusion centrality', 'Wu, Chia-Chin|Kannan, Kalpana|Lin, Steven|Yen, Laising|Milosavljevic, Aleksandar', 'Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA. perwu777@gmail.com|Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA. perwu777@gmail.com|Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA. perwu777@gmail.com|Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA. perwu777@gmail.com|Department of Genomic Medicine, UT MD Anderson Cancer Center, Houston, TX 77030, USA. perwu777@gmail.com', 'United States|United States|United States|United States|United States', 17, 'Gene Fusion|Gene Regulatory Networks|Genes, Neoplasm|Humans|Models, Genetic|Mutation|Neoplasms|Oncogene Fusion|Oncogene Proteins, Fusion|Protein Structure, Tertiary', 'Journal Article', '10.1093/bioinformatics/btt131', '23505294', 'Gene fusions are being discovered at an increasing rate using massively parallel sequencing technologies. Prioritization of cancer fusion drivers for validation cannot be performed using traditional single-gene based methods because fusions involve portions of two partner genes. To address this problem, we propose a novel network analysis method called fusion centrality that is specifically tailored for prioritizing gene fusions. We first propose a domain-based fusion model built on the theory of exon/domain shuffling. The model leads to a hypothesis that a fusion is more likely to be an oncogenic driver if its partner genes act like hubs in a network because the fusion mutation can deregulate normal functions of many other genes and their pathways. The hypothesis is supported by the observation that for most known cancer fusion genes, at least one of the fusion partners appears to be a hub in a network, and even for many fusions both partners appear to be hubs. Based on this model, we construct fusion centrality, a multi-gene-based network metric, and use it to score fusion drivers. We show that the fusion centrality outperforms other single gene-based methods. Specifically, the method successfully predicts most of 38 newly discovered fusions that had validated oncogenic importance. To our best knowledge, this is the first network-based approach for identifying fusion drivers.'),
(77523, 2013, 'bio', 'HAL: a hierarchical format for storing and analyzing multiple genome alignments', 'Hickey, Glenn|Paten, Benedict|Earl, Dent|Zerbino, Daniel|Haussler, David', 'Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz CA 95064, USA. hickey@soe.ucsc.edu|Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz CA 95064, USA. hickey@soe.ucsc.edu|Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz CA 95064, USA. hickey@soe.ucsc.edu|Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz CA 95064, USA. hickey@soe.ucsc.edu|Center for Biomolecular Science and Engineering, University of California Santa Cruz, Santa Cruz CA 95064, USA. hickey@soe.ucsc.edu', 'United States|United States|United States|United States|United States', 35, 'Animals|Base Sequence|Evolution, Molecular|Genome|Genomics|Humans|Phylogeny|Programming Languages|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btt128', '23505295', 'Large multiple genome alignments and inferred ancestral genomes are ideal resources for comparative studies of molecular evolution, and advances in sequencing and computing technology are making them increasingly obtainable. These structures can provide a rich understanding of the genetic relationships between all subsets of species they contain. Current formats for storing genomic alignments, such as XMFA and MAF, are all indexed or ordered using a single reference genome, however, which limits the information that can be queried with respect to other species and clades. This loss of information grows with the number of species under comparison, as well as their phylogenetic distance.'),
(77524, 2013, 'bio', 'Programming strategy for efficient modeling of dynamics in a population of heterogeneous cells', 'Hald, Bjørn Olav|Garkier Hendriksen, Morten|Sørensen, Preben Graae', 'Department of Biomedical Sciences, Blegdamsvej 3, 2200 Copenhagen, Denmark. bjornhald@gmail.com|Department of Biomedical Sciences, Blegdamsvej 3, 2200 Copenhagen, Denmark. bjornhald@gmail.com|Department of Biomedical Sciences, Blegdamsvej 3, 2200 Copenhagen, Denmark. bjornhald@gmail.com', 'Denmark|Denmark|Denmark', 7, 'Computer Simulation|Glycolysis|Models, Biological|Programming Languages|Software|Yeasts', 'Journal Article', '10.1093/bioinformatics/btt132', '23505296', 'Heterogeneity is a ubiquitous property of biological systems. Even in a genetically identical population of a single cell type, cell-to-cell differences are observed. Although the functional behavior of a given population is generally robust, the consequences of heterogeneity are fairly unpredictable. In heterogeneous populations, synchronization of events becomes a cardinal problem-particularly for phase coherence in oscillating systems.'),
(77525, 2013, 'bio', 'TfReg: calculating DNA and RNA melting temperatures and opening profiles with mesoscopic models', 'Weber, Gerald', 'Departamento de Física, Universidade Federal Minas Gerais, Belo Horizonte-MG, 31270-901 Brazil. gweberbh@gmail.com', 'Brazil', 11, 'DNA|Genome, Human|Humans|Hydrogen Bonding|Models, Chemical|Models, Statistical|Oligonucleotides|Programming Languages|RNA|Software|Temperature', 'Journal Article', '10.1093/bioinformatics/btt133', '23505297', 'The mesoscopic statistical physics models, known generically as Peyrard-Bishop (PB) models, have found many applications for the study of oligonucleotide properties. Unfortunately, PB models have not reached a wider non-specialized audience for the lack of freely available software implementations. Here we present an extensible C++ implementation of four variants of the PB model, which allows the user to calculate melting temperatures from tested model parameters. Even for a non-specialist, it should be straightforward to change these parameters to reflect different experimental environments or different types of oligonucleotides. For users with some proficiency in C++ programming, it should be feasible to extend the code to other PB models owing to the generic programming implementation adopted for TfReg. Pre-calculated parameters are included that allow the immediate calculation of melting temperatures and thermal equivalence indexes for DNA and RNA.'),
(77526, 2013, 'bio', 'pfsearchV3: a code acceleration and heuristic to search PROSITE profiles', 'Schuepbach, Thierry|Pagni, Marco|Bridge, Alan|Bougueleret, Lydie|Xenarios, Ioannis|Cerutti, Lorenzo', 'Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, Genopode, UNIL-Sorge, 1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 10, 'Algorithms|Databases, Protein|Molecular Sequence Annotation|Protein Structure, Tertiary|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btt129', '23505298', 'The PROSITE resource provides a rich and well annotated source of signatures in the form of generalized profiles that allow protein domain detection and functional annotation. One of the major limiting factors in the application of PROSITE in genome and metagenome annotation pipelines is the time required to search protein sequence databases for putative matches. We describe an improved and optimized implementation of the PROSITE search tool pfsearch that, combined with a newly developed heuristic, addresses this limitation. On a modern x86_64 hyper-threaded quad-core desktop computer, the new pfsearchV3 is two orders of magnitude faster than the original algorithm.'),
(77527, 2013, 'bio', 'PeptideLocator: prediction of bioactive peptides in protein sequences', 'Mooney, Catherine|Haslam, Niall J|Holton, Thérèse A|Pollastri, Gianluca|Shields, Denis C', 'Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland.|Complex and Adaptive Systems Laboratory, University College Dublin, Belfield, Dublin 4, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 34, 'Algorithms|Antimicrobial Cationic Peptides|Artificial Intelligence|Peptides|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btt103', '23505299', 'Peptides play important roles in signalling, regulation and immunity within an organism. Many have successfully been used as therapeutic products often mimicking naturally occurring peptides. Here we present PeptideLocator for the automated prediction of functional peptides in a protein sequence.'),
(77528, 2013, 'bio', 'SRV: an open-source toolbox to accelerate the recovery of metabolic biomarkers and correlations from metabolic phenotyping datasets', 'Navratil, Vincent|Pontoizeau, Clément|Billoir, Elise|Blaise, Benjamin J', 'Centre de RMN à Très Hauts Champs, Institut des sciences analytiques, CNRS/ENS Lyon/UCB Lyon 1, Université de Lyon, 5 rue de la Doua, 69100 Villeurbanne, France.|Centre de RMN à Très Hauts Champs, Institut des sciences analytiques, CNRS/ENS Lyon/UCB Lyon 1, Université de Lyon, 5 rue de la Doua, 69100 Villeurbanne, France.|Centre de RMN à Très Hauts Champs, Institut des sciences analytiques, CNRS/ENS Lyon/UCB Lyon 1, Université de Lyon, 5 rue de la Doua, 69100 Villeurbanne, France.|Centre de RMN à Très Hauts Champs, Institut des sciences analytiques, CNRS/ENS Lyon/UCB Lyon 1, Université de Lyon, 5 rue de la Doua, 69100 Villeurbanne, France.', 'France|France|France|France', 11, 'Algorithms|Biomarkers|Humans|Metabolic Networks and Pathways|Multivariate Analysis|Nuclear Magnetic Resonance, Biomolecular|Software', 'Journal Article', '10.1093/bioinformatics/btt136', '23508967', 'Supervised multivariate statistical analyses are often required to analyze the high-density spectral information in metabolic datasets acquired from complex mixtures in metabolic phenotyping studies. Here we present an implementation of the SRV-Statistical Recoupling of Variables-algorithm as an open-source Matlab and GNU Octave toolbox. SRV allows the identification of similarity between consecutive variables resulting from the high-resolution bucketing. Similar variables are gathered to restore the spectral dependency within the datasets and identify metabolic NMR signals. The correlation and significance of these new NMR variables for a given effect under study can then be measured and represented on a loading plot to allow a visual and efficient identification of candidate biomarkers. Further on, correlations between these candidate biomarkers can be visualized on a two-dimensional pseudospectrum, representing a correlation map, helping to understand the modifications of the underlying metabolic network.'),
(77529, 2013, 'bio', 'CytoHiC: a cytoscape plugin for visual comparison of Hi-C networks', 'Shavit, Yoli|Lio, Pietro', 'Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK. yolisha@gmail.com|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK. yolisha@gmail.com', 'United Kingdom|United Kingdom', 11, 'Chromosomes|Computer Graphics|Genomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt120', '23508968', 'With the introduction of the Hi-C method new and fundamental properties of the nuclear architecture are emerging. The ability to interpret data generated by this method, which aims to capture the physical proximity between and within chromosomes, is crucial for uncovering the three dimensional structure of the nucleus. Providing researchers with tools for interactive visualization of Hi-C data can help in gaining new and important insights. Specifically, visual comparison can pinpoint changes in spatial organization between Hi-C datasets, originating from different cell lines or different species, or normalized by different methods. Here, we present CytoHiC, a Cytsocape plugin, which allow users to view and compare spatial maps of genomic landmarks, based on normalized Hi-C datasets. CytoHiC was developed to support intuitive visual comparison of Hi-C data and integration of additional genomic annotations.'),
(77530, 2013, 'bio', 'CistromeFinder for ChIP-seq and DNase-seq data reuse', 'Sun, Hanfei|Qin, Bo|Liu, Tao|Wang, Qixuan|Liu, Jing|Wang, Juan|Lin, Xueqiu|Yang, Yulin|Taing, Len|Rao, Prakash K|Brown, Myles|Zhang, Yong|Long, Henry W|Liu, X Shirley', 'Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.|Department of Bioinformatics, School of Life Science and Technology, Tongji University, Shanghai 20092, China.', 'China|China|China|China|China|China|China|China|China|China|China|China|China|China', 14, 'Animals|Cell Line|Chromatin Immunoprecipitation|Databases, Genetic|Deoxyribonuclease I|Epigenesis, Genetic|High-Throughput Nucleotide Sequencing|Humans|Information Storage and Retrieval|Mice|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btt135', '23508969', 'Chromatin immunoprecipitation and DNase I hypersensitivity assays with high-throughput sequencing have greatly accelerated the understanding of transcriptional and epigenetic regulation, although data reuse for the community of experimental biologists has been challenging. We created a data portal CistromeFinder that can help query, evaluate and visualize publicly available Chromatin immunoprecipitation and DNase I hypersensitivity assays with high-throughput sequencing data in human and mouse. The database currently contains 6378 samples over 4391 datasets, 313 factors and 102 cell lines or cell populations. Each dataset has gone through a consistent analysis and quality control pipeline, therefore, users could evaluate the overall quality of each dataset before examining binding sites near their genes of interest. CistromeFinder is integrated with UCSC genome browser for visualization, Primer3Plus for ChIP-qPCR primer design and CistromeMap for submitting newly available datasets. It also allows users to leave comments to facilitate data evaluation and update.'),
(77531, 2013, 'bio', 'The Simmune Modeler visual interface for creating signaling networks based on bi-molecular interactions', 'Zhang, Fengkai|Angermann, Bastian R|Meier-Schellersheim, Martin', 'Computational Biology Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA. zhangfen@niaid.nih.gov|Computational Biology Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA. zhangfen@niaid.nih.gov|Computational Biology Unit, Laboratory of Systems Biology, National Institute of Allergy and Infectious Diseases, NIH, Bethesda, MD 20892, USA. zhangfen@niaid.nih.gov', 'United States|United States|United States', 24, 'Binding Sites|Computer Graphics|Models, Biological|Multiprotein Complexes|Receptors, G-Protein-Coupled|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt134', '23508970', 'Biochemical modeling efforts now frequently take advantage of the possibility to automatically create reaction networks based on the specification of pairwise molecular interactions. Even though a variety of tools exist to visualize the resulting networks, defining the rules for the molecular interactions typically requires writing scripts, which impacts the non-specialist accessibility of those approaches. We introduce the Simmune Modeler that allows users to specify molecular complexes and their interactions as well as the reaction-induced modifications of the molecules through a flexible visual interface. It can take into account the positions of the components of trans-membrane complexes relative to the embedding membranes as well as symmetry aspects affecting the reactions of multimeric molecular structures. Models created with this tool can be simulated using the Simmune Simulator or be exported as SBML code or as files describing the reaction networks as systems of ODEs for import into Matlab.'),
(77532, 2013, 'bio', 'Predicting the probability of H3K4me3 occupation at a base pair from the genome sequence context', 'Ha, Misook|Hong, Soondo|Li, Wen-Hsiung', 'Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA. misook.ha@samsung.com|Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA. misook.ha@samsung.com|Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA. misook.ha@samsung.com', 'United States|United States|United States', 5, 'Base Pairing|Binding Sites|Chromatin|Chromatin Assembly and Disassembly|Chromatin Immunoprecipitation|Chromosome Mapping|DNA|Epigenesis, Genetic|Genome, Human|Genomics|Histones|Humans|Methylation|Models, Statistical|Nucleosomes|Regulatory Elements, Transcriptional|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btt126', '23511541', 'Histone modifications regulate chromatin structure and gene expression. Although nucleosome formation is known to be affected by primary DNA sequence composition, no sequence signature has been identified for histone modifications. It is known that dense H3K4me3 nucleosome sites are accompanied by a low density of other nucleosomes and are associated with gene activation. This observation suggests a different sequence composition of H3K4me3 from other nucleosomes.'),
(77533, 2013, 'bio', 'FunFrame: functional gene ecological analysis pipeline', 'Weisman, David|Yasuda, Michie|Bowen, Jennifer L', 'Department of Biology, University of Massachusetts Boston, Boston, MA 02125, USA.|Department of Biology, University of Massachusetts Boston, Boston, MA 02125, USA.|Department of Biology, University of Massachusetts Boston, Boston, MA 02125, USA.', 'United States|United States|United States', 9, 'Algorithms|Metagenomics|Proteins|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt123', '23511542', 'Pyrosequencing of 16S rDNA is widely used to study microbial communities, and a rich set of software tools support this analysis. Pyrosequencing of protein-coding genes, which can help elucidate functional differences among microbial communities, significantly lags behind 16S rDNA in availability of sequence analysis software. In both settings, frequent homopolymer read errors inflate the estimation of microbial diversity, and de-noising is required to reduce that bias. Here we describe FunFrame, an R-based data-analysis pipeline that uses recently described algorithms to de-noise functional gene pyrosequences and performs ecological analysis on de-noised sequence data. The novelty of this pipeline is that it provides users a unified set of tools, adapted from disparate sources and designed for different applications, that can be used to examine a particular protein coding gene of interest. We evaluated FunFrame on functional genes from four PCR-amplified clones with sequence depths ranging from 9084 to 14 494 sequences. FunFrame produced from one to nine Operational Taxanomic Units for each clone, resulting in an error rate ranging from 0 to 0.18%. Importantly, FunFrame reduced spurious diversity while retaining more sequences than a commonly used de-noising method that discards sequences with frameshift errors.'),
(77534, 2013, 'bio', 'Parametric Bayesian priors and better choice of negative examples improve protein function prediction', 'Youngs, Noah|Penfold-Brown, Duncan|Drew, Kevin|Shasha, Dennis|Bonneau, Richard', 'Department of Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA.|Department of Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA.|Department of Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA.|Department of Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA.|Department of Computer Science, Center for Genomics and Systems Biology, New York University, New York, NY 10003, USA.', 'United States|United States|United States|United States|United States', 22, 'Algorithms|Animals|Artificial Intelligence|Bayes Theorem|Gene Regulatory Networks|Genome|Mice|Molecular Sequence Annotation|Protein Interaction Mapping|Proteins|Proteome|Yeasts', 'Journal Article', '10.1093/bioinformatics/btt110', '23511543', 'Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key parameters. The improper choice of negative examples, in particular, can hamper the accuracy of protein function prediction.'),
(77535, 2013, 'bio', 'PHISTO: pathogen-host interaction search tool', 'Durmuxc5x9f Tekir, Saliha|xc3x87akxc4xb1r, Tunahan|Ardixc3xa7, Emre|Sayxc4xb1lxc4xb1rbaxc5x9f, Ali Semih|Konuk, Gxc3xb6khan|Konuk, Mithat|Sarxc4xb1yer, Hasret|Uxc4x9furlu, Azat|Karadeniz, xc4xb0lknur|xc3x96zgxc3xbcr, Arzucan|Sevilgen, Fatih Erdoxc4x9fan|xc3x9clgen, Kutlu xc3x96', 'Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr|Department of Chemical Engineering, Boxc4x9fazixc3xa7i University, 34342 Bebek, Sarxc4xb1yer, xc4xb0stanbul, Turkey. saliha.durmus@boun.edu.tr', 'Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey', 60, 'Communicable Diseases|Data Mining|Databases, Protein|Host-Pathogen Interactions|Humans|Internet|Protein Interaction Domains and Motifs|Search Engine', 'Journal Article', '10.1093/bioinformatics/btt137', '23515528', 'Knowledge of pathogen-host protein interactions is required to better understand infection mechanisms. The pathogen-host interaction search tool (PHISTO) is a web-accessible platform that provides relevant information about pathogen-host interactions (PHIs). It enables access to the most up-to-date PHI data for all pathogen types for which experimentally verified protein interactions with human are available. The platform also offers integrated tools for visualization of PHI networks, graph-theoretical analysis of targeted human proteins, BLAST search and text mining for detecting missing experimental methods. PHISTO will facilitate PHI studies that provide potential therapeutic targets for infectious diseases.'),
(77536, 2013, 'bio', 'Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks', 'Greenfield, Alex|Hafemeister, Christoph|Bonneau, Richard', 'Computational Biology Program, New York University Sackler School of Medicine, New York, NY 10065, USA.|Computational Biology Program, New York University Sackler School of Medicine, New York, NY 10065, USA.|Computational Biology Program, New York University Sackler School of Medicine, New York, NY 10065, USA.', 'United States|United States|United States', 74, 'Algorithms|Bacillus subtilis|Bayes Theorem|Escherichia coli|Gene Expression|Gene Regulatory Networks|Models, Genetic|Regression Analysis|Systems Biology|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt099', '23525069', 'Inferring global regulatory networks (GRNs) from genome-wide data is a computational challenge central to the field of systems biology. Although the primary data currently used to infer GRNs consist of gene expression and proteomics measurements, there is a growing abundance of alternate data types that can reveal regulatory interactions, e.g. ChIP-Chip, literature-derived interactions, protein-protein interactions. GRN inference requires the development of integrative methods capable of using these alternate data as priors on the GRN structure. Each source of structure priors has its unique biases and inherent potential errors, thus, GRN methods using these data must be robust to noisy inputs.'),
(77537, 2013, 'bio', 'Improved ancestry inference using weights from external reference panels', 'Chen, Chia-Yen|Pollack, Samuela|Hunter, David J|Hirschhorn, Joel N|Kraft, Peter|Price, Alkes L', 'Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu|Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu|Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu|Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu|Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu|Department of Epidemiology, Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA. cychen@mail.harvard.edu', 'United States|United States|United States|United States|United States|United States', 41, 'African Americans|Continental Population Groups|European Continental Ancestry Group|Genome-Wide Association Study|Genotype|HapMap Project|Humans|Polymorphism, Single Nucleotide|Principal Component Analysis|Software|United States', 'Journal Article', '10.1093/bioinformatics/btt144', '23539302', 'Inference of ancestry using genetic data is motivated by applications in genetic association studies, population genetics and personal genomics. Here, we provide methods and software for improved ancestry inference using genome-wide single nucleotide polymorphism (SNP) weights from external reference panels. This approach makes it possible to leverage the rich ancestry information that is available from large external reference panels, without the administrative and computational complexities of re-analyzing the raw genotype data from the reference panel in subsequent studies.'),
(77538, 2013, 'bio', 'An accessible database for mouse and human whole transcriptome qPCR primers', 'Zeisel, Amit|Yitzhaky, Assif|Bossel Ben-Moshe, Noa|Domany, Eytan', 'Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. amit.zeisel@weizmann.ac.il|Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. amit.zeisel@weizmann.ac.il|Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. amit.zeisel@weizmann.ac.il|Department of Physics of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. amit.zeisel@weizmann.ac.il', 'Israel|Israel|Israel|Israel', 13, 'Animals|DNA Primers|Databases, Genetic|Exons|Humans|Introns|Mice|Real-Time Polymerase Chain Reaction|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt145', '23539303', 'Real time quantitative polymerase chain reaction (qPCR) is an important tool in quantitative studies of DNA and RNA molecules, especially in transcriptome studies, where different primer combinations allow identification of specific transcripts such as splice variants or precursor messenger RNA. Several softwares that implement various rules for optimal primer design are available. Nevertheless, as designing qPCR primers needs to be done manually, the repeated task is tedious, time consuming and prone to errors.'),
(77539, 2013, 'bio', 'Density-based hierarchical clustering of pyro-sequences on a large scale--the case of fungal ITS1', 'Pagni, Marco|Niculita-Hirzel, Hélène|Pellissier, Loïc|Dubuis, Anne|Xenarios, Ioannis|Guisan, Antoine|Sanders, Ian R|Goudet, Jérôme|Guex, Nicolas', 'Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.|Vital-IT Group, SIB Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 10, 'Algorithms|Cluster Analysis|DNA, Fungal|DNA, Ribosomal Spacer|Fungi|Reproducibility of Results|Soil Microbiology', 'Journal Article', '10.1093/bioinformatics/btt149', '23539304', 'Analysis of millions of pyro-sequences is currently playing a crucial role in the advance of environmental microbiology. Taxonomy-independent, i.e. unsupervised, clustering of these sequences is essential for the definition of Operational Taxonomic Units. For this application, reproducibility and robustness should be the most sought after qualities, but have thus far largely been overlooked.'),
(77540, 2013, 'bio', 'MCScanX-transposed: detecting transposed gene duplications based on multiple colinearity scans', 'Wang, Yupeng|Li, Jingping|Paterson, Andrew H', 'Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA. wyp1125@gmail.com|Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA. wyp1125@gmail.com|Plant Genome Mapping Laboratory, University of Georgia, Athens, GA 30602, USA. wyp1125@gmail.com', 'Georgia|Georgia|Georgia', 27, 'Algorithms|Evolution, Molecular|Gene Duplication|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btt150', '23539305', 'Gene duplication occurs via different modes such as segmental and single-gene duplications. Transposed gene duplication, a specific form of single-gene duplication, copies a gene from an ancestral chromosomal location to a novel location. MCScanX is a toolkit for detection and evolutionary analysis of gene colinearity. We have developed MCScanX-transposed, a software package to detect transposed gene duplications that occurred within different epochs, based on execution of MCScanX within and between related genomes. MCScanX-transposed can be also used for integrative analysis of gene duplication modes for a genome and to annotate a gene family of interest with gene duplication modes.'),
(77541, 2013, 'bio', 'FishingCNV: a graphical software package for detecting rare copy number variations in exome-sequencing data', 'Shi, Yuhao|Majewski, Jacek', 'Department of Human Genetics, McGill University, Montreal, Quebec, Canada. yuhao.shi@mail.mcgill.ca|Department of Human Genetics, McGill University, Montreal, Quebec, Canada. yuhao.shi@mail.mcgill.ca', 'Canada|Canada', 30, 'Algorithms|Computer Graphics|DNA Copy Number Variations|Exome|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt151', '23539306', 'Rare copy number variations (CNVs) are frequent causes of genetic diseases. We developed a graphical software package based on a novel approach that can consistently identify CNVs of all types (homozygous deletions, heterozygous deletions, heterozygous duplications) from exome-sequencing data without the need of a paired control. The algorithm compares coverage depth in a test sample against a background distribution of control samples and uses principal component analysis to remove batch effects. It is user friendly and can be run on a personal computer.'),
(77542, 2013, 'bio', 'Enabling interspecies epigenomic comparison with CEpBrowser', 'Cao, Xiaoyi|Zhong, Sheng', 'Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States', 0, 'Animals|Epigenomics|High-Throughput Nucleotide Sequencing|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btt114', '23543396', 'We developed the Comparative Epigenome Browser (CEpBrowser) to allow the public to perform multi-species epigenomic analysis. The web-based CEpBrowser integrates, manages and visualizes sequencing-based epigenomic datasets. Five key features were developed to maximize the efficiency of interspecies epigenomic comparisons.'),
(77543, 2013, 'bio', 'Fast simulation of reconstructed phylogenies under global time-dependent birth-death processes', 'Höhna, Sebastian', 'Department of Mathematics, Stockholm University, Kräftriket Hus 6, Stockholm, Sweden. hoehna@math.su.se', 'Sweden', 34, 'Algorithms|Biological Evolution|Computer Simulation|Extinction, Biological|Genetic Speciation|Genetic Variation|Models, Biological|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btt153', '23543414', 'Diversification rates and patterns may be inferred from reconstructed phylogenies. Both the time-dependent and the diversity-dependent birth-death process can produce the same observed patterns of diversity over time. To develop and test new models describing the macro-evolutionary process of diversification, generic and fast algorithms to simulate under these models are necessary. Simulations are not only important for testing and developing models but play an influential role in the assessment of model fit.'),
(77544, 2013, 'bio', 'PathVisio-Faceted Search: an exploration tool for multi-dimensional navigation of large pathways', 'Fried, Jake Y|van Iersel, Martijn P|Aladjem, Mirit I|Kohn, Kurt W|Luna, Augustin', 'Computer Engineering, University of Maryland, College Park, MD 20740, USA. jakeyfried@gmail.com|Computer Engineering, University of Maryland, College Park, MD 20740, USA. jakeyfried@gmail.com|Computer Engineering, University of Maryland, College Park, MD 20740, USA. jakeyfried@gmail.com|Computer Engineering, University of Maryland, College Park, MD 20740, USA. jakeyfried@gmail.com|Computer Engineering, University of Maryland, College Park, MD 20740, USA. jakeyfried@gmail.com', 'United States|United States|United States|United States|United States', 4, 'Genes|Humans|Lymphoma|Models, Biological|Proteins|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt146', '23547033', 'The PathVisio-Faceted Search plugin helps users explore and understand complex pathways by overlaying experimental data and data from webservices, such as Ensembl BioMart, onto diagrams drawn using formalized notations in PathVisio. The plugin then provides a filtering mechanism, known as a faceted search, to find and highlight diagram nodes (e.g. genes and proteins) of interest based on imported data. The tool additionally provides a flexible scripting mechanism to handle complex queries.'),
(77545, 2013, 'bio', 'Bayesian hierarchical model of protein-binding microarray k-mer data reduces noise and identifies transcription factor subclasses and preferred k-mers', 'Jiang, Bo|Liu, Jun S|Bulyk, Martha L', 'Department of Statistics, Harvard University, Cambridge, MA 02138, USA. bojiang83@gmail.com|Department of Statistics, Harvard University, Cambridge, MA 02138, USA. bojiang83@gmail.com|Department of Statistics, Harvard University, Cambridge, MA 02138, USA. bojiang83@gmail.com', 'United States|United States|United States', 0, 'Analysis of Variance|Artifacts|Bayes Theorem|Binding Sites|Chromatin Immunoprecipitation|DNA-Binding Proteins|Oligonucleotide Array Sequence Analysis|Regulatory Elements, Transcriptional|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt152', '23559638', 'Sequence-specific transcription factors (TFs) regulate the expression of their target genes through interactions with specific DNA-binding sites in the genome. Data on TF-DNA binding specificities are essential for understanding how regulatory specificity is achieved.'),
(77546, 2013, 'bio', 'A tool for RNA sequencing sample identity check', 'Huang, Jinyan|Chen, Jun|Lathrop, Mark|Liang, Liming', 'School of life science, Tongji University, Shanghai, China.|School of life science, Tongji University, Shanghai, China.|School of life science, Tongji University, Shanghai, China.|School of life science, Tongji University, Shanghai, China.', 'China|China|China|China', 0, 'Gene Expression Profiling|Genotype|Likelihood Functions|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt155', '23559639', 'RNA sequencing data are becoming a major method of choice to study transcriptomes, including the mapping of gene expression quantitative trait loci (eQTLs). RNA sample contamination or swapping is a serious problem for downstream analysis and may result in false discovery and lose power to detect the true biological relationships. When genetic data are available, for example, in eQTL studies or samples have been previously genotyped or DNA sequenced, it is possible to combine genetic data and RNA-seq data to detect sample contamination and resolve sample swapping problems. In this article, we introduce a tool (IDCheck) that allows easy assessment of concordance between genotype (from SNP arrays or DNA sequencing) and gene expression (RNA-seq) samples. IDCheck compares the identity of RNA-seq reads and SNP genotypes using a likelihood-based method. Based on maximum likelihood estimates of relevant parameters, we can detect sample contamination and identify correct sample pairs when swapping occurs. Our tool provides an efficient and convenient way to evaluate and resolve these problems.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77547, 2013, 'bio', 'Detecting regulatory gene-environment interactions with unmeasured environmental factors', 'Fusi, Nicoló|Lippert, Christoph|Borgwardt, Karsten|Lawrence, Neil D|Stegle, Oliver', 'Department of Computer Science, University of Sheffield, Sheffield, UK. nicolo.fusi@sheffield.ac.uk|Department of Computer Science, University of Sheffield, Sheffield, UK. nicolo.fusi@sheffield.ac.uk|Department of Computer Science, University of Sheffield, Sheffield, UK. nicolo.fusi@sheffield.ac.uk|Department of Computer Science, University of Sheffield, Sheffield, UK. nicolo.fusi@sheffield.ac.uk|Department of Computer Science, University of Sheffield, Sheffield, UK. nicolo.fusi@sheffield.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Fungal|Gene-Environment Interaction|Genotype|Humans|Linear Models|Models, Genetic|Quantitative Trait Loci', 'Journal Article', '10.1093/bioinformatics/btt148', '23559640', 'Genomic studies have revealed a substantial heritable component of the transcriptional state of the cell. To fully understand the genetic regulation of gene expression variability, it is important to study the effect of genotype in the context of external factors such as alternative environmental conditions. In model systems, explicit environmental perturbations have been considered for this purpose, allowing to directly test for environment-specific genetic effects. However, such experiments are limited to species that can be profiled in controlled environments, hampering their use in important systems such as human. Moreover, even in seemingly tightly regulated experimental conditions, subtle environmental perturbations cannot be ruled out, and hence unknown environmental influences are frequent. Here, we propose a model-based approach to simultaneously infer unmeasured environmental factors from gene expression profiles and use them in genetic analyses, identifying environment-specific associations between polymorphic loci and individual gene expression traits.'),
(77548, 2013, 'bio', 'tmVar: a text mining approach for extracting sequence variants in biomedical literature', 'Wei, Chih-Hsuan|Harris, Bethany R|Kao, Hung-Yu|Lu, Zhiyong', 'National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), 8600 Rockville Pike, Bethesda, MD 20894, USA.|National Center for Biotechnology Information (NCBI), National Library of Medicine (NLM), 8600 Rockville Pike, Bethesda, MD 20894, USA.', 'United States|United States|United States|United States', 0, 'Artificial Intelligence|DNA Mutational Analysis|Data Mining|Humans|Mutation|Software', 'Evaluation Studies', '10.1093/bioinformatics/btt156', '23564842', 'Text-mining mutation information from the literature becomes a critical part of the bioinformatics approach for the analysis and interpretation of sequence variations in complex diseases in the post-genomic era. It has also been used for assisting the creation of disease-related mutation databases. Most of existing approaches are rule-based and focus on limited types of sequence variations, such as protein point mutations. Thus, extending their extraction scope requires significant manual efforts in examining new instances and developing corresponding rules. As such, new automatic approaches are greatly needed for extracting different kinds of mutations with high accuracy.'),
(77549, 2013, 'bio', 'LibSBMLSim: a reference implementation of fully functional SBML simulator', 'Takizawa, Hiromu|Nakamura, Kazushige|Tabira, Akito|Chikahara, Yoichi|Matsui, Tatsuhiro|Hiroi, Noriko|Funahashi, Akira', 'Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kouhoku-ku, Yokohama, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 10, 'Computer Simulation|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt157', '23564843', 'The Systems Biology Markup Language (SBML) is currently supported by >230 software tools, among which 160 support numerical integration of ordinary differential equation (ODE) models. Although SBML is a widely accepted standard within this field, there is still no language-neutral library that supports all features of SBML for simulating ODE models. Therefore, a demand exists for a simple portable implementation of a numerical integrator that supports SBML to enhance the development of a computational platform for systems biology.'),
(77550, 2013, 'bio', 'Active learning-based information structure analysis of full scientific articles and two applications for biomedical literature review', 'Guo, Yufan|Silins, Ilona|Stenius, Ulla|Korhonen, Anna', 'Computer Laboratory, University of Cambridge, Cambridge, UK. yg244@cam.ac.uk|Computer Laboratory, University of Cambridge, Cambridge, UK. yg244@cam.ac.uk|Computer Laboratory, University of Cambridge, Cambridge, UK. yg244@cam.ac.uk|Computer Laboratory, University of Cambridge, Cambridge, UK. yg244@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Artificial Intelligence|Data Mining|Periodicals as Topic|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btt163', '23564844', 'Techniques that are capable of automatically analyzing the information structure of scientific articles could be highly useful for improving information access to biomedical literature. However, most existing approaches rely on supervised machine learning (ML) and substantial labeled data that are expensive to develop and apply to different sub-fields of biomedicine. Recent research shows that minimal supervision is sufficient for fairly accurate information structure analysis of biomedical abstracts. However, is it realistic for full articles given their high linguistic and informational complexity? We introduce and release a novel corpus of 50 biomedical articles annotated according to the Argumentative Zoning (AZ) scheme, and investigate active learning with one of the most widely used ML models-Support Vector Machines (SVM)-on this corpus. Additionally, we introduce two novel applications that use AZ to support real-life literature review in biomedicine via question answering and summarization.'),
(77551, 2013, 'bio', 'Network predicting drugs anatomical therapeutic chemical code', 'Wang, Yong-Cui|Chen, Shi-Long|Deng, Nai-Yang|Wang, Yong', 'Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China.|Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China.|Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China.|Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China.', 'China|China|China|China', 30, 'Algorithms|Databases, Pharmaceutical|Drug Delivery Systems|Pharmaceutical Preparations|Software', 'Journal Article', '10.1093/bioinformatics/btt158', '23564845', 'Discovering drugs Anatomical Therapeutic Chemical (ATC) classification rules at molecular level is of vital importance to understand a vast majority of drugs action. However, few studies attempt to annotate drugs potential ATC-codes by computational approaches.'),
(77552, 2013, 'bio', 'MonaLisa--visualization and analysis of functional modules in biochemical networks', 'Einloft, Jens|Ackermann, Jörg|Nöthen, Joachim|Koch, Ina', 'Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Robert-Mayer-Strasse 11-15, Frankfurt am Main, Germany.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Robert-Mayer-Strasse 11-15, Frankfurt am Main, Germany.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Robert-Mayer-Strasse 11-15, Frankfurt am Main, Germany.|Molecular Bioinformatics Group, Institute of Computer Science, Faculty of Computer Science and Mathematics, Cluster of Excellence Frankfurt Macromolecular Complexes, Robert-Mayer-Strasse 11-15, Frankfurt am Main, Germany.', 'Germany|Germany|Germany|Germany', 18, 'Biochemical Phenomena|Computer Graphics|Software', 'Journal Article', '10.1093/bioinformatics/btt165', '23564846', 'Structural modeling of biochemical networks enables qualitative as well as quantitative analysis of those networks. Automated network decomposition into functional modules is a crucial point in network analysis. Although there exist approaches for the analysis of networks, there is no open source tool available that combines editing, visualization and the computation of steady-state functional modules. We introduce a new tool called MonaLisa, which combines computation and visualization of functional modules as well as an editor for biochemical Petri nets. The analysis techniques allow for network decomposition into functional modules, for example t-invariants (elementary modes), maximal common transition sets, minimal cut sets and t-clusters. The graphical user interface provides various functionalities to construct and modify networks as well as to visualize the results of the analysis.'),
(77553, 2013, 'bio', 'Analysis of Latino populations from GALA and MEC studies reveals genomic loci with biased local ancestry estimation', 'Pasaniuc, Bogdan|Sankararaman, Sriram|Torgerson, Dara G|Gignoux, Christopher|Zaitlen, Noah|Eng, Celeste|Rodriguez-Cintron, William|Chapela, Rocio|Ford, Jean G|Avila, Pedro C|Rodriguez-Santana, Jose|Chen, Gary K|Le Marchand, Loic|Henderson, Brian|Reich, David|Haiman, Christopher A|Gonzàlez Burchard, Esteban|Halperin, Eran', 'Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399|Department of Pathology and Molecular Medicine, Geffen School of Medicine, University of California-Los Angeles, CA 10833, USA. R01 HG006399', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 24, 'Bias|Cohort Studies|Family|Genetic Loci|Genetics, Population|Genome, Human|Genome-Wide Association Study|Genotype|Haplotypes|Hispanic Americans|Humans|Mexican Americans|Puerto Rico|United States', 'Journal Article', '10.1093/bioinformatics/btt166', '23572411', 'Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging.'),
(77554, 2013, 'bio', 'Measuring gene functional similarity based on group-wise comparison of GO terms', 'Teng, Zhixia|Guo, Maozu|Liu, Xiaoyan|Dai, Qiguo|Wang, Chunyu|Xuan, Ping', 'Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.|Department of Computer Science and Engineering, Harbin Institute of Technology, Harbin, P.R. China.', 'China|China|China|China|China|China', 65, 'Algorithms|Computational Biology|Genes|Molecular Sequence Annotation|Proteins|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btt160', '23572412', 'Compared with sequence and structure similarity, functional similarity is more informative for understanding the biological roles and functions of genes. Many important applications in computational molecular biology require functional similarity, such as gene clustering, protein function prediction, protein interaction evaluation and disease gene prioritization. Gene Ontology (GO) is now widely used as the basis for measuring gene functional similarity. Some existing methods combined semantic similarity scores of single term pairs to estimate gene functional similarity, whereas others compared terms in groups to measure it. However, these methods may make error-prone judgments about gene functional similarity. It remains a challenge that measuring gene functional similarity reliably.'),
(77555, 2013, 'bio', 'OKVAR-Boost: a novel boosting algorithm to infer nonlinear dynamics and interactions in gene regulatory networks', 'Lim, Néhémy|Senbabaoglu, Yasin|Michailidis, George|dAlché-Buc, Florence', 'IBISC EA 4526, Université dÉvry-Val dEssonne, Évry, France.|IBISC EA 4526, Université dÉvry-Val dEssonne, Évry, France.|IBISC EA 4526, Université dÉvry-Val dEssonne, Évry, France.|IBISC EA 4526, Université dÉvry-Val dEssonne, Évry, France.', 'France|France|France|France', 0, 'Algorithms|Computer Simulation|Gene Regulatory Networks|Models, Genetic|Nonlinear Dynamics|T-Lymphocytes', 'Journal Article', '10.1093/bioinformatics/btt167', '23574736', 'Reverse engineering of gene regulatory networks remains a central challenge in computational systems biology, despite recent advances facilitated by benchmark in silico challenges that have aided in calibrating their performance. A number of approaches using either perturbation (knock-out) or wild-type time-series data have appeared in the literature addressing this problem, with the latter using linear temporal models. Nonlinear dynamical models are particularly appropriate for this inference task, given the generation mechanism of the time-series data. In this study, we introduce a novel nonlinear autoregressive model based on operator-valued kernels that simultaneously learns the model parameters, as well as the network structure.'),
(77556, 2013, 'bio', 'Biographer: web-based editing and rendering of SBGN compliant biochemical networks', 'Krause, Falko|Schulz, Marvin|Ripkens, Ben|Flöttmann, Max|Krantz, Marcus|Klipp, Edda|Handorf, Thomas', 'Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.|Theoretical Biophysics, Humboldt-Universität zu Berlin, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Biochemical Phenomena|Internet|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt159', '23574737', 'The rapid accumulation of knowledge in the field of Systems Biology during the past years requires advanced, but simple-to-use, methods for the visualization of information in a structured and easily comprehensible manner.'),
(77557, 2013, 'bio', 'DP2: Distributed 3D image segmentation using micro-labor workforce', 'Giuly, Richard J|Kim, Keun-Young|Ellisman, Mark H', 'National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA. rgiuly@ucsd.edu|National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA. rgiuly@ucsd.edu|National Center for Microscopy and Imaging Research, Center for Research in Biological Systems, Department of Neurosciences, University of California, San Diego, La Jolla, CA 92093, USA. rgiuly@ucsd.edu', 'United States|United States|United States', 0, 'Axons|Imaging, Three-Dimensional|Microscopy|Myelin Sheath|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/btt154', '23574738', 'This application note describes a new scalable semi-automatic approach, the Dual Point Decision Process, for segmentation of 3D structures contained in 3D microscopy. The segmentation problem is distributed to many individual workers such that each receives only simple questions regarding whether two points in an image are placed on the same object. A large pool of micro-labor workers available through Amazons Mechanical Turk system provides the labor in a scalable manner.'),
(77558, 2013, 'bio', 'Analyzing genome coverage profiles with applications to quality control in metagenomics', 'Lindner, Martin S|Kollock, Maximilian|Zickmann, Franziska|Renard, Bernhard Y', 'Research Group Bioinformatics NG4, Robert Koch-Institut, 13353 Berlin, Germany.|Research Group Bioinformatics NG4, Robert Koch-Institut, 13353 Berlin, Germany.|Research Group Bioinformatics NG4, Robert Koch-Institut, 13353 Berlin, Germany.|Research Group Bioinformatics NG4, Robert Koch-Institut, 13353 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Bacteria|Gastrointestinal Tract|Genome|Genome, Bacterial|Humans|Metagenomics|Probability|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btt147', '23589648', 'Genome coverage, the number of sequencing reads mapped to a position in a genome, is an insightful indicator of irregularities within sequencing experiments. While the average genome coverage is frequently used within algorithms in computational genomics, the complete information available in coverage profiles (i.e. histograms over all coverages) is currently not exploited to its full extent. Thus, biases such as fragmented or erroneous reference genomes often remain unaccounted for. Making this information accessible can improve the quality of sequencing experiments and quantitative analyses.'),
(77559, 2013, 'bio', 'Exome-based analysis for RNA epigenome sequencing data', 'Meng, Jia|Cui, Xiaodong|Rao, Manjeet K|Chen, Yidong|Huang, Yufei', 'Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu|Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu|Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu|Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu|Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology, Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, MA 02139, USA. jmeng@mit.edu', 'United States|United States|United States|United States|United States', 50, 'Epigenesis, Genetic|Exome|HEK293 Cells|Humans|Immunoprecipitation|RNA Processing, Post-Transcriptional|Sequence Analysis, RNA|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt171', '23589649', 'Fragmented RNA immunoprecipitation combined with RNA sequencing enabled the unbiased study of RNA epigenome at a near single-base resolution, however, unique features of this new type of data call for novel computational techniques.'),
(77560, 2013, 'bio', 'Shrinkage estimation of dispersion in Negative Binomial models for RNA-seq experiments with small sample size', 'Yu, Danni|Huber, Wolfgang|Vitek, Olga', 'Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.', 'Germany|Germany|Germany', 0, 'Binomial Distribution|Models, Statistical|Probability|RNA|Sample Size|Sequence Analysis, RNA|Transcriptome', 'Journal Article', '10.1093/bioinformatics/btt143', '23589650', 'RNA-seq experiments produce digital counts of reads that are affected by both biological and technical variation. To distinguish the systematic changes in expression between conditions from noise, the counts are frequently modeled by the Negative Binomial distribution. However, in experiments with small sample size, the per-gene estimates of the dispersion parameter are unreliable.'),
(77561, 2013, 'bio', 'Novel algorithms and the benefits of comparative validation', 'Smith, Robert|Ventura, Dan|Prince, John T', 'Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.|Genome Biology Unit, European Molecular Biology Laboratory, Mayerhofstraxc3x9fe 1, Heidelberg 69117, Germany.', 'Germany|Germany|Germany', 19, 'Algorithms|Periodicals as Topic|Reproducibility of Results', 'Letter', '10.1093/bioinformatics/btt176', '23589651', '-'),
(77562, 2013, 'bio', 'UPDtool: a tool for detection of iso- and heterodisomy in parent-child trios using SNP microarrays', 'Schroeder, Christopher|Sturm, Marc|Dufke, Andreas|Mau-Holzmann, Ulrike|Eggermann, Thomas|Poths, Sven|Riess, Olaf|Bonin, Michael', 'Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de|Department of Medical Genetics, University of Tübingen, Calwerstr. 7, 72076 Tübingen, Germany. christopher.schroeder@med.uni-tuebingen.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 17, 'Algorithms|Child|Humans|Microsatellite Repeats|Oligonucleotide Array Sequence Analysis|Parents|Polymorphism, Single Nucleotide|Software|Uniparental Disomy', 'Journal Article', '10.1093/bioinformatics/btt174', '23589652', 'UPDtool is a computational tool for detection and classification of uniparental disomy (UPD) in trio SNP-microarray experiments. UPDs are rare events of chromosomal malsegregation and describe the condition of two homologous chromosomes or homologous chromosomal segments that were inherited from one parent. The occurrence of UPD can be of major clinical relevance. Though high-throughput molecular screening techniques are widely used, detection of UPDs and especially the subclassification remains complex. We developed UPDtool to detect and classify UPDs from SNP microarray data of parent-child trios. The algorithm was tested using five positive controls including both iso- and heterodisomic segmental UPDs and 30 trios from the HapMap project as negative controls. With UPDtool, we were able to correctly identify all occurrences of non-mosaic UPD within our positive controls, whereas no occurrence of UPD was found within our negative controls. In addition, the chromosomal breakage points could be determined more precisely than by microsatellite analysis. Our results were compared with both the gold standard, microsatellite analysis and SNPtrio, another program available for UPD detection. UPDtool is platform independent, light weight and flexible. Because of its simple input format, UPDtool may also be used with other high-throughput technologies (e.g., next-generation sequencing).'),
(77563, 2013, 'bio', 'Learning gene network structure from time laps cell imaging in RNAi Knock downs', 'Failmezger, Henrik|Praveen, Paurush|Tresch, Achim|Fröhlich, Holger', 'Computational Biology and Regulatory Networks, Max-Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Cologne, Germany.|Computational Biology and Regulatory Networks, Max-Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Cologne, Germany.|Computational Biology and Regulatory Networks, Max-Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Cologne, Germany.|Computational Biology and Regulatory Networks, Max-Planck Institute for Plant Breeding Research, Carl-von-Linne-Weg 10, 50829 Cologne, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Cell Cycle|Gene Knockdown Techniques|Gene Regulatory Networks|Markov Chains|Microscopy|Monte Carlo Method|RNA Interference|Time-Lapse Imaging', 'Journal Article', '10.1093/bioinformatics/btt179', '23595660', 'As RNA interference is becoming a standard method for targeted gene perturbation, computational approaches to reverse engineer parts of biological networks based on measurable effects of RNAi become increasingly relevant. The vast majority of these methods use gene expression data, but little attention has been paid so far to other data types.'),
(77564, 2013, 'bio', 'NetworkPrioritizer: a versatile tool for network-based prioritization of candidate disease genes or other molecules', 'Kacprowski, Tim|Doncheva, Nadezhda T|Albrecht, Mario', 'Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Saarbrücken, Germany.', 'Germany|Germany|Germany', 28, 'Disease|Genes|Humans|Inflammatory Bowel Diseases|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt164', '23595661', 'The prioritization of candidate disease genes is often based on integrated datasets and their network representation with genes as nodes connected by edges for biological relationships. However, the majority of prioritization methods does not allow for a straightforward integration of the users own input data. Therefore, we developed the Cytoscape plugin NetworkPrioritizer that particularly supports the integrative network-based prioritization of candidate disease genes or other molecules. Our versatile software tool computes a number of important centrality measures to rank nodes based on their relevance for network connectivity and provides different methods to aggregate and compare rankings.'),
(77565, 2013, 'bio', 'A self-updating road map of The Cancer Genome Atlas', 'Robbins, David E|Grüneberg, Alexander|Deus, Helena F|Tanik, Murat M|Almeida, Jonas S', 'Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233-7331, USA. robbinsd@uab.edu|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233-7331, USA. robbinsd@uab.edu|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233-7331, USA. robbinsd@uab.edu|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233-7331, USA. robbinsd@uab.edu|Division of Informatics, Department of Pathology, University of Alabama at Birmingham, Birmingham, AL 35233-7331, USA. robbinsd@uab.edu', 'United States|United States|United States|United States|United States', 0, 'Genome, Human|Humans|Information Storage and Retrieval|Internet|Neoplasms|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btt141', '23595662', 'Since 2011, The Cancer Genome Atlas (TCGA) files have been accessible through HTTP from a public site, creating entirely new possibilities for cancer informatics by enhancing data discovery and retrieval. Significantly, these enhancements enable the reporting of analysis results that can be fully traced to and reproduced using their source data. However, to realize this possibility, a continually updated road map of files in the TCGA is required. Creation of such a road map represents a significant data modeling challenge, due to the size and fluidity of this resource: each of the 33 cancer types is instantiated in only partially overlapping sets of analytical platforms, while the number of data files available doubles approximately every 7 months.'),
(77566, 2013, 'bio', 'EPSILON: an eQTL prioritization framework using similarity measures derived from local networks', 'Verbeke, Lieven P C|Cloots, Lore|Demeester, Piet|Fostier, Jan|Marchal, Kathleen', 'Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be|Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be|Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be|Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be|Department of Information Technology, Ghent University - iMinds, 9050 Gent, Belgium. lieven.verbeke@intec.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 7, 'Algorithms|Gene Expression|Gene Knockout Techniques|Mutation|Quantitative Trait Loci|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btt142', '23595663', 'When genomic data are associated with gene expression data, the resulting expression quantitative trait loci (eQTL) will likely span multiple genes. eQTL prioritization techniques can be used to select the most likely causal gene affecting the expression of a target gene from a list of candidates. As an input, these techniques use physical interaction networks that often contain highly connected genes and unreliable or irrelevant interactions that can interfere with the prioritization process. We present EPSILON, an extendable framework for eQTL prioritization, which mitigates the effect of highly connected genes and unreliable interactions by constructing a local network before a network-based similarity measure is applied to select the true causal gene.'),
(77567, 2013, 'bio', 'Cytoscape app store', 'Lotia, Samad|Montojo, Jason|Dong, Yue|Bader, Gary D|Pico, Alexander R', 'Gladstone Institutes, San Francisco, CA 94158, USA.|Gladstone Institutes, San Francisco, CA 94158, USA.|Gladstone Institutes, San Francisco, CA 94158, USA.|Gladstone Institutes, San Francisco, CA 94158, USA.|Gladstone Institutes, San Francisco, CA 94158, USA.', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Internet|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btt138', '23595664', 'Cytoscape is an open source software tool for biological network visualization and analysis, which can be extended with independently developed apps. We launched the Cytoscape App Store to highlight the important features that apps add to Cytoscape, enable researchers to find and install apps they need and help developers promote their apps.'),
(77568, 2013, 'bio', 'CellH5: a format for data exchange in high-content screening', 'Sommer, Christoph|Held, Michael|Fischer, Bernd|Huber, Wolfgang|Gerlich, Daniel W', 'Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.|Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.|Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.|Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.|Institute of Molecular Biotechnology of the Austrian Academy of Sciences, 1030 Vienna, Austria.', 'Austria|Austria|Austria|Austria|Austria', 7, 'Algorithms|HeLa Cells|Humans|Image Processing, Computer-Assisted|Microscopy|Software', 'Journal Article', '10.1093/bioinformatics/btt175', '23595665', 'High-throughput microscopy data require a diversity of analytical approaches. However, the construction of workflows that use algorithms from different software packages is difficult owing to a lack of interoperability. To overcome this limitation, we present CellH5, an HDF5 data format for cell-based assays in high-throughput microscopy, which stores high-dimensional image data along with inter-object relations in graphs. CellH5Browser, an interactive gallery image browser, demonstrates the versatility and performance of the file format on live imaging data of dividing human cells. CellH5 provides new opportunities for integrated data analysis by multiple software platforms.'),
(77569, 2013, 'bio', 'Network-guided sparse regression modeling for detection of gene-by-gene interactions', 'Lu, Chen|Latourelle, Jeanne|OConnor, George T|Dupuis, Josée|Kolaczyk, Eric D', 'Department of Biostatistics, Boston University School of Public Health, Pulmonary Center, Department of Medicine and Department of Neurology, Boston University School of Medicine, Boston, MA, USA. chenlu@bu.edu|Department of Biostatistics, Boston University School of Public Health, Pulmonary Center, Department of Medicine and Department of Neurology, Boston University School of Medicine, Boston, MA, USA. chenlu@bu.edu|Department of Biostatistics, Boston University School of Public Health, Pulmonary Center, Department of Medicine and Department of Neurology, Boston University School of Medicine, Boston, MA, USA. chenlu@bu.edu|Department of Biostatistics, Boston University School of Public Health, Pulmonary Center, Department of Medicine and Department of Neurology, Boston University School of Medicine, Boston, MA, USA. chenlu@bu.edu|Department of Biostatistics, Boston University School of Public Health, Pulmonary Center, Department of Medicine and Department of Neurology, Boston University School of Medicine, Boston, MA, USA. chenlu@bu.edu', 'United States|United States|United States|United States|United States', 4, 'Computer Simulation|Epistasis, Genetic|Genome-Wide Association Study|HLA Antigens|Humans|Hypersensitivity|Immunoglobulin E|Polymorphism, Single Nucleotide|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btt139', '23599501', 'Genetic variants identified by genome-wide association studies to date explain only a small fraction of total heritability. Gene-by-gene interaction is one important potential source of unexplained total heritability. We propose a novel approach to detect such interactions that uses penalized regression and sparse estimation principles, and incorporates outside biological knowledge through a network-based penalty.'),
(77570, 2013, 'bio', 'INstruct: a database of high-quality 3D structurally resolved protein interactome networks', 'Meyer, Michael J|Das, Jishnu|Wang, Xiujuan|Yu, Haiyuan', 'Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.|Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.|Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.|Department of Biological Statistics and Computational Biology and Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, NY 14853, USA.', 'United States|United States|United States|United States', 62, 'Animals|Databases, Protein|Humans|Mice|Protein Interaction Domains and Motifs|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btt181', '23599502', 'INstruct is a database of high-quality, 3D, structurally resolved protein interactome networks in human and six model organisms. INstruct combines the scale of available high-quality binary protein interaction data with the specificity of atomic-resolution structural information derived from co-crystal evidence using a tested interaction interface inference method. Its web interface is designed to allow for flexible search based on standard and organism-specific protein and gene-naming conventions, visualization of protein architecture highlighting interaction interfaces and viewing and downloading custom 3D structurally resolved interactome datasets.'),
(77571, 2013, 'bio', 'A powerful and efficient set test for genetic markers that handles confounders', 'Listgarten, Jennifer|Lippert, Christoph|Kang, Eun Yong|Xiang, Jing|Kadie, Carl M|Heckerman, David', 'eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com|eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com|eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com|eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com|eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com|eScience Group, Microsoft Research, Los Angeles, CA 90024, USA. jennl@microsoft.com', 'United States|United States|United States|United States|United States|United States', 44, 'Algorithms|Case-Control Studies|Crohn Disease|Genetic Markers|Genome-Wide Association Study|Humans|Linear Models|Phenotype|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btt177', '23599503', 'Approaches for testing sets of variants, such as a set of rare or common variants within a gene or pathway, for association with complex traits are important. In particular, set tests allow for aggregation of weak signal within a set, can capture interplay among variants and reduce the burden of multiple hypothesis testing. Until now, these approaches did not address confounding by family relatedness and population structure, a problem that is becoming more important as larger datasets are used to increase power.'),
(77572, 2013, 'bio', 'An HMM-based algorithm for evaluating rates of receptor-ligand binding kinetics from thermal fluctuation data', 'Ju, Lining|Wang, Yijie Dylan|Hung, Ying|Wu, Chien-Fu Jeff|Zhu, Cheng', 'Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta 30318, USA.|Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta 30318, USA.|Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta 30318, USA.|Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta 30318, USA.|Coulter Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta 30318, USA.', 'Georgia|Georgia|Georgia|Georgia|Georgia', 1, 'Algorithms|Kinetics|Ligands|Markov Chains|Platelet Glycoprotein GPIb-IX Complex|Protein Binding|Temperature|von Willebrand Factor', 'Journal Article', '10.1093/bioinformatics/btt180', '23599504', 'Abrupt reduction/resumption of thermal fluctuations of a force probe has been used to identify association/dissociation events of protein-ligand bonds. We show that off-rate of molecular dissociation can be estimated by the analysis of the bond lifetime, while the on-rate of molecular association can be estimated by the analysis of the waiting time between two neighboring bond events. However, the analysis relies heavily on subjective judgments and is time-consuming. To automate the process of mapping out bond events from thermal fluctuation data, we develop a hidden Markov model (HMM)-based method.'),
(77573, 2013, 'bio', 'APP2: automatic tracing of 3D neuron morphology based on hierarchical pruning of a gray-weighted image distance-tree', 'Xiao, Hang|Peng, Hanchuan', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.', 'United States|United States', 91, 'Algorithms|Animals|Drosophila|Imaging, Three-Dimensional|Microscopy|Neurons|Software', 'Journal Article', '10.1093/bioinformatics/btt170', '23603332', 'Tracing of neuron morphology is an essential technique in computational neuroscience. However, despite a number of existing methods, few open-source techniques are completely or sufficiently automated and at the same time are able to generate robust results for real 3D microscopy images.'),
(77574, 2013, 'bio', 'rRNA:mRNA pairing alters the length and the symmetry of mRNA-protected fragments in ribosome profiling experiments', 'OConnor, Patrick B F|Li, Gene-Wei|Weissman, Jonathan S|Atkins, John F|Baranov, Pavel V', 'Department of Biochemistry, University College Cork, Cork, Ireland.|Department of Biochemistry, University College Cork, Cork, Ireland.|Department of Biochemistry, University College Cork, Cork, Ireland.|Department of Biochemistry, University College Cork, Cork, Ireland.|Department of Biochemistry, University College Cork, Cork, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland', 40, '5 Untranslated Regions|Bacillus subtilis|Codon|Escherichia coli|Protein Biosynthesis|RNA, Messenger|RNA, Ribosomal, 16S|Ribosomes', 'Journal Article', '10.1093/bioinformatics/btt184', '23603333', 'Ribosome profiling is a new technique that allows monitoring locations of translating ribosomes on mRNA at a whole transcriptome level. A recent ribosome profiling study demonstrated that internal Shine-Dalgarno (SD) sequences have a major global effect on translation rates in bacteria: ribosomes pause at SD sites in mRNA. Therefore, it is important to understand how SD sites effect mRNA movement through the ribosome and generation of ribosome footprints.'),
(77575, 2013, 'bio', 'ELOPER: elongation of paired-end reads as a pre-processing tool for improved de novo genome assembly', 'Silver, David H|Ben-Elazar, Shay|Bogoslavsky, Alexei|Yanai, Itai', 'Department of Biology, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Biology, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Biology, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Biology, Technion-Israel Institute of Technology, Haifa, Israel.', 'Israel|Israel|Israel|Israel', 5, 'Contig Mapping|Gene Library|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt169', '23603334', 'Paired-end sequencing resulting in gapped short reads is commonly used for de novo genome assembly. Assembly methods use paired-end sequences in a two-step process, first treating each read-end independently, only later invoking the pairing to join the contiguous assemblies (contigs) into gapped scaffolds. Here, we present ELOPER, a pre-processing tool for pair-end sequences that produces a better read library for assembly programs.'),
(77576, 2013, 'bio', 'A multi-layer inference approach to reconstruct condition-specific genes and their regulation', 'Wu, Ming|Liu, Li|Hijazi, Hussein|Chan, Christina', 'Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.|Department of Computer Science and Engineering, Michigan State University, East Lansing, MI 48824, USA.', 'United States|United States|United States|United States', 5, 'Acclimatization|Antigens, Neoplasm|Arabidopsis|Breast Neoplasms|Cell Adhesion Molecules|Cold Temperature|Female|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Fungal|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Systems Biology|Transcription Factors|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btt186', '23610368', 'An important topic in systems biology is the reverse engineering of regulatory mechanisms through reconstruction of context-dependent gene networks. A major challenge is to identify the genes and the regulations specific to a condition or phenotype, given that regulatory processes are highly connected such that a specific response is typically accompanied by numerous collateral effects. In this study, we design a multi-layer approach that is able to reconstruct condition-specific genes and their regulation through an integrative analysis of large-scale information of gene expression, protein interaction and transcriptional regulation (transcription factor-target gene relationships). We establish the accuracy of our methodology against synthetic datasets, as well as a yeast dataset. We then extend the framework to the application of higher eukaryotic systems, including human breast cancer and Arabidopsis thaliana cold acclimation. Our study identified TACSTD2 (TROP2) as a target gene for human breast cancer and discovered its regulation by transcription factors CREB, as well as NFkB. We also predict KIF2C is a target gene for ER-/HER2- breast cancer and is positively regulated by E2F1. The predictions were further confirmed through experimental studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77577, 2013, 'bio', 'Automated annotation and quantification of glycans using liquid chromatography-mass spectrometry', 'Yu, Chuan-Yih|Mayampurath, Anoop|Hu, Yunli|Zhou, Shiyue|Mechref, Yehia|Tang, Haixu', 'School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. chuyu@indiana.edu', 'India|India|India|India|India|India', 24, 'Cell Line, Tumor|Chromatography, Liquid|Glycomics|Glycoproteins|Glycosylation|Humans|Mass Spectrometry|Molecular Sequence Annotation|Polysaccharides|Protein Processing, Post-Translational|Software', 'Journal Article', '10.1093/bioinformatics/btt190', '23610369', 'As a common post-translational modification, protein glycosylation plays an important role in many biological processes, and it is known to be associated with human diseases. Mass spectrometry (MS)-based glycomic profiling techniques have been developed to measure the abundances of glycans in complex biological samples and applied to the discovery of putative glycan biomarkers. To automate the annotation of glycomic profiles in the liquid chromatography-MS (LC-MS) data, we present here a user-friendly software tool, MultiGlycan, implemented in C# on Windows systems. We tested MultiGlycan by using several glycomic profiling datasets acquired using LC-MS under different preparations and show that MultiGlycan executes fast and generates robust and reliable results.'),
(77578, 2013, 'bio', 'Mendel: the Swiss army knife of genetic analysis programs', 'Lange, Kenneth|Papp, Jeanette C|Sinsheimer, Janet S|Sripracha, Ram|Zhou, Hua|Sobel, Eric M', 'Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu|Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu|Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu|Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu|Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu|Department of Human Genetics and Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095, USA. klange@ucla.edu', 'United States|United States|United States|United States|United States|United States', 74, 'Chromosome Mapping|Data Interpretation, Statistical|Genetic Linkage|Genome-Wide Association Study|Humans|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/btt187', '23610370', 'Mendel is one of the few statistical genetics packages that provide a full spectrum of gene mapping methods, ranging from parametric linkage in large pedigrees to genome-wide association with rare variants. Our latest additions to Mendel anticipate and respond to the needs of the genetics community. Compared with earlier versions, Mendel is faster and easier to use and has a wider range of applications. Supported platforms include Linux, MacOS and Windows.'),
(77579, 2013, 'bio', 'A unifying kinetic framework for modeling oxidoreductase-catalyzed reactions', 'Chang, Ivan|Baldi, Pierre', 'Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA.|Department of Biomedical Engineering, University of California, Irvine, CA 92697, USA.', 'United States|United States', 0, 'Eukaryota|Kinetics|Models, Chemical|Oxidation-Reduction|Oxidoreductases|Prokaryotic Cells|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btt140', '23613486', 'Oxidoreductases are a fundamental class of enzymes responsible for the catalysis of oxidation-reduction reactions, crucial in most bioenergetic metabolic pathways. From their common root in the ancient prebiotic environment, oxidoreductases have evolved into diverse and elaborate protein structures with specific kinetic properties and mechanisms adapted to their individual functional roles and environmental conditions. While accurate kinetic modeling of oxidoreductases is thus important, current models suffer from limitations to the steady-state domain, lack empirical validation or are too specialized to a single system or set of conditions.'),
(77580, 2013, 'bio', 'mapDamage20: fast approximate Bayesian estimates of ancient DNA damage parameters', 'Jxc3xb3nsson, Hxc3xa1kon|Ginolhac, Aurxc3xa9lien|Schubert, Mikkel|Johnson, Philip L F|Orlando, Ludovic', 'Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Kxc3xb8benhavn K, Denmark. jonsson.hakon@gmail.com|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Kxc3xb8benhavn K, Denmark. jonsson.hakon@gmail.com|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Kxc3xb8benhavn K, Denmark. jonsson.hakon@gmail.com|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Kxc3xb8benhavn K, Denmark. jonsson.hakon@gmail.com|Centre for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Kxc3xb8benhavn K, Denmark. jonsson.hakon@gmail.com', 'Denmark|Denmark|Denmark|Denmark|Denmark', 398, 'Bayes Theorem|Cytosine|DNA Damage|Deamination|Fossils|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt193', '23613487', 'Ancient DNA (aDNA) molecules in fossilized bones and teeth, coprolites, sediments, mummified specimens and museum collections represent fantastic sources of information for evolutionary biologists, revealing the agents of past epidemics and the dynamics of past populations. However, the analysis of aDNA generally faces two major issues. Firstly, sequences consist of a mixture of endogenous and various exogenous backgrounds, mostly microbial. Secondly, high nucleotide misincorporation rates can be observed as a result of severe post-mortem DNA damage. Such misincorporation patterns are instrumental to authenticate ancient sequences versus modern contaminants. We recently developed the user-friendly mapDamage package that identifies such patterns from next-generation sequencing (NGS) sequence datasets. The absence of formal statistical modeling of the DNA damage process, however, precluded rigorous quantitative comparisons across samples.'),
(77581, 2013, 'bio', 'CellAging: a tool to study segregation and partitioning in division in cell lineages of Escherichia coli', 'Häkkinen, Antti|Muthukrishnan, Anantha-Barathi|Mora, Andre|Fonseca, Jose M|Ribeiro, Andre S', 'Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland.', 'Finland|Finland|Finland|Finland|Finland', 29, 'Cell Division|Cell Lineage|Escherichia coli|Image Processing, Computer-Assisted|Luminescent Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt194', '23613488', 'Cell division in Escherichia coli is morphologically symmetric. However, as unwanted protein aggregates are segregated to the cell poles and, after divisions, accumulate at older poles, generate asymmetries in sister cells vitality. Novel single-molecule detection techniques allow observing aging-related processes in vivo, over multiple generations, informing on the underlying mechanisms.'),
(77582, 2013, 'bio', 'Systematic tracking of dysregulated modules identifies novel genes in cancer', 'Srihari, Sriganesh|Ragan, Mark A', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia', 47, 'BRCA2 Protein|Breast Neoplasms|Female|Gene Expression|Gene Expression Regulation, Neoplastic|Genes, BRCA1|Genes, BRCA2|Genes, Neoplasm|Humans|Mutation|Neoplasms|Pancreatic Neoplasms|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/btt191', '23613489', 'Deciphering the modus operandi of dysregulated cellular mechanisms in cancer is critical to implicate novel cancer genes and develop effective anti-cancer therapies. Fundamental to this is meticulous tracking of the behavior of core modules, including complexes and pathways across specific conditions in cancer.'),
(77583, 2013, 'bio', 'Dragon PolyA Spotter: predictor of poly(A) motifs within human genomic DNA sequences', 'Kalkatawi, Manal|Rangkuti, Farania|Schramm, Michael|Jankovic, Boris R|Kamau, Allan|Chowdhary, Rajesh|Archer, John A C|Bajic, Vladimir B', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 6, 'Algorithms|Humans|Neural Networks (Computer)|Poly A', 'Letter', '10.1093/bioinformatics/btt161', '23616439', '-'),
(77584, 2013, 'bio', 'Structural RNA alignment by multi-objective optimization', 'Schnattinger, Thomas|Schöning, Uwe|Kestler, Hans A', 'Institute of Theoretical Computer Science, Ulm University, 89069 Ulm, Germany.|Institute of Theoretical Computer Science, Ulm University, 89069 Ulm, Germany.|Institute of Theoretical Computer Science, Ulm University, 89069 Ulm, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Nucleic Acid Conformation|RNA|RNA, Transfer|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt188', '23620356', 'The calculation of reliable alignments for structured RNA is still considered as an open problem. One approach is the incorporation of secondary structure information into the optimization criteria by using a weighted sum of sequence and structure components as an objective function. As it is not clear how to choose the weighting parameters, we use multi-objective optimization to calculate a set of Pareto-optimal RNA sequence-structure alignments. The solutions in this set then represent all possible trade-offs between the different objectives, independent of any previous weighting.'),
(77585, 2013, 'bio', 'A support vector machine for identification of single-nucleotide polymorphisms from next-generation sequencing data', 'OFallon, Brendan D|Wooderchak-Donahue, Whitney|Crockett, David K', 'ARUP Institute of Clinical and Experimental Pathology, 500 Chipeta Way, Salt Lake City, UT 84102, USA. brendan.d.ofallon@aruplab.com|ARUP Institute of Clinical and Experimental Pathology, 500 Chipeta Way, Salt Lake City, UT 84102, USA. brendan.d.ofallon@aruplab.com|ARUP Institute of Clinical and Experimental Pathology, 500 Chipeta Way, Salt Lake City, UT 84102, USA. brendan.d.ofallon@aruplab.com', 'United States|United States|United States', 22, 'Genomics|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btt172', '23620357', 'Accurate determination of single-nucleotide polymorphisms (SNPs) from next-generation sequencing data is a significant challenge facing bioinformatics researchers. Most current methods use mechanistic models that assume nucleotides aligning to a given reference position are sampled from a binomial distribution. While such methods are sensitive, they are often unable to discriminate errors resulting from misaligned reads, sequencing errors or platform artifacts from true variants.'),
(77586, 2013, 'bio', 'A novel web server predicts amino acid residue protection against hydrogen-deuterium exchange', 'Lobanov, Mikhail Yu|Suvorina, Masha Yu|Dovidchenko, Nikita V|Sokolovskiy, Igor V|Surin, Alexey K|Galzitskaya, Oxana V', 'Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.|Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.|Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.|Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.|Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.|Institute of Protein Research, Russian Academy of Sciences, Pushchino, Moscow Region, Russia.', '-|-|-|-|-|-', 12, 'Amino Acids|Deuterium Exchange Measurement|Internet|Mass Spectrometry|Peptides|Proteins|Protons|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btt168', '23620358', 'To clarify the relationship between structural elements and polypeptide chain mobility, a set of statistical analyses of structures is necessary. Because at present proteins with determined spatial structures are much less numerous than those with amino acid sequence known, it is important to be able to predict the extent of proton protection from hydrogen-deuterium (HD) exchange basing solely on the protein primary structure.'),
(77587, 2013, 'bio', 'Janus--a comprehensive tool investigating the two faces of transcription', 'Barann, Matthias|Esser, Daniela|Klostermeier, Ulrich C|Lappalainen, Tuuli|Luzius, Anne|Kuiper, Jan W P|Ammerpohl, Ole|Vater, Inga|Siebert, Reiner|Amstislavskiy, Vyacheslav|Sudbrak, Ralf|Lehrach, Hans|Schreiber, Stefan|Rosenstiel, Philip', 'Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de|Institute for Clinical Molecular Biology, Christian-Albrechts-University, 24105 Kiel, Germany. m.barann@mucosa.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 1, 'Cell Line, Transformed|DNA Methylation|Gene Expression Profiling|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|RNA, Antisense|Software', 'Journal Article', '10.1093/bioinformatics/btt185', '23620359', 'Protocols to generate strand-specific transcriptomes with next-generation sequencing platforms have been used by the scientific community roughly since 2008. Strand-specific reads allow for detection of antisense events and a higher resolution of expression profiles enabling extension of current transcript annotations. However, applications making use of this strandedness information are still scarce.'),
(77588, 2013, 'bio', 'Shimmer: detection of genetic alterations in tumors using next-generation sequence data', 'Hansen, Nancy F|Gartner, Jared J|Mei, Lan|Samuels, Yardena|Mullikin, James C', 'Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov|Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov|Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov|Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov|Genome Technology Branch, NHGRI/NIH, Bethesda, MD 20892-9400, USA. nhansen@mail.nih.gov', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Cell Line, Tumor|DNA Mutational Analysis|Exome|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|Mutation|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btt183', '23620360', 'Extensive DNA sequencing of tumor and matched normal samples using exome and whole-genome sequencing technologies has enabled the discovery of recurrent genetic alterations in cancer cells, but variability in stromal contamination and subclonal heterogeneity still present a severe challenge to available detection algorithms.'),
(77589, 2013, 'bio', 'Sharing and executing linked data queries in a collaborative environment', 'García Godoy, María Jesús|López-Camacho, Esteban|Navas-Delgado, Ismael|Aldana-Montes, José F', 'Lenguajes y Ciencias de la Computación, Universidad de Málaga, Bulevar Louis Pasteur 35, Málaga, Spain.|Lenguajes y Ciencias de la Computación, Universidad de Málaga, Bulevar Louis Pasteur 35, Málaga, Spain.|Lenguajes y Ciencias de la Computación, Universidad de Málaga, Bulevar Louis Pasteur 35, Málaga, Spain.|Lenguajes y Ciencias de la Computación, Universidad de Málaga, Bulevar Louis Pasteur 35, Málaga, Spain.', 'Spain|Spain|Spain|Spain', 7, 'Biological Science Disciplines|Cooperative Behavior|Databases, Factual|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btt192', '23620361', 'Life Sciences have emerged as a key domain in the Linked Data community because of the diversity of data semantics and formats available through a great variety of databases and web technologies. Thus, it has been used as the perfect domain for applications in the web of data. Unfortunately, bioinformaticians are not exploiting the full potential of this already available technology, and experts in Life Sciences have real problems to discover, understand and devise how to take advantage of these interlinked (integrated) data.'),
(77590, 2013, 'bio', 'RSVSim: an R/Bioconductor package for the simulation of structural variations', 'Bartenhagen, Christoph|Dugas, Martin', 'Institute of Medical Informatics, University of Münster, Münster. christoph.bartenhagen@uni-muenster.de|Institute of Medical Informatics, University of Münster, Münster. christoph.bartenhagen@uni-muenster.de', '-|-', 0, 'Chromosome Breakpoints|Computer Simulation|Genome|Genomic Structural Variation|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btt198', '23620362', 'RSVSim is a tool for the simulation of deletions, insertions, inversions, tandem duplications and translocations of various sizes in any genome available as FASTA-file or data package in R. The structural variations can be generated randomly, based on user-supplied genomic coordinates or associated to various kinds of repeats. The package further comprises functions to estimate the distribution of structural variation sizes from real datasets.'),
(77591, 2013, 'bio', 'Predicting the functional consequences of cancer-associated amino acid substitutions', 'Shihab, Hashem A|Gough, Julian|Cooper, David N|Day, Ian N M|Gaunt, Tom R', 'Bristol Centre for Systems Biomedicine and MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK.|Bristol Centre for Systems Biomedicine and MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK.|Bristol Centre for Systems Biomedicine and MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK.|Bristol Centre for Systems Biomedicine and MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK.|Bristol Centre for Systems Biomedicine and MRC CAiTE Centre, School of Social and Community Medicine, University of Bristol, Bristol BS8 2BN, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 102, 'Algorithms|Amino Acid Substitution|DNA Mutational Analysis|Genomics|Humans|Mutation, Missense|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btt182', '23620363', 'The number of missense mutations being identified in cancer genomes has greatly increased as a consequence of technological advances and the reduced cost of whole-genome/whole-exome sequencing methods. However, a high proportion of the amino acid substitutions detected in cancer genomes have little or no effect on tumour progression (passenger mutations). Therefore, accurate automated methods capable of discriminating between driver (cancer-promoting) and passenger mutations are becoming increasingly important. In our previous work, we developed the Functional Analysis through Hidden Markov Models (FATHMM) software and, using a model weighted for inherited disease mutations, observed improved performances over alternative computational prediction algorithms. Here, we describe an adaptation of our original algorithm that incorporates a cancer-specific model to potentiate the functional analysis of driver mutations.'),
(77592, 2013, 'bio', 'HOMECAT: consensus homologs mapping for interspecific knowledge transfer and functional genomic data integration', 'Zorzan, Simone|Lorenzetto, Erika|Ettorre, Michele|Pontelli, Valeria|Laudanna, Carlo|Buffelli, Mario', 'Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it|Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it|Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it|Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it|Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it|Department of Neurological, Neuropsychological, Morphological and Motor Sciences, Section of Physiology, University of Verona, Strada le Grazie 8, 37134, Verona, Italy. simone.zorzan@univr.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Animals|Genomics|Mice|Oligonucleotide Array Sequence Analysis|Rats|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btt189', '23620364', 'Comparative studies are encouraged by the fast increase of data availability from the latest high-throughput techniques, in particular from functional genomic studies. Yet, the size of datasets, the challenge of complete orthologs findings and not last, the variety of identification formats, make information integration challenging. With HOMECAT, we aim to facilitate cross-species relationship identification and data mapping, by combining orthology predictions from several publicly available sources, a convenient interface for high-throughput data download and automatic identifier conversion into a Cytoscape plug-in, that provides both an integration with a large set of bioinformatics tools, as well as a user-friendly interface.'),
(77593, 2013, 'bio', 'NetworkTrail--a web service for identifying and visualizing deregulated subnetworks', 'Stöckel, Daniel|Müller, Oliver|Kehl, Tim|Gerasch, Andreas|Backes, Christina|Rurainski, Alexander|Keller, Andreas|Kaufmann, Michael|Lenhof, Hans-Peter', 'Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de|Center for Bioinformatics, Saarland University, 66041 Saarbrücken, Germany. dstoeckel@bioinf.uni-sb.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 9, 'Algorithms|Animals|Computer Graphics|Computer Simulation|Gene Expression Profiling|Gene Regulatory Networks|Humans|Internet|Mice|Programming, Linear|Rats|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt204', '23625999', 'The deregulation of biochemical pathways plays a central role in many diseases like cancer or Parkinsonss disease. In silico tools for calculating these deregulated pathways may help to gain new insights into pathogenic mechanisms and may open novel avenues for therapy stratification in the sense of personalized medicine. Here, we present NetworkTrail, a web service for the detection of deregulated pathways and subgraphs in biological networks. NetworkTrail uses a state-of-the-art integer linear programming-based approach for this task and offers interfaces to the Biological Network Analyzer (BiNA) and Cytoscape Web for visualizing the resulting subnetworks. By providing an accessible interface to otherwise hard-to-use command line tools, the new web service enables non-experts to quickly and reliably carry out this type of network analyses.'),
(77594, 2013, 'bio', 'OCSANA: optimal combinations of interventions from network analysis', 'Vera-Licona, Paola|Bonnet, Eric|Barillot, Emmanuel|Zinovyev, Andrei', 'Institut Curie, Paris F-75248, France, INSERM, U900, Paris F-75248, France. paola.vera-licona@curie.fr|Institut Curie, Paris F-75248, France, INSERM, U900, Paris F-75248, France. paola.vera-licona@curie.fr|Institut Curie, Paris F-75248, France, INSERM, U900, Paris F-75248, France. paola.vera-licona@curie.fr|Institut Curie, Paris F-75248, France, INSERM, U900, Paris F-75248, France. paola.vera-licona@curie.fr', 'France|France|France|France', 17, 'Algorithms|Breast Neoplasms|ErbB Receptors|Female|Humans|Receptor, ErbB-2|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btt195', '23626000', 'Targeted therapies interfering with specifically one protein activity are promising strategies in the treatment of diseases like cancer. However, accumulated empirical experience has shown that targeting multiple proteins in signaling networks involved in the disease is often necessary. Thus, one important problem in biomedical research is the design and prioritization of optimal combinations of interventions to repress a pathological behavior, while minimizing side-effects. OCSANA (optimal combinations of interventions from network analysis) is a new software designed to identify and prioritize optimal and minimal combinations of interventions to disrupt the paths between source nodes and target nodes. When specified by the user, OCSANA seeks to additionally minimize the side effects that a combination of interventions can cause on specified off-target nodes. With the crucial ability to cope with very large networks, OCSANA includes an exact solution and a novel selective enumeration approach for the combinatorial interventions problem.'),
(77595, 2013, 'bio', 'Incorporating key position and amino acid residue features to identify general and species-specific Ubiquitin conjugation sites', 'Chen, Xiang|Qiu, Jian-Ding|Shi, Shao-Ping|Suo, Sheng-Bao|Huang, Shu-Yun|Liang, Ru-Ping', 'Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.|Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.|Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.|Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.|Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.|Department of Chemistry, Nanchang University, Nanchang 330031, Peoples Republic of China.', 'China|China|China|China|China|China', 67, 'Amino Acids|Animals|Artificial Intelligence|Humans|Mice|Proteome|Proteomics|Sequence Analysis, Protein|Software|Species Specificity|Ubiquitin|Ubiquitinated Proteins|Ubiquitination', 'Journal Article', '10.1093/bioinformatics/btt196', '23626001', 'Systematic dissection of the ubiquitylation proteome is emerging as an appealing but challenging research topic because of the significant roles ubiquitylation play not only in protein degradation but also in many other cellular functions. High-throughput experimental studies using mass spectrometry have identified many ubiquitylation sites, primarily from eukaryotes. However, the vast majority of ubiquitylation sites remain undiscovered, even in well-studied systems. Because mass spectrometry-based experimental approaches for identifying ubiquitylation events are costly, time-consuming and biased toward abundant proteins and proteotypic peptides, in silico prediction of ubiquitylation sites is a potentially useful alternative strategy for whole proteome annotation. Because of various limitations, current ubiquitylation site prediction tools were not well designed to comprehensively assess proteomes.'),
(77596, 2013, 'bio', 'KGVDB: a population-based genomic map of CNVs tagged by SNPs in Koreans', 'Moon, Sanghoon|Jung, Kwang Su|Kim, Young Jin|Hwang, Mi Yeong|Han, Kyungsook|Lee, Jong-Young|Park, Kiejung|Kim, Bong-Jo', 'Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.|Division of Structural and Functional Genomics, Division of Bio-Medical informatics, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, Korea.', '-|-|-|-|-|-|-|-', 0, 'Asian Continental Ancestry Group|Chromosome Mapping|DNA Copy Number Variations|Databases, Nucleic Acid|Genome, Human|Genome-Wide Association Study|Genomics|Humans|Korea|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btt173', '23626002', 'Despite a growing interest in a correlation between copy number variations (CNVs) and flanking single nucleotide polymorphisms, few databases provide such information. In particular, most information on CNV available so far was obtained in Caucasian and Yoruba populations, and little is known about CNV in Asian populations. This article presents a database that provides CNV regions tagged by single nucleotide polymorphisms in about 4700 Koreans, which were detected under strict quality control, manually curated and experimentally validated.'),
(77597, 2013, 'bio', 'RUbioSeq: a suite of parallelized pipelines to automate exome variation and bisulfite-seq analyses', 'Rubio-Camarillo, Miriam|Gómez-López, Gonzalo|Fernández, José M|Valencia, Alfonso|Pisano, David G', 'Structural Computational Biology Group, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, 28029 Madrid, Spain. mrubioc@cnio.es|Structural Computational Biology Group, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, 28029 Madrid, Spain. mrubioc@cnio.es|Structural Computational Biology Group, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, 28029 Madrid, Spain. mrubioc@cnio.es|Structural Computational Biology Group, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, 28029 Madrid, Spain. mrubioc@cnio.es|Structural Computational Biology Group, Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, 28029 Madrid, Spain. mrubioc@cnio.es', 'Spain|Spain|Spain|Spain|Spain', 29, 'DNA Copy Number Variations|DNA Methylation|Exome|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btt203', '23630175', 'RUbioSeq has been developed to facilitate the primary and secondary analysis of re-sequencing projects by providing an integrated software suite of parallelized pipelines to detect exome variants (single-nucleotide variants and copy number variations) and to perform bisulfite-seq analyses automatically. RUbioSeqs variant analysis results have been already validated and published.'),
(77598, 2013, 'bio', 'BioBlend: automating pipeline analyses within Galaxy and CloudMan', 'Sloggett, Clare|Goonasekera, Nuwan|Afgan, Enis', 'Victorian Life Sciences Computation Initiative, University of Melbourne, Melbourne, Australia.|Victorian Life Sciences Computation Initiative, University of Melbourne, Melbourne, Australia.|Victorian Life Sciences Computation Initiative, University of Melbourne, Melbourne, Australia.', 'Australia|Australia|Australia', 0, 'Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btt199', '23630176', 'We present BioBlend, a unified API in a high-level language (python) that wraps the functionality of Galaxy and CloudMan APIs. BioBlend makes it easy for bioinformaticians to automate end-to-end large data analysis, from scratch, in a way that is highly accessible to collaborators, by allowing them to both provide the required infrastructure and automate complex analyses over large datasets within the familiar Galaxy environment.'),
(77599, 2013, 'bio', 'Intervention in gene regulatory networks with maximal phenotype alteration', 'Yousefi, Mohammadmahdi R|Dougherty, Edward R', 'Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States', 21, 'Algorithms|Cell Cycle|Gene Regulatory Networks|Humans|Melanoma|Neoplasm Metastasis|Phenotype|Probability|Programming, Linear', 'Journal Article', '10.1093/bioinformatics/btt242', '23630177', 'A basic issue for translational genomics is to model gene interaction via gene regulatory networks (GRNs) and thereby provide an informatics environment to study the effects of intervention (say, via drugs) and to derive effective intervention strategies. Taking the view that the phenotype is characterized by the long-run behavior (steady-state distribution) of the network, we desire interventions to optimally move the probability mass from undesirable to desirable states Heretofore, two external control approaches have been taken to shift the steady-state mass of a GRN: (i) use a user-defined cost function for which desirable shift of the steady-state mass is a by-product and (ii) use heuristics to design a greedy algorithm. Neither approach provides an optimal control policy relative to long-run behavior.'),
(77600, 2013, 'bio', 'miMsg: a target enrichment algorithm for predicted miR-mRNA interactions based on relative ranking of matched expression data', 'Rijlaarsdam, Martin A|Rijlaarsdam, David J|Gillis, Ad J M|Dorssers, Lambert C J|Looijenga, Leendert H J', 'Department of Pathology, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. l.looijenga@erasmusmc.nl|Department of Pathology, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. l.looijenga@erasmusmc.nl|Department of Pathology, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. l.looijenga@erasmusmc.nl|Department of Pathology, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. l.looijenga@erasmusmc.nl|Department of Pathology, Erasmus MC-University Medical Center Rotterdam, Rotterdam, The Netherlands. l.looijenga@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 4, 'Algorithms|Gene Expression Profiling|Humans|MicroRNAs|Neoplasms, Germ Cell and Embryonal|RNA, Messenger', 'Journal Article', '10.1093/bioinformatics/btt246', '23640718', 'Algorithms predicting microRNA (miR)-mRNA interactions generate high numbers of possible interactions, many of which might be non-existent or irrelevant in a certain biological context. It is desirable to develop a transparent, user-friendly, unbiased tool to enrich miR-mRNA predictions.'),
(77601, 2013, 'bio', 'Self-interaction of transmembrane helices representing pre-clusters from the human single-span membrane proteins', 'Kirrbach, Jan|Krugliak, Miriam|Ried, Christian L|Pagel, Philipp|Arkin, Isaiah T|Langosch, Dieter', 'Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.|Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.|Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.|Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.|Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.|Lehrstuhl für Chemie der Biopolymere, Technische Universität München, 85354 Freising, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 8, 'Humans|Membrane Proteins|Mutation|Protein Interaction Domains and Motifs|Protein Structure, Secondary|Protein Structure, Tertiary|Proteome|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btt247', '23640719', 'Most integral membrane proteins form dimeric or oligomeric complexes. Oligomerization is frequently supported by the non-covalent interaction of transmembrane helices. It is currently not clear how many high-affinity transmembrane domains (TMD) exist in a proteome and how specific their interactions are with respect to preferred contacting faces and their underlying residue motifs.'),
(77602, 2013, 'bio', 'RegaDB: community-driven data management and analysis for infectious diseases', 'Libin, Pieter|Beheydt, Gertjan|Deforche, Koen|Imbrechts, Stijn|Ferreira, Fossie|Van Laethem, Kristel|Theys, Kristof|Carvalho, Ana Patricia|Cavaco-Silva, Joana|Lapadula, Giuseppe|Torti, Carlo|Assel, Matthias|Wesner, Stefan|Snoeck, Joke|Ruelle, Jean|De Bel, Annelies|Lacor, Patrick|De Munter, Paul|Van Wijngaerden, Eric|Zazzi, Maurizio|Kaiser, Rolf|Ayouba, Ahidjo|Peeters, Martine|de Oliveira, Tulio|Alcantara, Luiz C J|Grossman, Zehava|Sloot, Peter|Otelea, Dan|Paraschiv, Simona|Boucher, Charles|Camacho, Ricardo J|Vandamme, Anne-Mieke', 'Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute for Medical Research, KU Leuven, Leuven, Belgium. pieter.libin@rega.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belg', 21, 'Database Management Systems|Databases, Factual|Humans|Software|Virus Diseases', 'Journal Article', '10.1093/bioinformatics/btt162', '23645815', 'RegaDB is a free and open source data management and analysis environment for infectious diseases. RegaDB allows clinicians to store, manage and analyse patient data, including viral genetic sequences. Moreover, RegaDB provides researchers with a mechanism to collect data in a uniform format and offers them a canvas to make newly developed bioinformatics tools available to clinicians and virologists through a user friendly interface.'),
(77603, 2014, 'bio', 'Further steps in TANGO: improved taxonomic assignment in metagenomics', 'Alonso-Alemany, Daniel|Barré, Aurélien|Beretta, Stefano|Bonizzoni, Paola|Nikolski, Macha|Valiente, Gabriel', 'Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.|Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.|Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.|Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.|Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.|Department of Software, Technical University of Catalonia, E-08034 Barcelona, Spain, Université Bordeaux, Bordeaux Bioinformatics Center (CBiB), F-33000 Bordeaux, France, Dipartimento di Informatica Sistemistica e Comunicazione, Università Degli Studi di Milano-Bicocca, I-20125 Milan, Italy and Université Bordeaux, Laboratoire Bordelais de Recherche en Informatique (CNRS/LaBRI), F-33405 Talence, France.', 'Spain|Spain|Spain|Spain|Spain|Spain', 12, 'Algorithms|Metagenomics|Software', 'Journal Article', '10.1093/bioinformatics/btt256', '23645816', 'TANGO is one of the most accurate tools for the taxonomic assignment of sequence reads. However, because of the differences in the taxonomy structures, performing a taxonomic assignment on different reference taxonomies will produce divergent results.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77604, 2013, 'bio', 'A universal open-source Electronic Laboratory Notebook', 'Voegele, Catherine|Bouchereau, Baptiste|Robinot, Nivonirina|McKay, James|Damiecki, Philippe|Alteyrac, Lucile', 'Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, 69003 Lyon, France. voegele@iarc.fr', 'France|France|France|France|France|France', 13, 'Databases, Factual|Laboratories|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btt253', '23645817', 'Laboratory notebooks remain crucial to the activities of research communities. With the increase in generation of electronic data within both wet and dry analytical laboratories and new technologies providing more efficient means of communication, Electronic Laboratory Notebooks (ELN) offer equivalent record keeping to paper-based laboratory notebooks (PLN). They additionally allow more efficient mechanisms for data sharing and retrieval, which explains the growing number of commercial ELNs available varying in size and scope but all are increasingly accepted and used by the scientific community. The International Agency for Research on Cancer (IARC) having already an LIMS and a Biobank Management System for respectively laboratory workflows and sample management, we have developed a free multidisciplinary ELN specifically dedicated to work notes that will be flexible enough to accommodate different types of data.'),
(77605, 2013, 'bio', 'pyGenClean: efficient tool for genetic data clean up before association testing', 'Lemieux Perreault, Louis-Philippe|Provost, Sylvie|Legault, Marc-André|Barhdadi, Amina|Dubé, Marie-Pierre', 'Montreal Heart Institute Research Center, Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca|Montreal Heart Institute Research Center, Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca|Montreal Heart Institute Research Center, Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca|Montreal Heart Institute Research Center, Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca|Montreal Heart Institute Research Center, Beaulieu-Saucier Université de Montréal Pharmacogenomics Centre, 5000 Bélanger Street, Montréal, Canada. louis-philippe.lemieux.perreault@umontreal.ca', 'Canada|Canada|Canada|Canada|Canada', 7, 'Genetic Association Studies|Genotyping Techniques|Humans|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/btt261', '23652425', 'Genetic association studies making use of high-throughput genotyping arrays need to process large amounts of data in the order of millions of markers per experiment. The first step of any analysis with genotyping arrays is typically the conduct of a thorough data clean up and quality control to remove poor quality genotypes and generate metrics to inform and select individuals for downstream statistical analysis. We have developed pyGenClean, a bioinformatics tool to facilitate and standardize the genetic data clean up pipeline with genotyping array data. In conjunction with a source batch-queuing system, the tool minimizes data manipulation errors, accelerates the completion of the data clean up process and provides informative plots and metrics to guide decision making for statistical analysis.'),
(77606, 2013, 'bio', 'InterEvScore: a novel coarse-grained interface scoring function using a multi-body statistical potential coupled to evolution', 'Andreani, Jessica|Faure, Guilhem|Guerois, Raphael', 'CEA, iBiTecS, Service de Bioenergetique Biologie Structurale et Mecanismes SB2SM, Laboratoire de Biologie Structurale et Radiobiologie LBSR, F-91191 Gif sur Yvette, France.|CEA, iBiTecS, Service de Bioenergetique Biologie Structurale et Mecanismes SB2SM, Laboratoire de Biologie Structurale et Radiobiologie LBSR, F-91191 Gif sur Yvette, France.|CEA, iBiTecS, Service de Bioenergetique Biologie Structurale et Mecanismes SB2SM, Laboratoire de Biologie Structurale et Radiobiologie LBSR, F-91191 Gif sur Yvette, France.', 'France|France|France', 41, 'Data Interpretation, Statistical|Evolution, Molecular|Knowledge Bases|Molecular Docking Simulation|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt260', '23652426', 'Structural prediction of protein interactions currently remains a challenging but fundamental goal. In particular, progress in scoring functions is critical for the efficient discrimination of near-native interfaces among large sets of decoys. Many functions have been developed using knowledge-based potentials, but few make use of multi-body interactions or evolutionary information, although multi-residue interactions are crucial for protein-protein binding and protein interfaces undergo significant selection pressure to maintain their interactions.'),
(77607, 2013, 'bio', 'Evidence for the dissemination of cryptic non-coding RNAs transcribed from intronic and intergenic segments by retroposition', 'Hahn, Yoonsoo', 'Department of Life Science, Research Center for Biomolecules and Biosystems, Chung-Ang University, Seoul 156-756, Korea. yoonsoo.hahn@gmail.com', '-', 0, 'Animals|Base Sequence|Conserved Sequence|DNA, Intergenic|Evolution, Molecular|Exons|Genome|Genomics|Humans|Introns|Mice|Promoter Regions, Genetic|RNA, Untranslated|Rats', 'Journal Article', '10.1093/bioinformatics/btt258', '23652427', 'Insertion of DNA segments is one mechanism by which genomes evolve. The bulk of genomic segments are now known to be transcribed into long and short non-coding RNAs (ncRNAs), promoter-associated transcripts and enhancer-templated transcripts. These various cryptic ncRNAs are thought to be dispersed in the human and other genomes by retroposition.'),
(77608, 2014, 'bio', 'A poor mans BLASTX--high-throughput metagenomic protein database search using PAUDA', 'Huson, Daniel H|Xie, Chao', 'Singapore Centre on Environmental Life Sciences Engineering, School of Biological Sciences, Nanyang Technological University, Singapore 637551, Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany and Life Sciences Institute, National University of Singapore, Singapore 117456.|Singapore Centre on Environmental Life Sciences Engineering, School of Biological Sciences, Nanyang Technological University, Singapore 637551, Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany and Life Sciences Institute, National University of Singapore, Singapore 117456.', 'Germany|Germany', 40, 'Algorithms|Amino Acid Sequence|Base Sequence|Databases, Protein|Metagenomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt254', '23658416', 'In the context of metagenomics, we introduce a new approach to protein database search called PAUDA, which runs ~10,000 times faster than BLASTX, while achieving about one-third of the assignment rate of reads to KEGG orthology groups, and producing gene and taxon abundance profiles that are highly correlated to those obtained with BLASTX. PAUDA requires <80 CPU hours to analyze a dataset of 246 million Illumina DNA reads from permafrost soil for which a previous BLASTX analysis (on a subset of 176 million reads) reportedly required 800,000 CPU hours, leading to the same clustering of samples by functional profiles.'),
(77609, 2013, 'bio', 'TrioVis: a visualization approach for filtering genomic variants of parent-child trios', 'Sakai, Ryo|Sifrim, Alejandro|Vande Moere, Andrew|Aerts, Jan', 'Department of Electrical Engineering-ESAT, KU Leuven, SCD-SISTA, Leuven 3001, Belgium. ryo.sakai@esat.kuleuven.be|Department of Electrical Engineering-ESAT, KU Leuven, SCD-SISTA, Leuven 3001, Belgium. ryo.sakai@esat.kuleuven.be|Department of Electrical Engineering-ESAT, KU Leuven, SCD-SISTA, Leuven 3001, Belgium. ryo.sakai@esat.kuleuven.be|Department of Electrical Engineering-ESAT, KU Leuven, SCD-SISTA, Leuven 3001, Belgium. ryo.sakai@esat.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium', 4, 'Child|Computer Graphics|Exome|Genetic Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Parents|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt267', '23658417', 'TrioVis is a visual analytics tool developed for filtering on coverage and variant frequency for genomic variants from exome sequencing of parent-child trios. In TrioVis, the variant data are organized by grouping each variant based on the laws of Mendelian inheritance. Taking three Variant Call Format files as input, TrioVis allows the user to test different coverage thresholds (i.e. different levels of stringency), to find the optimal threshold values tailored to their hypotheses and to gain insights into the global effects of filtering through interaction.'),
(77610, 2013, 'bio', 'PconsC: combination of direct information methods and alignments improves contact prediction', 'Skwark, Marcin J|Abdel-Rehim, Abbi|Elofsson, Arne', 'Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden.|Department of Biochemistry and Biophysics, Stockholm University, 10691 Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 49, 'Algorithms|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btt259', '23658418', 'Recently, several new contact prediction methods have been published. They use (i) large sets of multiple aligned sequences and (ii) assume that correlations between columns in these alignments can be the results of indirect interaction. These methods are clearly superior to earlier methods when it comes to predicting contacts in proteins. Here, we demonstrate that combining predictions from two prediction methods, PSICOV and plmDCA, and two alignment methods, HHblits and jackhmmer at four different e-value cut-offs, provides a relative improvement of 20% in comparison with the best single method, exceeding 70% correct predictions for one contact prediction per residue.'),
(77611, 2013, 'bio', 'DAPPLE: a pipeline for the homology-based prediction of phosphorylation sites', 'Trost, Brett|Arsenault, Ryan|Griebel, Philip|Napper, Scott|Kusalik, Anthony', 'Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca|Department of Computer Science, University of Saskatchewan, Saskatoon, SK S7N 5C9, Canada. brett.trost@usask.ca', 'Canada|Canada|Canada|Canada|Canada', 30, 'Animals|Cattle|Humans|Phosphoproteins|Phosphorylation|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/btt265', '23658419', 'While many experimentally characterized phosphorylation sites exist for certain organisms, such as human, rat and mouse, few sites are known for other organisms, hampering related research efforts. We have developed a software pipeline called DAPPLE that automates the process of using known phosphorylation sites from other organisms to identify putative sites in an organism of interest.'),
(77612, 2013, 'bio', 'Twine: display and analysis of cis-regulatory modules', 'Pearson, Joseph C|Crews, Stephen T', 'Department of Biochemistry and Biophysics and Program in Molecular Biology and Biotechnology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3280, USA.|Department of Biochemistry and Biophysics and Program in Molecular Biology and Biotechnology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-3280, USA.', 'United States|United States', 4, 'Animals|Binding Sites|Computer Graphics|Enhancer Elements, Genetic|Nucleotide Motifs|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt264', '23658420', 'Many algorithms analyze enhancers for overrepresentation of known and novel motifs, with the goal of identifying binding sites for direct regulators of gene expression. Twine is a Java GUI with multiple graphical representations (Views) of enhancer alignments that displays motifs, as IUPAC consensus sequences or position frequency matrices, in the context of phylogenetic conservation to facilitate cis-regulatory element discovery. Thresholds of phylogenetic conservation and motif stringency can be altered dynamically to facilitate detailed analysis of enhancer architecture. Views can be exported to vector graphics programs to generate high-quality figures for publication. Twine can be extended via Java plugins to manipulate alignments and analyze sequences.'),
(77613, 2013, 'bio', 'Detection of significantly differentially methylated regions in targeted bisulfite sequencing data', 'Hebestreit, Katja|Dugas, Martin|Klein, Hans-Ulrich', 'Institute of Medical Informatics, University of Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany. katja.hebestreit@uni-muenster.de|Institute of Medical Informatics, University of Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany. katja.hebestreit@uni-muenster.de|Institute of Medical Informatics, University of Münster, Albert-Schweitzer-Campus 1, 48149 Münster, Germany. katja.hebestreit@uni-muenster.de', 'Germany|Germany|Germany', 120, 'Algorithms|CpG Islands|DNA Methylation|Genome, Human|Humans|Leukemia, Promyelocytic, Acute|Sequence Analysis, DNA|Software|Sulfites', 'Journal Article', '10.1093/bioinformatics/btt263', '23658421', 'Bisulfite sequencing is currently the gold standard to obtain genome-wide DNA methylation profiles in eukaryotes. In contrast to the rapid development of appropriate pre-processing and alignment software, methods for analyzing the resulting methylation profiles are relatively limited so far. For instance, an appropriate pipeline to detect DNA methylation differences between cancer and control samples is still required.'),
(77614, 2013, 'bio', 'FYPO: the fission yeast phenotype ontology', 'Harris, Midori A|Lock, Antonia|Bähler, Jürg|Oliver, Stephen G|Wood, Valerie', 'Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK. mah79@cam.ac.uk|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK. mah79@cam.ac.uk|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK. mah79@cam.ac.uk|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK. mah79@cam.ac.uk|Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Sanger Building, 80 Tennis Court Road, Cambridge CB2 1GA, UK. mah79@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 32, 'Biological Ontologies|Databases, Genetic|Gene Ontology|Phenotype|Schizosaccharomyces', 'Journal Article', '10.1093/bioinformatics/btt266', '23658422', 'To provide consistent computable descriptions of phenotype data, PomBase is developing a formal ontology of phenotypes observed in fission yeast.'),
(77615, 2013, 'bio', 'CMAP: Complement Map Database', 'Yang, Kun|Dinasarapu, Ashok R|Reis, Edimara S|Deangelis, Robert A|Ricklin, Daniel|Subramaniam, Shankar|Lambris, John D', 'Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.|Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Complement C5a|Complement System Proteins|Databases, Protein|Humans|Proteins', 'Journal Article', '10.1093/bioinformatics/btt269', '23661693', 'The human complement system is increasingly perceived as an intricate protein network of effectors, inhibitors and regulators that drives critical processes in health and disease and extensively communicates with associated physiological pathways ranging from immunity and inflammation to homeostasis and development. A steady stream of experimental data reveals new fascinating connections at a rapid pace, although opening unique opportunities for research discoveries, the comprehensiveness and large diversity of experimental methods, nomenclatures and publication sources renders it highly challenging to keep up with the essential findings. With the Complement Map Database (CMAP), we have created a novel and easily accessible research tool to assist the complement community and scientists from related disciplines in exploring the complement network and discovering new connections.'),
(77616, 2014, 'bio', 'Adaptive reference-free compression of sequence quality scores', 'Janin, Lilian|Rosone, Giovanna|Cox, Anthony J', 'Computational Biology Group, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK and Dipartimento di Matematica e Informatica, University of Palermo, Via Archirafi 34, 90123 Palermo, Italy.|Computational Biology Group, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK and Dipartimento di Matematica e Informatica, University of Palermo, Via Archirafi 34, 90123 Palermo, Italy.|Computational Biology Group, Illumina Cambridge Ltd., Chesterford Research Park, Little Chesterford, Essex CB10 1XL, UK and Dipartimento di Matematica e Informatica, University of Palermo, Via Archirafi 34, 90123 Palermo, Italy.', 'Italy|Italy|Italy', 29, 'Algorithms|Animals|Caenorhabditis elegans|Data Compression|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Metagenomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btt257', '23661694', 'Rapid technological progress in DNA sequencing has stimulated interest in compressing the vast datasets that are now routinely produced. Relatively little attention has been paid to compressing the quality scores that are assigned to each sequence, even though these scores may be harder to compress than the sequences themselves. By aggregating a set of reads into a compressed index, we find that the majority of bases can be predicted from the sequence of bases that are adjacent to them and, hence, are likely to be less informative for variant calling or other applications. The quality scores for such bases are aggressively compressed, leaving a relatively small number at full resolution. As our approach relies directly on redundancy present in the reads, it does not need a reference sequence and is, therefore, applicable to data from metagenomics and de novo experiments as well as to re-sequencing data.'),
(77617, 2013, 'bio', 'iFUSE: integrated fusion gene explorer', 'Hiltemann, Saskia|McClellan, Elizabeth A|van Nijnatten, Jos|Horsman, Sebastiaan|Palli, Ivo|Teles Alves, Ines|Hartjes, Thomas|Trapman, Jan|van der Spek, Peter|Jenster, Guido|Stubbs, Andrew', 'Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl|Department of Urology, Erasmus MC, 3015 GE Rotterdam, The Netherlands. s.hiltemann@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 5, 'Gene Fusion|Genes, Neoplasm|Genomic Structural Variation|Genomics|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btt252', '23661695', 'We present iFUSE (integrated fusion gene explorer), an online visualization tool that provides a fast and informative view of structural variation data and prioritizes those breaks likely representing fusion genes. This application uses calculated break points to determine fusion genes based on the latest annotation for genomic sequence information, and where relevant the structural variation (SV) events are annotated with predicted RNA and protein sequences. iFUSE takes as input a Complete Genomics (CG) junction file, a FusionMap fusion detection report file or a file already analysed and annotated by the iFUSE application on a previous occasion.'),
(77618, 2013, 'bio', 'pyDockWEB: a web server for rigid-body protein-protein docking using electrostatics and desolvation scoring', 'Jiménez-García, Brian|Pons, Carles|Fernández-Recio, Juan', 'Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, National Institute of Bioinformatics, Jordi Girona 29, 08034 Barcelona, Spain.|Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, National Institute of Bioinformatics, Jordi Girona 29, 08034 Barcelona, Spain.|Joint BSC-IRB Research Programme in Computational Biology, Department of Life Sciences, Barcelona Supercomputing Center, National Institute of Bioinformatics, Jordi Girona 29, 08034 Barcelona, Spain.', 'Spain|Spain|Spain', 103, 'Algorithms|Internet|Molecular Docking Simulation|Multiprotein Complexes|Protein Interaction Mapping|Software|Static Electricity', 'Journal Article', '10.1093/bioinformatics/btt262', '23661696', 'pyDockWEB is a web server for the rigid-body docking prediction of protein-protein complex structures using a new version of the pyDock scoring algorithm. We use here a new custom parallel FTDock implementation, with adjusted grid size for optimal FFT calculations, and a new version of pyDock, which dramatically speeds up calculations while keeping the same predictive accuracy. Given the 3D coordinates of two interacting proteins, pyDockWEB returns the best docking orientations as scored mainly by electrostatics and desolvation energy.'),
(77619, 2013, 'bio', 'International Society for Computational Biology honors Goncalo Abecasis with top bioinformatics/computational biology award for 2013', 'Fogg, Christiana N|Kovats, Diane E', 'International Society for Computational Biology, La Jolla, CA, USA.|International Society for Computational Biology, La Jolla, CA, USA.', 'United States|United States', 0, 'Awards and Prizes|Computational Biology|History, 21st Century|Humans|Michigan|Societies, Scientific', 'Biography', '10.1093/bioinformatics/btt251', '23661697', '-'),
(77620, 2013, 'bio', 'GAGE-B: an evaluation of genome assemblers for bacterial organisms', 'Magoc, Tanja|Pabinger, Stephan|Canzar, Stefan|Liu, Xinyue|Su, Qi|Puiu, Daniela|Tallon, Luke J|Salzberg, Steven L', 'Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.|Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21025, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 97, 'Algorithms|Gene Library|Genome, Bacterial|Genomics|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btt273', '23665771', 'A large and rapidly growing number of bacterial organisms have been sequenced by the newest sequencing technologies. Cheaper and faster sequencing technologies make it easy to generate very high coverage of bacterial genomes, but these advances mean that DNA preparation costs can exceed the cost of sequencing for small genomes. The need to contain costs often results in the creation of only a single sequencing library, which in turn introduces new challenges for genome assembly methods.'),
(77621, 2013, 'bio', 'A combinatorial approach to the peptide feature matching problem for label-free quantification', 'Lin, Hao|He, Lin|Ma, Bin', 'David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.|David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.|David R. Cheriton School of Computer Science, University of Waterloo, Waterloo, Ontario, Canada N2L 3G1.', 'Canada|Canada|Canada', 35, 'Algorithms|Chromatography, Liquid|Mass Spectrometry|Peptides|Software', 'Journal Article', '10.1093/bioinformatics/btt274', '23665772', 'Label-free quantification is an important approach to identify biomarkers, as it measures the quantity change of peptides across different biological samples. One of the fundamental steps for label-free quantification is to match the peptide features that are detected in two datasets to each other. Although ad hoc software tools exist for the feature matching, the definition of a combinatorial model for this problem is still not available.'),
(77622, 2014, 'bio', 'A statistical framework for power calculations in ChIP-seq experiments', 'Zuo, Chandler|Kelexc5x9f, Sxc3xbcndxc3xbcz', 'Department of Statistics, and Department of Biostatistics and Medical Informatics, 1300 University Avenue, Madison, WI 53706, USA.|Department of Statistics, and Department of Biostatistics and Medical Informatics, 1300 University Avenue, Madison, WI 53706, USA.', 'United States|United States', 0, 'Chromatin Immunoprecipitation|Escherichia coli|High-Throughput Nucleotide Sequencing|Oligonucleotide Array Sequence Analysis|Pilot Projects', 'Journal Article', '10.1093/bioinformatics/btt200', '23665773', 'ChIP-seq technology enables investigators to study genome-wide binding of transcription factors and mapping of epigenomic marks. Although the availability of basic analysis tools for ChIP-seq data is rapidly increasing, there has not been much progress on the related design issues. A challenging question for designing a ChIP-seq experiment is how deeply should the ChIP and the control samples be sequenced? The answer depends on multiple factors some of which can be set by the experimenter based on pilot/preliminary data. The sequencing depth of a ChIP-seq experiment is one of the key factors that determine whether all the underlying targets (e.g. binding locations or epigenomic profiles) can be identified with a targeted power.'),
(77623, 2013, 'bio', 'MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics', 'Wei, Xiaoli|Shi, Xue|Koo, Imhoi|Kim, Seongho|Schmidt, Robin H|Arteel, Gavin E|Watson, Walter H|McClain, Craig|Zhang, Xiang', 'Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.|Department of Chemistry, Department of Bioinformatics and Biostatistics, Department of Pharmacology & Toxicology, Alcohol Research Center, Department of Medicine, University of Louisville and Robley Rex Louisville VAMC, Louisville, KY 40292, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 37, 'Animals|Gas Chromatography-Mass Spectrometry|Metabolome|Metabolomics|Mice|Software', 'Journal Article', '10.1093/bioinformatics/btt275', '23665844', 'Due to the high complexity of metabolome, the comprehensive 2D gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) is considered as a powerful analytical platform for metabolomics study. However, the applications of GC×GC-TOF MS in metabolomics are not popular owing to the lack of bioinformatics system for data analysis.'),
(77624, 2012, 'bio', 'Proceedings of the 11th European Conference on Computational Biology, ECCB 2012, September 9-12, 2012, Basal, Switzerland', '-', '-', '-', 37, 'Animals|Computational Biology|Humans|Molecular Biology', 'Congress', '10.1093/bioinformatics/btt275', '23675586', '-'),
(77625, 2013, 'bio', 'A hierarchical model of transcriptional dynamics allows robust estimation of transcription rates in populations of single cells with variable gene copy number', 'Woodcock, Dan J|Vance, Keith W|Komorowski, Michal|Koentges, Georgy|Finkenstädt, Bärbel|Rand, David A', 'Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk|Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk|Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk|Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk|Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk|Warwick Systems Biology Centre and Department of Life Sciences, University of Warwick, Coventry, CV4 7AL, UK. d.j.woodcock@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Bayes Theorem|Cell Line|Enhancer Elements, Genetic|Gene Dosage|MSX1 Transcription Factor|Mice|Models, Genetic|Promoter Regions, Genetic|Single-Cell Analysis|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btt201', '23677939', 'cis-regulatory DNA sequence elements, such as enhancers and silencers, function to control the spatial and temporal expression of their target genes. Although the overall levels of gene expression in large cell populations seem to be precisely controlled, transcription of individual genes in single cells is extremely variable in real time. It is, therefore, important to understand how these cis-regulatory elements function to dynamically control transcription at single-cell resolution. Recently, statistical methods have been proposed to back calculate the rates involved in mRNA transcription using parameter estimation of a mathematical model of transcription and translation. However, a major complication in these approaches is that some of the parameters, particularly those corresponding to the gene copy number and transcription rate, cannot be distinguished, therefore, these methods cannot be used when the copy number is unknown.'),
(77626, 2013, 'bio', 'Identification of hidden relationships from the coupling of hydrophobic cluster analysis and domain architecture information', 'Faure, Guilhem|Callebaut, Isabelle', 'IMPMC, UMR7590, CNRS, Universitxc3xa9 Pierre et Marie Curie-Paris6, Paris Cedex 05, France.|IMPMC, UMR7590, CNRS, Universitxc3xa9 Pierre et Marie Curie-Paris6, Paris Cedex 05, France.', 'France|France', 17, 'Amino Acid Sequence|Cluster Analysis|Humans|Hydrophobic and Hydrophilic Interactions|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Transcription Factor TFIID', 'Journal Article', '10.1093/bioinformatics/btt271', '23677940', 'Describing domain architecture is a critical step in the functional characterization of proteins. However, some orphan domains do not match any profile stored in dedicated domain databases and are thereby difficult to analyze.'),
(77627, 2013, 'bio', 'Relation between sequence and structure in membrane proteins', 'Olivella, Mireia|Gonzalez, Angel|Pardo, Leonardo|Deupi, Xavier', 'Grup de Recerca en Bioinformxc3xa0tica i Estadxc3xadstica Mxc3xa8dica, Departament de Biologia de Sistemes, Escola Politxc3xa8cnica Superior, Universitat de Vic, 08500 Vic, Barcelona, Catalonia, Spain. Mireia.Olivella@uvic.cat|Grup de Recerca en Bioinformxc3xa0tica i Estadxc3xadstica Mxc3xa8dica, Departament de Biologia de Sistemes, Escola Politxc3xa8cnica Superior, Universitat de Vic, 08500 Vic, Barcelona, Catalonia, Spain. Mireia.Olivella@uvic.cat|Grup de Recerca en Bioinformxc3xa0tica i Estadxc3xadstica Mxc3xa8dica, Departament de Biologia de Sistemes, Escola Politxc3xa8cnica Superior, Universitat de Vic, 08500 Vic, Barcelona, Catalonia, Spain. Mireia.Olivella@uvic.cat|Grup de Recerca en Bioinformxc3xa0tica i Estadxc3xadstica Mxc3xa8dica, Departament de Biologia de Sistemes, Escola Politxc3xa8cnica Superior, Universitat de Vic, 08500 Vic, Barcelona, Catalonia, Spain. Mireia.Olivella@uvic.cat', 'Spain|Spain|Spain|Spain', 0, 'Amino Acid Sequence|Conserved Sequence|Membrane Proteins|Protein Structure, Secondary|Protein Structure, Tertiary|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/btt249', '23677941', 'Integral polytopic membrane proteins contain only two types of folds in their transmembrane domains: xcexb1-helix bundles and xcexb2-barrels. The increasing number of available crystal structures of these proteins permits an initial estimation of how sequence variability affects the structure conservation in their transmembrane domains. We, thus, aim to determine the pairwise sequence identity necessary to maintain the transmembrane molecular architectures compatible with the hydrophobic nature of the lipid bilayer.'),
(77628, 2013, 'bio', 'PconsD: ultra rapid, accurate model quality assessment for protein structure prediction', 'Skwark, Marcin J|Elofsson, Arne', 'Department of Biochemistry and Biophysics, Science for Life Laboratory, Swedish E-Science Research Center, Stockholm University, Box 1031, 17121 Solna, Sweden.|Department of Biochemistry and Biophysics, Science for Life Laboratory, Swedish E-Science Research Center, Stockholm University, Box 1031, 17121 Solna, Sweden.', 'Sweden|Sweden', 22, 'Cluster Analysis|Computational Biology|Models, Molecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt272', '23677942', 'Clustering methods are often needed for accurately assessing the quality of modeled protein structures. Recent blind evaluation of quality assessment methods in CASP10 showed that there is little difference between many different methods as far as ranking models and selecting best model are concerned. When comparing many models, the computational cost of the model comparison can become significant. Here, we present PconsD, a fast, stream-computing method for distance-driven model quality assessment that runs on consumer hardware. PconsD is at least one order of magnitude faster than other methods of comparable accuracy.'),
(77629, 2013, 'bio', 'Updating RNA-Seq analyses after re-annotation', 'Roberts, Adam|Schaeffer, Lorian|Pachter, Lior', 'Department of Computer Science, University of Calofornia Berkeley, Berkeley, CA 94720, USA.|Department of Computer Science, University of Calofornia Berkeley, Berkeley, CA 94720, USA.|Department of Computer Science, University of Calofornia Berkeley, Berkeley, CA 94720, USA.', 'United States|United States|United States', 0, 'Algorithms|Animals|Gene Expression Profiling|Mice|Molecular Sequence Annotation|RNA Isoforms|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt197', '23677943', 'The estimation of isoform abundances from RNA-Seq data requires a time-intensive step of mapping reads to either an assembled or previously annotated transcriptome, followed by an optimization procedure for deconvolution of multi-mapping reads. These procedures are essential for downstream analysis such as differential expression. In cases where it is desirable to adjust the underlying annotation, for example, on the discovery of novel isoforms or errors in existing annotations, current pipelines must be rerun from scratch. This makes it difficult to update abundance estimates after re-annotation, or to explore the effect of changes in the transcriptome on analyses. We present a novel efficient algorithm for updating abundance estimates from RNA-Seq experiments on re-annotation that does not require re-analysis of the entire dataset. Our approach is based on a fast partitioning algorithm for identifying transcripts whose abundances may depend on the added or deleted isoforms, and on a fast follow-up approach to re-estimating abundances for all transcripts. We demonstrate the effectiveness of our methods by showing how to synchronize RNA-Seq abundance estimates with the daily RefSeq incremental updates. Thus, we provide a practical approach to maintaining relevant databases of RNA-Seq derived abundance estimates even as annotations are being constantly revised.'),
(77630, 2013, 'bio', 'ReviSTER: an automated pipeline to revise misaligned reads to simple tandem repeats', 'Tae, Hongseok|McMahon, Kevin W|Settlage, Robert E|Bavarva, Jasmin H|Garner, Harold R', 'Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Blacksburg, VA 24061, USA.', 'United States|United States|United States|United States|United States', 0, 'Alleles|Exome|Genomics|Genotyping Techniques|Haploidy|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software|Tandem Repeat Sequences', 'Journal Article', '10.1093/bioinformatics/btt277', '23677944', 'Simple tandem repeats are highly variable genetic elements and widespread in genomes of many organisms. Next-generation sequencing technologies have enabled a robust comparison of large numbers of simple tandem repeat loci, however, analysis of their variation using traditional sequence analysis approaches still remains limiting and problematic due to variants occurring in repeat sequences confusing alignment programs into mapping sequence reads to incorrect loci when the sequence reads are significantly different from the reference sequence.'),
(77631, 2013, 'bio', 'DrugMap Central: an on-line query and visualization tool to facilitate drug repositioning studies', 'Fu, Changhe|Jin, Guangxu|Gao, Junfeng|Zhu, Rui|Ballesteros-Villagrana, Efren|Wong, Stephen T C', 'Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.|Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.|Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.|Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.|Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.|Department of Systems Medicine and Bioengineering, The Methodist Hospital Research Institute, Weill Cornell Medical College.', '-|-|-|-|-|-', 19, 'Computer Graphics|Databases, Pharmaceutical|Drug Repositioning|Humans|Internet|Pharmaceutical Preparations|Software|United States|United States Food and Drug Administration', 'Journal Article', '10.1093/bioinformatics/btt279', '23681121', 'Systematic studies of drug repositioning require the integration of multi-level drug data, including basic chemical information (such as SMILES), drug targets, target-related signaling pathways, clinical trial information and Food and Drug Administration (FDA)-approval information, to predict new potential indications of existing drugs. Currently available databases, however, lack query support for multi-level drug information and thus are not designed to support drug repositioning studies. DrugMap Central (DMC), an online tool, is developed to help fill the gap. DMC enables the users to integrate, query, visualize, interrogate, and download multi-level data of known drugs or compounds quickly for drug repositioning studies all within one system.'),
(77632, 2013, 'bio', 'CAPITO--a web server-based analysis and plotting tool for circular dichroism data', 'Wiedemann, Christoph|Bellstedt, Peter|Görlach, Matthias', 'Biomolecular NMR Spectroscopy, Leibniz Institute for Age Research-Fritz Lipmann Institute, Beutenbergstr. 11, 07745 Jena, Germany. cwiede@fli-leibniz.de|Biomolecular NMR Spectroscopy, Leibniz Institute for Age Research-Fritz Lipmann Institute, Beutenbergstr. 11, 07745 Jena, Germany. cwiede@fli-leibniz.de|Biomolecular NMR Spectroscopy, Leibniz Institute for Age Research-Fritz Lipmann Institute, Beutenbergstr. 11, 07745 Jena, Germany. cwiede@fli-leibniz.de', 'Germany|Germany|Germany', 112, 'Circular Dichroism|Internet|Protein Folding|Protein Structure, Secondary|Software', 'Journal Article', '10.1093/bioinformatics/btt278', '23681122', 'Circular dichroism (CD) spectroscopy is one of the most versatile tools to study protein folding and to validate the proper fold of purified proteins. Here, we aim to provide a readily accessible, user-friendly and platform-independent tool capable of analysing multiple CD datasets of virtually any format and returning results as high-quality graphical output to the user.'),
(77633, 2013, 'bio', 'TANGO: a generic tool for high-throughput 3D image analysis for studying nuclear organization', 'Ollion, Jean|Cochennec, Julien|Loll, François|Escudé, Christophe|Boudier, Thomas', 'CNRS UMR7196, INSERM U565, MNHN, 43 rue Cuvier 75005 Paris, France.|CNRS UMR7196, INSERM U565, MNHN, 43 rue Cuvier 75005 Paris, France.|CNRS UMR7196, INSERM U565, MNHN, 43 rue Cuvier 75005 Paris, France.|CNRS UMR7196, INSERM U565, MNHN, 43 rue Cuvier 75005 Paris, France.|CNRS UMR7196, INSERM U565, MNHN, 43 rue Cuvier 75005 Paris, France.', 'France|France|France|France|France', 0, 'Cell Nucleus|Genome|Imaging, Three-Dimensional|Microscopy, Fluorescence|Software', 'Journal Article', '10.1093/bioinformatics/btt276', '23681123', 'The cell nucleus is a highly organized cellular organelle that contains the genetic material. The study of nuclear architecture has become an important field of cellular biology. Extracting quantitative data from 3D fluorescence imaging helps understand the functions of different nuclear compartments. However, such approaches are limited by the requirement for processing and analyzing large sets of images.'),
(77634, 2013, 'bio', 'ACCUSA2: multi-purpose SNV calling enhanced by probabilistic integration of quality scores', 'Piechotta, Michael|Dieterich, Christoph', 'Bioinformatics in Quantitative Biology, The Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin-Buch, Germany.|Bioinformatics in Quantitative Biology, The Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin-Buch, Germany.', 'Germany|Germany', 1, 'Genetic Variation|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Probability|Software', 'Journal Article', '10.1093/bioinformatics/btt268', '23681124', 'Direct comparisons of assembled short-read stacks are one way to identify single-nucleotide variants. Single-nucleotide variant detection is especially challenging across samples with different read depths (e.g. RNA-Seq) and high-background levels (e.g. selection experiments). We present ACCUSA2 to identify variant positions where nucleotide frequency spectra differ between two samples. To this end, ACCUSA2 integrates quality scores for base calling and read mapping into a common framework. Our benchmarks demonstrate that ACCUSA2 is superior to a state-of-the-art SNV caller in situations of diverging read depths and reliably detects subtle differences among sample nucleotide frequency spectra. Additionally, we show that ACCUSA2 is fast and robust against base quality score deviations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77635, 2013, 'bio', 'MEME-LaB: motif analysis in clusters', 'Brown, Paul|Baxter, Laura|Hickman, Richard|Beynon, Jim|Moore, Jonathan D|Ott, Sascha', 'Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk|Warwick Systems Biology Centre, University of Warwick, Coventry CV4 7AL, UK. p.e.brown@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Binding Sites|Cluster Analysis|Internet|Nucleotide Motifs|Promoter Regions, Genetic|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt248', '23681125', 'Genome-wide expression analysis can result in large numbers of clusters of co-expressed genes. Although there are tools for ab initio discovery of transcription factor-binding sites, most do not provide a quick and easy way to study large numbers of clusters. To address this, we introduce a web tool called MEME-LaB. The tool wraps MEME (an ab initio motif finder), providing an interface for users to input multiple gene clusters, retrieve promoter sequences, run motif finding and then easily browse and condense the results, facilitating better interpretation of the results from large-scale datasets.'),
(77636, 2014, 'bio', 'Specificity control for read alignments using an artificial reference genome-guided false discovery rate', 'Giese, Sven H|Zickmann, Franziska|Renard, Bernhard Y', 'Research Group Bioinformatics (NG4), Robert Koch-Institut, Nordufer 20, 13353 Berlin, Germany.|Research Group Bioinformatics (NG4), Robert Koch-Institut, Nordufer 20, 13353 Berlin, Germany.|Research Group Bioinformatics (NG4), Robert Koch-Institut, Nordufer 20, 13353 Berlin, Germany.', 'Germany|Germany|Germany', 5, 'Algorithms|Amino Acid Sequence|Animals|Base Sequence|Caenorhabditis elegans|Genome|High-Throughput Nucleotide Sequencing|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btt255', '23685787', 'Accurate estimation, comparison and evaluation of read mapping error rates is a crucial step in the processing of next-generation sequencing data, as further analysis steps and interpretation assume the correctness of the mapping results. Current approaches are either focused on sensitivity estimation and thereby disregard specificity or are based on read simulations. Although continuously improving, read simulations are still prone to introduce a bias into the mapping error quantitation and cannot capture all characteristics of an individual dataset.'),
(77637, 2013, 'bio', 'NETAL: a new graph-based method for global alignment of protein-protein interaction networks', 'Neyshabur, Behnam|Khadem, Ahmadreza|Hashemifar, Somaye|Arab, Seyed Shahriar', 'Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.|Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.|Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.|Department of Computer Engineering, Sharif University of Technology, Tehran, Iran.', '-|-|-|-', 0, 'Algorithms|Computer Graphics|Humans|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btt202', '23696650', 'The interactions among proteins and the resulting networks of such interactions have a central role in cell biology. Aligning these networks gives us important information, such as conserved complexes and evolutionary relationships. Although there have been several publications on the global alignment of protein networks, however, none of proposed methods are able to produce a highly conserved and meaningful alignment. Moreover, time complexity of current algorithms makes them impossible to use for multiple alignment of several large networks together.'),
(77638, 2013, 'bio', 'TiPs: a database of therapeutic targets in pathogens and associated tools', 'Lepore, Rosalba|Tramontano, Anna|Via, Allegra', 'Department of Physics, Sapienza University, 00185 Rome, Italy.|Department of Physics, Sapienza University, 00185 Rome, Italy.|Department of Physics, Sapienza University, 00185 Rome, Italy.', 'Italy|Italy|Italy', 0, 'Binding Sites|Databases, Pharmaceutical|Drug Discovery|Humans|Infection|Models, Molecular|Pharmaceutical Preparations|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt289', '23698860', 'The need for new drugs and new targets is particularly compelling in an era that is witnessing an alarming increase of drug resistance in human pathogens. The identification of new targets of known drugs is a promising approach, which has proven successful in several cases. Here, we describe a database that includes information on 5153 putative drug-target pairs for 150 human pathogens derived from available drug-target crystallographic complexes.'),
(77639, 2013, 'bio', 'MASS: meta-analysis of score statistics for sequencing studies', 'Tang, Zheng-Zheng|Lin, Dan-Yu', 'Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599-7420, USA.|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599-7420, USA.', 'United States|United States', 28, 'Data Interpretation, Statistical|Genetic Variation|Humans|Meta-Analysis as Topic|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt280', '23698861', 'MASS is a command-line program to perform meta-analysis of sequencing studies by combining the score statistics from multiple studies. It implements three types of multivariate tests that encompass all commonly used association tests for rare variants. The input files can be generated from the accompanying software SCORE-Seq. This bundle of programs allows analysis of large sequencing studies in a time and memory efficient manner.'),
(77640, 2013, 'bio', 'ShereKhan--calculating exchange parameters in relaxation dispersion data from CPMG experiments', 'Mazur, Adam|Hammesfahr, Björn|Griesinger, Christian|Lee, Donghan|Kollmar, Martin', 'Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.|Department of NMR-based Structural Biology, Max-Planck-Institute for Biophysical Chemistry, Am Fassberg 11, 37077 Göttingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 7, 'Internet|Nuclear Magnetic Resonance, Biomolecular|Software', 'Journal Article', '10.1093/bioinformatics/btt286', '23698862', 'Dynamics governing the function of biomolecule is usually described as exchange processes and can be monitored at atomic resolution with nuclear magnetic resonance (NMR) relaxation dispersion data. Here, we present a new tool for the analysis of CPMG relaxation dispersion profiles (ShereKhan). The web interface to ShereKhan provides a user-friendly environment for the analysis.'),
(77641, 2013, 'bio', 'Assembling the 20 Gb white spruce (Picea glauca) genome from whole-genome shotgun sequencing data', 'Birol, Inanc|Raymond, Anthony|Jackman, Shaun D|Pleasance, Stephen|Coope, Robin|Taylor, Greg A|Yuen, Macaire Man Saint|Keeling, Christopher I|Brand, Dana|Vandervalk, Benjamin P|Kirk, Heather|Pandoh, Pawan|Moore, Richard A|Zhao, Yongjun|Mungall, Andrew J|Jaquish, Barry|Yanchuk, Alvin|Ritland, Carol|Boyle, Brian|Bousquet, Jean|Ritland, Kermit|Mackay, John|Bohlmann, Jörg|Jones, Steven J M', 'Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Agency, Vancouver, BC V5Z 4S6, Canada. ibirol@bcgsc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Ca', 0, 'Base Sequence|Genome, Plant|Genomics|Molecular Sequence Data|Picea|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt178', '23698863', 'White spruce (Picea glauca) is a dominant conifer of the boreal forests of North America, and providing genomics resources for this commercially valuable tree will help improve forest management and conservation efforts. Sequencing and assembling the large and highly repetitive spruce genome though pushes the boundaries of the current technology. Here, we describe a whole-genome shotgun sequencing strategy using two Illumina sequencing platforms and an assembly approach using the ABySS software. We report a 20.8 giga base pairs draft genome in 4.9 million scaffolds, with a scaffold N50 of 20,356 bp. We demonstrate how recent improvements in the sequencing technology, especially increasing read lengths and paired end reads from longer fragments have a major impact on the assembly contiguity. We also note that scalable bioinformatics tools are instrumental in providing rapid draft assemblies.'),
(77642, 2013, 'bio', 'Triplex: an R/Bioconductor package for identification and visualization of potential intramolecular triplex patterns in DNA sequences', 'Hon, Jixc5x99xc3xad|Martxc3xadnek, Tomxc3xa1xc5xa1|Rajdl, Kamil|Lexa, Matej', 'Department of Computer Systems, Faculty of Information Technology, Brno Technical University, Boxc5xbeetxc4x9bchova 2, 61266 Brno, Czech Republic.|Department of Computer Systems, Faculty of Information Technology, Brno Technical University, Boxc5xbeetxc4x9bchova 2, 61266 Brno, Czech Republic.|Department of Computer Systems, Faculty of Information Technology, Brno Technical University, Boxc5xbeetxc4x9bchova 2, 61266 Brno, Czech Republic.|Department of Computer Systems, Faculty of Information Technology, Brno Technical University, Boxc5xbeetxc4x9bchova 2, 61266 Brno, Czech Republic.', '-|-|-|-', 0, 'Algorithms|Computer Graphics|DNA|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt299', '23709494', 'Upgrade and integration of triplex software into the R/Bioconductor framework.'),
(77643, 2013, 'bio', 'miRTCat: a comprehensive map of human and mouse microRNA target sites including non-canonical nucleation bulges', 'Kim, Ka-Kyung|Ham, Juyoung|Chi, Sung Wook', 'Samsung Biomedical Research Institute, Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University and Samsung Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea.|Samsung Biomedical Research Institute, Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University and Samsung Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea.|Samsung Biomedical Research Institute, Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University and Samsung Research Institute for Future Medicine, Samsung Medical Center, 81 Irwon-ro, Gangnam-gu, Seoul 135-710, Korea.', '-|-|-', 11, '3 Untranslated Regions|Animals|Base Sequence|Conserved Sequence|Humans|Mice|MicroRNAs|Software', 'Journal Article', '10.1093/bioinformatics/btt296', '23709495', 'MicroRNAs (miRNAs) regulate various biological functions by binding hundreds of transcripts to impart post-transcriptional repression. Recently, by applying a transcriptome-wide experimental method for identifying miRNA target sites (Ago HITS-CLIP), a novel non-canonical target site, named nucleation bulge, was discovered as widespread, functional and evolutionally conserved. Although such non-canonical nucleation bulges have been proven to be predictive by using pivot pairing rule and sequence conservation, this approach has not been applied yet. To facilitate the functional studies of non-canonical miRNA targets, we implement miRTCat: a comprehensive searchable map of miRNA target sites, including non-canonical nucleation bulges, not only mapped in experimentally verified miRNA-bound regions but also predicted in all 3-untranslated regions (3-UTRs) derived from human and mouse (xe2x88xbc15.6% as expected false-positive results).'),
(77644, 2013, 'bio', 'PIUS: peptide identification by unbiased search', 'Costa, Eduardo P|Menschaert, Gerben|Luyten, Walter|De Grave, Kurt|Ramon, Jan', 'Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. eduardo.costa@cs.kuleuven.be|Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. eduardo.costa@cs.kuleuven.be|Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. eduardo.costa@cs.kuleuven.be|Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. eduardo.costa@cs.kuleuven.be|Department of Computer Science, KU Leuven, Celestijnenlaan 200A, B-3001 Heverlee, Belgium. eduardo.costa@cs.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Animals|Cell Line|Databases, Protein|Genome|Genomics|Mice|Peptides|Proteomics|Sequence Analysis, Protein|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btt298', '23709496', 'We present PIUS, a tool that identifies peptides from tandem mass spectrometry data by analyzing the six-frame translation of a complete genome. It differs from earlier studies that have performed such a genomic search in two ways: (i) it considers a larger search space and (ii) it is designed for natural peptide identification rather than proteomics. Differently from other peptidomics tools designed for genome-wide searches, PIUS does not limit the analysis to a set of sequences that match a list of de novo reconstructions.'),
(77645, 2013, 'bio', 'viRome: an R package for the visualization and analysis of viral small RNA sequence datasets', 'Watson, Mick|Schnettler, Esther|Kohl, Alain', 'ARK-Genomics, The Roslin Institute and Royal Dick School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG. mick.watson@roslin.ed.ac.uk|ARK-Genomics, The Roslin Institute and Royal Dick School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG. mick.watson@roslin.ed.ac.uk|ARK-Genomics, The Roslin Institute and Royal Dick School of Veterinary Studies, University of Edinburgh, Easter Bush, Midlothian EH25 9RG. mick.watson@roslin.ed.ac.uk', '-|-|-', 20, 'Computer Graphics|Genomics|RNA Interference|RNA, Small Untranslated|RNA, Viral|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt297', '23709497', 'RNA interference (RNAi) is known to play an important part in defence against viruses in a range of species. Second-generation sequencing technologies allow us to assay these systems and the small RNAs that play a key role with unprecedented depth. However, scientists need access to tools that can condense, analyse and display the resulting data. Here, we present viRome, a package for R that takes aligned sequence data and produces a range of essential plots and reports.'),
(77646, 2013, 'bio', 'DeMix: deconvolution for mixed cancer transcriptomes using raw measured data', 'Ahn, Jaeil|Yuan, Ying|Parmigiani, Giovanni|Suraokar, Milind B|Diao, Lixia|Wistuba, Ignacio I|Wang, Wenyi', 'Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Bioinformatics and Computational Biology and Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States|United States', 49, 'Algorithms|Animals|Computer Simulation|Gene Expression Profiling|Humans|Neoplasms|Rats', 'Journal Article', '10.1093/bioinformatics/btt301', '23712657', 'Tissue samples of tumor cells mixed with stromal cells cause underdetection of gene expression signatures associated with cancer prognosis or response to treatment. In silico dissection of mixed cell samples is essential for analyzing expression data generated in cancer studies. Currently, a systematic approach is lacking to address three challenges in computational deconvolution: (i) violation of linear addition of expression levels from multiple tissues when log-transformed microarray data are used, (ii) estimation of both tumor proportion and tumor-specific expression, when neither is known a priori, and (iii) estimation of expression profiles for individual patients.'),
(77647, 2013, 'bio', 'ChemMapper: a versatile web server for exploring pharmacology and chemical structure association based on molecular 3D similarity method', 'Gong, Jiayu|Cai, Chaoqian|Liu, Xiaofeng|Ku, Xin|Jiang, Hualiang|Gao, Daqi|Li, Honglin', 'School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China.', 'China|China|China|China|China|China|China', 105, 'Drug Discovery|Internet|Pharmaceutical Preparations|Software', 'Journal Article', '10.1093/bioinformatics/btt270', '23712658', 'ChemMapper is an online platform to predict polypharmacology effect and mode of action for small molecules based on 3D similarity computation. ChemMapper collects >350 000 chemical structures with bioactivities and associated target annotations (as well as >3 000 000 non-annotated compounds for virtual screening). Taking the user-provided chemical structure as the query, the top most similar compounds in terms of 3D similarity are returned with associated pharmacology annotations. ChemMapper is designed to provide versatile services in a variety of chemogenomics, drug repurposing, polypharmacology, novel bioactive compounds identification and scaffold hopping studies.'),
(77648, 2013, 'bio', 'Mutascope: sensitive detection of somatic mutations from deep amplicon sequencing', 'Yost, Shawn E|Alakus, Hakan|Matsui, Hiroko|Schwab, Richard B|Jepsen, Kristen|Frazer, Kelly A|Harismendy, Olivier', 'Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.|Bioinformatics Graduate Program, University of California San Diego, 9500 Gilman Drive, La Jolla, CA, USA.', 'United States|United States|United States|United States|United States|United States|United States', 20, 'DNA Mutational Analysis|High-Throughput Nucleotide Sequencing|Humans|Internet|Mutation|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btt305', '23712659', 'We present Mutascope, a sequencing analysis pipeline specifically developed for the identification of somatic variants present at low-allelic fraction from high-throughput sequencing of amplicons from matched tumor-normal specimen. Using datasets reproducing tumor genetic heterogeneity, we demonstrate that Mutascope has a higher sensitivity and generates fewer false-positive calls than tools designed for shotgun sequencing or diploid genomes.'),
(77649, 2013, 'bio', 'A method for finding consensus breakpoints in the cancer genome from copy number data', 'Toloxc5x9fi, Laura|Theixc3x9fen, Jessica|Halachev, Konstantin|Hero, Barbara|Berthold, Frank|Lengauer, Thomas', 'Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Campus E1.4, 66123 Saarbrxc3xbccken, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 6, 'Algorithms|Chromosome Breakpoints|DNA Copy Number Variations|Genome, Human|Genomics|Humans|Neoplasms|Neuroblastoma|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btt300', '23716195', 'Recurrent DNA breakpoints in cancer genomes indicate the presence of critical functional elements for tumor development. Identifying them can help determine new therapeutic targets. High-dimensional DNA microarray experiments like arrayCGH afford the identification of DNA copy number breakpoints with high precision, offering a solid basis for computational estimation of recurrent breakpoint locations.'),
(77650, 2013, 'bio', 'HitPick: a web server for hit identification and target prediction of chemical screenings', 'Liu, Xueping|Vogt, Ingo|Haque, Tanzeem|Campillos, Mónica', 'Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.|Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, 85764 Neuherberg, Germany.', 'Germany|Germany|Germany|Germany', 49, 'Algorithms|Bayes Theorem|High-Throughput Screening Assays|Humans|Internet|Ligands|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt303', '23716196', 'High-throughput phenotypic assays reveal information about the molecules that modulate biological processes, such as a disease phenotype and a signaling pathway. In these assays, the identification of hits along with their molecular targets is critical to understand the chemical activities modulating the biological system. Here, we present HitPick, a web server for identification of hits in high-throughput chemical screenings and prediction of their molecular targets. HitPick applies the B-score method for hit identification and a newly developed approach combining 1-nearest-neighbor (1NN) similarity searching and Laplacian-modified naïve Bayesian target models to predict targets of identified hits. The performance of the HitPick web server is presented and discussed.'),
(77651, 2013, 'bio', 'EpiCombFlu: exploring known influenza epitopes and their combination to design a universal influenza vaccine', 'Jaiswal, Varun|Chanumolu, Sree K|Sharma, Pankaj|Chauhan, Rajinder S|Rout, Chittaranjan', 'Department of Biotechnology & Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India.|Department of Biotechnology & Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India.|Department of Biotechnology & Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India.|Department of Biotechnology & Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India.|Department of Biotechnology & Bioinformatics, Jaypee University of Information Technology, Waknaghat, Solan, Himachal Pradesh 173234, India.', 'India|India|India|India|India', 2, 'Algorithms|Epitopes|Humans|Influenza Vaccines|Internet|Orthomyxoviridae|Sequence Analysis, Protein|Software|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/btt304', '23716197', 'Influenza is responsible for half a million deaths annually, and vaccination is the best preventive measure against this pervasive health problem. Influenza vaccines developed from surveillance data of each season are strain-specific, and therefore, are unable to provide protection against pandemic strains arising from antigenic shift and drift. Seasonal epidemics and occasional pandemics of influenza have created a need for a universal influenza vaccine (UIV). Researchers have shown that a combination of conserved epitopes has the potential to be used as a UIV.'),
(77652, 2013, 'bio', 'COPRED: prediction of fold, GO molecular function and functional residues at the domain level', 'López, Daniel|Pazos, Florencio', 'Systems Biology Department, Computational Systems Biology Group CNB-CSIC, c/ Darwin, 3. Cantoblanco, 28049 Madrid, Spain.|Systems Biology Department, Computational Systems Biology Group CNB-CSIC, c/ Darwin, 3. Cantoblanco, 28049 Madrid, Spain.', 'Spain|Spain', 1, 'Gene Ontology|Internet|Molecular Sequence Annotation|Protein Folding|Protein Structure, Tertiary|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btt283', '23720488', 'Only recently the first resources devoted to the functional annotation of proteins at the domain level started to appear. The next step is to develop specific methodologies for predicting function at the domain level based on these resources, and to implement them in web servers to be used by the community. In this work, we present COPRED, a web server for the concomitant prediction of fold, molecular function and functional sites at the domain level, based on a methodology for domain molecular function prediction and a resource of domain functional annotations previously developed and benchmarked.'),
(77653, 2013, 'bio', 'Improved image alignment method in application to X-ray images and biological images', 'Wang, Ching-Wei|Chen, Hsiang-Chou', 'Graduate Institute of Biomedical Engineering, and Graduate Institute of Applied Science and Technology, Honors College National Taiwan University of Science and Technology, Taipei City, 10607 Taiwan. cweiwang@mail.ntust.edu.tw|Graduate Institute of Biomedical Engineering, and Graduate Institute of Applied Science and Technology, Honors College National Taiwan University of Science and Technology, Taipei City, 10607 Taiwan. cweiwang@mail.ntust.edu.tw', '-|-', 11, 'Animals|Artifacts|Humans|Image Interpretation, Computer-Assisted|Mice|Microscopy|Software|Tomography, X-Ray Computed|Tooth', 'Journal Article', '10.1093/bioinformatics/btt309', '23720489', 'Alignment of medical images is a vital component of a large number of applications throughout the clinical track of events, not only within clinical diagnostic settings, but prominently so in the area of planning, consummation and evaluation of surgical and radiotherapeutical procedures. However, image registration of medical images is challenging because of variations on data appearance, imaging artifacts and complex data deformation problems. Hence, the aim of this study is to develop a robust image alignment method for medical images.'),
(77654, 2013, 'bio', 'Drug-target interaction prediction through domain-tuned network-based inference', 'Alaimo, Salvatore|Pulvirenti, Alfredo|Giugno, Rosalba|Ferro, Alfredo', 'Department of Mathematics and Computer Science and Department of Clinical and Molecular Biomedicine, University of Catania, Catania, Italy.|Department of Mathematics and Computer Science and Department of Clinical and Molecular Biomedicine, University of Catania, Catania, Italy.|Department of Mathematics and Computer Science and Department of Clinical and Molecular Biomedicine, University of Catania, Catania, Italy.|Department of Mathematics and Computer Science and Department of Clinical and Molecular Biomedicine, University of Catania, Catania, Italy.', 'Italy|Italy|Italy|Italy', 98, 'Algorithms|Databases, Pharmaceutical|Drug Discovery|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btt307', '23720490', 'The identification of drug-target interaction (DTI) represents a costly and time-consuming step in drug discovery and design. Computational methods capable of predicting reliable DTI play an important role in the field. Recently, recommendation methods relying on network-based inference (NBI) have been proposed. However, such approaches implement naive topology-based inference and do not take into account important features within the drug-target domain.'),
(77655, 2013, 'bio', 'SPANNER: taxonomic assignment of sequences using pyramid matching of similarity profiles', 'Porter, Michael S|Beiko, Robert G', 'Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, Nova Scotia, B3H 4R2, Canada.|Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, Nova Scotia, B3H 4R2, Canada.', 'Canada|Canada', 6, 'Algorithms|Genome, Microbial|Genomics|Metagenome|Phylogeny|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btt313', '23732273', 'Homology-based taxonomic assignment is impeded by differences between the unassigned read and reference database, forcing a rank-specific classification to the closest (and possibly incorrect) reference lineage. This assignment may be correct only to a general rank (e.g. order) and incorrect below that rank (e.g. family and genus). Algorithms like LCA avoid this by varying the predicted taxonomic rank based on matches to a set of taxonomic references. LCA and related approaches can be conservative, especially if best matches are taxonomically widespread because of events such as lateral gene transfer (LGT).'),
(77656, 2013, 'bio', 'AuthorReward: increasing community curation in biological knowledge wikis through automated authorship quantification', 'Dai, Lin|Tian, Ming|Wu, Jiayan|Xiao, Jingfa|Wang, Xumin|Townsend, Jeffrey P|Zhang, Zhang', 'CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.|CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China.', 'China|China|China|China|China|China|China', 7, 'Algorithms|Authorship|Cooperative Behavior|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btt284', '23732274', 'Community curation-harnessing community intelligence in knowledge curation, bears great promise in dealing with the flood of biological knowledge. To exploit the full potential of the scientific community for knowledge curation, multiple biological wikis (bio-wikis) have been built to date. However, none of them have achieved a substantial impact on knowledge curation. One of the major limitations in bio-wikis is insufficient community participation, which is intrinsically because of lack of explicit authorship and thus no credit for community curation. To increase community curation in bio-wikis, here we develop AuthorReward, an extension to MediaWiki, to reward community-curated efforts in knowledge curation. AuthorReward quantifies researchers contributions by properly factoring both edit quantity and quality and yields automated explicit authorship according to their quantitative contributions. AuthorReward provides bio-wikis with an authorship metric, helpful to increase community participation in bio-wikis and to achieve community curation of massive biological knowledge.'),
(77657, 2013, 'bio', 'Relating genes to function: identifying enriched transcription factors using the ENCODE ChIP-Seq significance tool', 'Auerbach, Raymond K|Chen, Bin|Butte, Atul J', 'Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, 1265 Welch Road, Room X-163 MS-5415, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, 1265 Welch Road, Room X-163 MS-5415, Stanford, CA 94305, USA.|Division of Systems Medicine, Department of Pediatrics, Stanford University School of Medicine, 1265 Welch Road, Room X-163 MS-5415, Stanford, CA 94305, USA.', 'United States|United States|United States', 43, 'Chromatin Immunoprecipitation|Genes|Internet|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt316', '23732275', 'Biological analysis has shifted from identifying genes and transcripts to mapping these genes and transcripts to biological functions. The ENCODE Project has generated hundreds of ChIP-Seq experiments spanning multiple transcription factors and cell lines for public use, but tools for a biomedical scientist to analyze these data are either non-existent or tailored to narrow biological questions. We present the ENCODE ChIP-Seq Significance Tool, a flexible web application leveraging public ENCODE data to identify enriched transcription factors in a gene or transcript list for comparative analyses.'),
(77658, 2014, 'bio', 'Informed and automated k-mer size selection for genome assembly', 'Chikhi, Rayan|Medvedev, Paul', 'Department of Computer Science and Engineering and Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA.|Department of Computer Science and Engineering and Department of Biochemistry and Molecular Biology, The Pennsylvania State University, University Park, PA 16802, USA.', 'United States|United States', 0, 'Algorithms|Animals|Automation|Genome|High-Throughput Nucleotide Sequencing|Humans|Insecta|Sequence Analysis, DNA|Software|Staphylococcus aureus', 'Journal Article', '10.1093/bioinformatics/btt310', '23732276', 'Genome assembly tools based on the de Bruijn graph framework rely on a parameter k, which represents a trade-off between several competing effects that are difficult to quantify. There is currently a lack of tools that would automatically estimate the best k to use and/or quickly generate histograms of k-mer abundances that would allow the user to make an informed decision.'),
(77659, 2013, 'bio', 'Gene-set analysis is severely biased when applied to genome-wide methylation data', 'Geeleher, Paul|Hartnett, Lori|Egan, Laurance J|Golden, Aaron|Raja Ali, Raja Affendi|Seoighe, Cathal', 'Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.|Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.|Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.|Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.|Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.|Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL 60637 USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Colitis, Ulcerative|CpG Islands|DNA Methylation|Genes|Genomics|Humans|Lung Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btt311', '23732277', 'DNA methylation is an epigenetic mark that can stably repress gene expression. Because of its biological and clinical significance, several methods have been developed to compare genome-wide patterns of methylation between groups of samples. The application of gene set analysis to identify relevant groups of genes that are enriched for differentially methylated genes is often a major component of the analysis of these data. This can be used, for example, to identify processes or pathways that are perturbed in disease development. We show that gene-set analysis, as it is typically applied to genome-wide methylation assays, is severely biased as a result of differences in the numbers of CpG sites associated with different classes of genes and gene promoters.'),
(77660, 2013, 'bio', 'BeCAS: biomedical concept recognition services and visualization', 'Nunes, Tiago|Campos, David|Matos, Sérgio|Oliveira, José Luís', 'DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, 3810 - 193 Aveiro, Portugal. tiago.nunes@ua.pt|DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, 3810 - 193 Aveiro, Portugal. tiago.nunes@ua.pt|DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, 3810 - 193 Aveiro, Portugal. tiago.nunes@ua.pt|DETI/IEETA, University of Aveiro, Campus Universitário de Santiago, 3810 - 193 Aveiro, Portugal. tiago.nunes@ua.pt', 'Portugal|Portugal|Portugal|Portugal', 0, 'Data Mining|Databases, Factual|Internet|MEDLINE|Software', 'Journal Article', '10.1093/bioinformatics/btt317', '23736528', 'The continuous growth of the biomedical scientific literature has been motivating the development of text-mining tools able to efficiently process all this information. Although numerous domain-specific solutions are available, there is no web-based concept-recognition system that combines the ability to select multiple concept types to annotate, to reference external databases and to automatically annotate nested and intercepted concepts. BeCAS, the Biomedical Concept Annotation System, is an API for biomedical concept identification and a web-based tool that addresses these limitations. MEDLINE abstracts or free text can be annotated directly in the web interface, where identified concepts are enriched with links to reference databases. Using its customizable widget, it can also be used to augment external web pages with concept highlighting features. Furthermore, all text-processing and annotation features are made available through an HTTP REST API, allowing integration in any text-processing pipeline.'),
(77661, 2013, 'bio', 'Isaac: ultra-fast whole-genome secondary analysis on Illumina sequencing platforms', 'Raczy, Come|Petrovski, Roman|Saunders, Christopher T|Chorny, Ilya|Kruglyak, Semyon|Margulies, Elliott H|Chuang, Han-Yu|Källberg, Morten|Kumar, Swathi A|Liao, Arnold|Little, Kristina M|Strömberg, Michael P|Tanner, Stephen W', 'Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com|Illumina United Kingdom, Chesterford Research Park, Little Chesterford, Nr Saffron Walden, Essex, UK. craczy@illumina.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kin', 144, 'Genetic Variation|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt314', '23736529', 'An ultrafast DNA sequence aligner (Isaac Genome Alignment Software) that takes advantage of high-memory hardware (>48 GB) and variant caller (Isaac Variant Caller) have been developed. We demonstrate that our combined pipeline (Isaac) is four to five times faster than BWA + GATK on equivalent hardware, with comparable accuracy as measured by trio conflict rates and sensitivity. We further show that Isaac is effective in the detection of disease-causing variants and can easily/economically be run on commodity hardware.'),
(77662, 2013, 'bio', 'Whole-Genome rVISTA: a tool to determine enrichment of transcription factor binding sites in gene promoters from transcriptomic data', 'Dubchak, Inna|Munoz, Matthew|Poliakov, Alexandre|Salomonis, Nathan|Minovitsky, Simon|Bodmer, Rolf|Zambon, Alexander C', 'Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov|Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA. ildubchak@lbl.gov', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Gene Expression Profiling|Genomics|Humans|Internet|Mice|Promoter Regions, Genetic|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btt318', '23736530', 'We have developed a web-based query tool, Whole-Genome rVISTA (WGRV), that determines enrichment of transcription factors (TFs) and associated target genes in sets of co-regulated genes. WGRV enables users to query databases containing pre-computed genome coordinates of evolutionarily conserved transcription factor binding sites in the proximal promoters (from 100 bp to 5 kb upstream) of human, mouse and Drosophila genomes. TF binding sites are based on position-weight matrices from the TRANSFAC Professional database. For a given set of co-regulated genes, WGRV returns statistically enriched and evolutionarily conserved binding sites, mapped by the regulatory VISTA (rVISTA) algorithm. Users can then retrieve a list of genes from the query set containing the enriched TF binding sites and their location in the query set promoters. Results are exported in a BED format for rapid visualization in the UCSC genome browser. Flat files of mapped conserved sites and their genomic coordinates are also available for analysis with stand-alone software.'),
(77663, 2013, 'bio', 'NGS++: a library for rapid prototyping of epigenomics software tools', 'Nordell Markovits, Alexei|Joly Beauparlant, Charles|Toupin, Dominique|Wang, Shengrui|Droit, Arnaud|Gevry, Nicolas', 'Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.|Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.|Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.|Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.|Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.|Department of Biology, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 4, 'Epigenomics|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/btt312', '23736531', 'The development of computational tools to enable testing and analysis of high-throughput-sequencing data is essential to modern genomics research. However, although multiple frameworks have been developed to facilitate access to these tools, comparatively little effort has been made at implementing low-level programming libraries to increase the speed and ease of their development.');
