INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75546, 2010, 'bio', 'A new method for designing degenerate primers and its use in the identification of sequences in Brachiaria showing similarity to apomixis-associated genes', 'Gorrón, Eduardo|Rodríguez, Fausto|Bernal, Diana|Rodriguez-Rojas, Luis Miguel|Bernal, Adriana|Restrepo, Silvia|Tohme, Joe', 'Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.|Centro Internacional de Agricultura Tropical (CIAT), Cali, Colombia.', 'Colombia|Colombia|Colombia|Colombia|Colombia|Colombia|Colombia', 6, 'Algorithms|Base Sequence|Brachiaria|DNA Primers|Expressed Sequence Tags|Genes, Plant|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq312', '20547638', 'We developed a technique and a tool for degenerate primer design based on multiple local alignments employing the MEME algorithm supported with electronic PCR. The objective is to find adequate primers starting from sequences with poor global similarity. We show an example of its application in our laboratory to find sequences in Brachiaria with similarity to ESTs related to apomixis.'),
(75547, 2010, 'bio', 'ViewDock TDW: high-throughput visualization of virtual screening results', 'Lau, Christopher D|Levesque, Marshall J|Chien, Shu|Date, Susumu|Haga, Jason H', 'Department of Bioengineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California-San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States|United States', 12, 'Computational Biology|Internet|Ligands|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq296', '20551133', 'ViewDock TDW is a modification of the pre-existing ViewDock Chimera extension (http://www.cgl.ucsf.edu/chimera/) used to visualize results of virtual screening experiments. By combing TDW hardware and an enhanced ViewDock interface, dozens of ligand-protein complexes are rendered simultaneously to parallelize the analysis of candidate ligands. The ViewDock TDW GUI allows the user to easily and interactively manipulate the molecules on the TDW as an entire set, a selected subset or a single ligand-protein complex and preserves all Chimera functionality.'),
(75548, 2010, 'bio', 'Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood', 'Csurös, Miklós', 'Department of Computer Science and Operations Research, University of Montréal, Montréal, Québec, Canada. csuros@iro.umontreal.ca', 'Canada', 181, 'Algorithms|Computational Biology|Phylogeny|Probability|Software', 'Journal Article', '10.1093/bioinformatics/btq315', '20551134', 'Count is a software package for the analysis of numerical profiles on a phylogeny. It is primarily designed to deal with profiles derived from the phyletic distribution of homologous gene families, but is suited to study any other integer-valued evolutionary characters. Count performs ancestral reconstruction, and infers family- and lineage-specific characteristics along the evolutionary tree. It implements popular methods employed in gene content analysis such as Dollo and Wagner parsimony, propensity for gene loss, as well as probabilistic methods involving a phylogenetic birth-and-death model.'),
(75549, 2010, 'bio', 'JAMIE: joint analysis of multiple ChIP-chip experiments', 'Wu, Hao|Ji, Hongkai', 'Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA.|Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, 615 North Wolfe Street, Baltimore, MD 21205, USA.', 'United States|United States', 11, 'Binding Sites|Chromatin Immunoprecipitation|Computational Biology|Genome|Oligonucleotide Array Sequence Analysis|Protein Binding', 'Journal Article', '10.1093/bioinformatics/btq314', '20551135', 'Chromatin immunoprecipitation followed by genome tiling array hybridization (ChIP-chip) is a powerful approach to identify transcription factor binding sites (TFBSs) in target genomes. When multiple related ChIP-chip datasets are available, analyzing them jointly allows one to borrow information across datasets to improve peak detection. This is particularly useful for analyzing noisy datasets.'),
(75550, 2010, 'bio', 'Structure-based kernels for the prediction of catalytic residues and their involvement in human inherited disease', 'Xin, Fuxiao|Myers, Steven|Li, Yong Fuga|Cooper, David N|Mooney, Sean D|Radivojac, Predrag', 'School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA.', 'India|India|India|India|India|India', 15, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Catalysis|Catalytic Domain|Computational Biology|Enzymes|Genetic Diseases, Inborn|Humans|Mutation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq319', '20551136', 'Enzyme catalysis is involved in numerous biological processes and the disruption of enzymatic activity has been implicated in human disease. Despite this, various aspects of catalytic reactions are not completely understood, such as the mechanics of reaction chemistry and the geometry of catalytic residues within active sites. As a result, the computational prediction of catalytic residues has the potential to identify novel catalytic pockets, aid in the design of more efficient enzymes and also predict the molecular basis of disease.'),
(75551, 2010, 'bio', 'Molecular signatures-based prediction of enzyme promiscuity', 'Carbonell, Pablo|Faulon, Jean-Loup', 'iSSB, Institute of Systems and Synthetic Biology, University of Evry, Evry, France. pcarbonell@issb.genopole.fr|iSSB, Institute of Systems and Synthetic Biology, University of Evry, Evry, France. pcarbonell@issb.genopole.fr', 'France|France', 51, 'Artificial Intelligence|Catalysis|Catalytic Domain|Enzymes|Protein Engineering|Proteins', 'Journal Article', '10.1093/bioinformatics/btq317', '20551137', 'Enzyme promiscuity, a property with practical applications in biotechnology and synthetic biology, has been related to the evolvability of enzymes. At the molecular level, several structural mechanisms have been linked to enzyme promiscuity in enzyme families. However, it is at present unclear to what extent these observations can be generalized. Here, we introduce for the first time a method for predicting catalytic and substrate promiscuity using a graph-based representation known as molecular signature.'),
(75552, 2010, 'bio', 'A Bayesian approach using covariance of single nucleotide polymorphism data to detect differences in linkage disequilibrium patterns between groups of individuals', 'Clark, Taane G|Campino, Susana G|Anastasi, Elisa|Auburn, Sarah|Teo, Yik Y|Small, Kerrin|Rockett, Kirk A|Kwiatkowski, Dominic P|Holmes, Christopher C', 'Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk|Department of Epidemiology and Public Health, London School of Hygiene and Tropical Medicine, London, UK. taane.clark@lshtm.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 5, 'Bayes Theorem|Genome|Genome-Wide Association Study|Genotype|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Sample Size|Software', 'Journal Article', '10.1093/bioinformatics/btq327', '20554688', 'Quantifying differences in linkage disequilibrium (LD) between sub-groups can highlight genetic regions or sites under selection and/or associated with disease, and may have utility in trans-ethnic mapping studies.'),
(75553, 2010, 'bio', 'Homology of SMP domains to the TULIP superfamily of lipid-binding proteins provides a structural basis for lipid exchange between ER and mitochondria', 'Kopec, Klaus O|Alva, Vikram|Lupas, Andrei N', 'Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Tübingen, Germany.|Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Tübingen, Germany.|Department of Protein Evolution, Max-Planck-Institute for Developmental Biology, Tübingen, Germany.', 'Germany|Germany|Germany', 142, 'Amino Acid Sequence|Animals|Biological Transport|Carrier Proteins|Endoplasmic Reticulum|Membrane Proteins|Mitochondria|Mitochondrial Proteins|Molecular Sequence Data|Phospholipids', 'Journal Article', '10.1093/bioinformatics/btq326', '20554689', 'Mitochondria must uptake some phospholipids from the endoplasmic reticulum (ER) for the biogenesis of their membranes. They convert one of these lipids, phosphatidylserine, to phosphatidylethanolamine, which can be re-exported via the ER to all other cellular membranes. The mechanisms underlying these exchanges between ER and mitochondria are poorly understood. Recently, a complex termed ER-mitochondria encounter structure (ERMES) was shown to be necessary for phospholipid exchange in budding yeast. However, it is unclear whether this complex is merely an inter-organelle tether or also the transporter. ERMES consists of four proteins: Mdm10, Mdm34 (Mmm2), Mdm12 and Mmm1, three of which contain the uncharacterized SMP domain common to a number of eukaryotic membrane-associated proteins. Here, we show that the SMP domain belongs to the TULIP superfamily of lipid/hydrophobic ligand-binding domains comprising members of known structure. This relationship suggests that the SMP domains of the ERMES complex mediate lipid exchange between ER and mitochondria.'),
(75554, 2010, 'bio', 'A Poisson model for random multigraphs', 'Ranola, John M O|Ahn, Sangtae|Sehl, Mary|Smith, Desmond J|Lange, Kenneth', 'Department of Biomathematics, University of California, Los Angeles, CA, USA.|Department of Biomathematics, University of California, Los Angeles, CA, USA.|Department of Biomathematics, University of California, Los Angeles, CA, USA.|Department of Biomathematics, University of California, Los Angeles, CA, USA.|Department of Biomathematics, University of California, Los Angeles, CA, USA.', 'United States|United States|United States|United States|United States', 12, 'Algorithms|Computer Graphics|Models, Biological|Neural Networks (Computer)|Poisson Distribution|Protein Interaction Mapping|Radiation Hybrid Mapping', 'Journal Article', '10.1093/bioinformatics/btq309', '20554690', 'Biological networks are often modeled by random graphs. A better modeling vehicle is a multigraph where each pair of nodes is connected by a Poisson number of edges. In the current model, the mean number of edges equals the product of two propensities, one for each node. In this context it is possible to construct a simple and effective algorithm for rapid maximum likelihood estimation of all propensities. Given estimated propensities, it is then possible to test statistically for functionally connected nodes that show an excess of observed edges over expected edges. The model extends readily to directed multigraphs. Here, propensities are replaced by outgoing and incoming propensities.'),
(75555, 2010, 'bio', 'Causal relationship inference for a large-scale cellular network', 'Zhou, Tong|Wang, Ya-Li', 'Department of Automation, Tsinghua University, Beijing, China. tzhou@mail.tsinghua.edu.cn|Department of Automation, Tsinghua University, Beijing, China. tzhou@mail.tsinghua.edu.cn', 'China|China', 23, 'Algorithms|Computer Simulation|Least-Squares Analysis|Likelihood Functions|MAP Kinase Signaling System|Models, Biological|Probability|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btq325', '20554691', 'Cellular networks usually consist of numerous chemical species, such as DNA, RNA, proteins and small molecules, etc. Different biological tasks are generally performed by complex interactions of these species. As these interactions can rarely be directly measured, it is widely recognized that causal relationship identification is essential in understanding biological behaviors of a cellular network. Challenging issues here include not only the large number of interactions to be estimated, but also many restrictions on probing signals. The purposes of this study are to incorporate power law in cellular network identification, in order to increase accuracy of causal regulation estimations, especially to reduce false positive errors.'),
(75556, 2010, 'bio', 'Deriving the consequences of genomic variants with the Ensembl API and SNP Effect Predictor', 'McLaren, William|Pritchard, Bethan|Rios, Daniel|Chen, Yuan|Flicek, Paul|Cunningham, Fiona', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK. wm2@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1052, 'Genetic Variation|Genomics|Internet|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq330', '20562413', 'A tool to predict the effect that newly discovered genomic variants have on known transcripts is indispensible in prioritizing and categorizing such variants. In Ensembl, a web-based tool (the SNP Effect Predictor) and API interface can now functionally annotate variants in all Ensembl and Ensembl Genomes supported species.'),
(75557, 2010, 'bio', 'Assemble: an interactive graphical tool to analyze and build RNA architectures at the 2D and 3D levels', 'Jossinet, Fabrice|Ludwig, Thomas E|Westhof, Eric', 'Architecture et Réactivité de lARN, Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France. f.jossinet@ibmc-cnrs.unistra.fr|Architecture et Réactivité de lARN, Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France. f.jossinet@ibmc-cnrs.unistra.fr|Architecture et Réactivité de lARN, Université de Strasbourg, Institut de Biologie Moléculaire et Cellulaire du CNRS, Strasbourg, France. f.jossinet@ibmc-cnrs.unistra.fr', 'France|France|France', 126, 'Computational Biology|Computer Graphics|Models, Molecular|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq321', '20562414', 'Assemble is an intuitive graphical interface to analyze, manipulate and build complex 3D RNA architectures. It provides several advanced and unique features within the framework of a semi-automated modeling process that can be performed by homology and ab initio with or without electron density maps. Those include the interactive editing of a secondary structure and a searchable, embedded library of annotated tertiary structures. Assemble helps users with performing recurrent and otherwise tedious tasks in structural RNA research.'),
(75558, 2010, 'bio', 'Iterative Correction of Reference Nucleotides (iCORN) using second generation sequencing technology', 'Otto, Thomas D|Sanders, Mandy|Berriman, Matthew|Newbold, Chris', 'Parasite Genomics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK. tdo@sanger.ac.uk|Parasite Genomics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK. tdo@sanger.ac.uk|Parasite Genomics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK. tdo@sanger.ac.uk|Parasite Genomics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SA, UK. tdo@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Genome, Protozoan|Genomics|Nucleotides|Plasmodium falciparum|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq269', '20562415', 'The accuracy of reference genomes is important for downstream analysis but a low error rate requires expensive manual interrogation of the sequence. Here, we describe a novel algorithm (Iterative Correction of Reference Nucleotides) that iteratively aligns deep coverage of short sequencing reads to correct errors in reference genome sequences and evaluate their accuracy.'),
(75559, 2010, 'bio', 'Manipulation of FASTQ data with Galaxy', 'Blankenberg, Daniel|Gordon, Assaf|Von Kuster, Gregory|Coraor, Nathan|Taylor, James|Nekrutenko, Anton|Galaxy Team', 'Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.|Huck Institute for the Life Sciences, Penn State University, University Park, PA 16803, USA.', 'United States|United States|United States|United States|United States|United States|United States', 357, 'Databases, Factual|Genomics|Internet|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq281', '20562416', 'Here, we describe a tool suite that functions on all of the commonly known FASTQ format variants and provides a pipeline for manipulating next generation sequencing data taken from a sequencing machine all the way through the quality filtering steps.'),
(75560, 2010, 'bio', 'An alignment algorithm for bisulfite sequencing using the Applied Biosystems SOLiD System', 'Ondov, Brian D|Cochran, Charles|Landers, Mark|Meredith, Gavin D|Dudas, Miroslav|Bergman, Nicholas H', 'National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.|National Biodefense Analysis and Countermeasures Center, 110 Thomas Johnson Drive, Frederick, MD 21702, USA.', 'United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Arabidopsis|Sequence Alignment|Sequence Analysis, DNA|Sulfites', 'Journal Article', '10.1093/bioinformatics/btq291', '20562417', 'Bisulfite sequencing allows cytosine methylation, an important epigenetic marker, to be detected via nucleotide substitutions. Since the Applied Biosystems SOLiD System uses a unique di-base encoding that increases confidence in the detection of nucleotide substitutions, it is a potentially advantageous platform for this application. However, the di-base encoding also makes reads with many nucleotide substitutions difficult to align to a reference sequence with existing tools, preventing the platforms potential utility for bisulfite sequencing from being realized. Here, we present SOCS-B, a reference-based, un-gapped alignment algorithm for the SOLiD System that is tolerant of both bisulfite-induced nucleotide substitutions and a parametric number of sequencing errors, facilitating bisulfite sequencing on this platform. An implementation of the algorithm has been integrated with the previously reported SOCS alignment tool, and was used to align CpG methylation-enriched Arabidopsis thaliana bisulfite sequence data, exhibiting a 2-fold increase in sensitivity compared to existing methods for aligning SOLiD bisulfite data.'),
(75561, 2010, 'bio', 'Phenoclustering: online mining of cross-species phenotypes', 'Groth, Philip|Kalev, Ivan|Kirov, Ivaylo|Traikov, Borislav|Leser, Ulf|Weiss, Bertram', 'Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.|Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.|Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.|Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.|Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.|Research Laboratories of Bayer Schering Pharma AG, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Cluster Analysis|Data Mining|Internet|Phenotype', 'Journal Article', '10.1093/bioinformatics/btq311', '20562418', 'Recently, several methods for analyzing phenotype data have been published, but only few are able to cope with data sets generated in different studies, with different methods, or for different species. We developed an online system in which more than 300 000 phenotypes from a wide variety of sources and screening methods can be analyzed together. Clusters of similar phenotypes are visualized as networks of highly similar phenotypes, inducing gene groups useful for functional analysis. This system is part of PhenomicDB, providing the worlds largest cross-species phenotype data collection with a tool to mine its wealth of information.'),
(75562, 2010, 'bio', 'CplexA: a Mathematica package to study macromolecular-assembly control of gene expression', 'Vilar, Jose M G|Saiz, Leonor', 'Biophysics Unit (CSIC-UPV/EHU), University of the Basque Country, Bilbao, Spain. j.vilar@ikerbasque.org|Biophysics Unit (CSIC-UPV/EHU), University of the Basque Country, Bilbao, Spain. j.vilar@ikerbasque.org', 'Spain|Spain', 29, 'Gene Expression|Gene Expression Regulation|Promoter Regions, Genetic|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq328', '20562419', 'Macromolecular assembly coordinates essential cellular processes, such as gene regulation and signal transduction. A major challenge for conventional computational methods to study these processes is tackling the exponential increase of the number of configurational states with the number of components. CplexA is a Mathematica package that uses functional programming to efficiently compute probabilities and average properties over such exponentially large number of states from the energetics of the interactions. The package is particularly suited to study gene expression at complex promoters controlled by multiple, local and distal, DNA binding sites for transcription factors.'),
(75563, 2010, 'bio', 'MISS: a non-linear methodology based on mutual information for genetic association studies in both population and sib-pairs analysis', 'Brunel, Helena|Gallardo-Chacón, Joan-Josep|Buil, Alfonso|Vallverdú, Montserrat|Soria, José Manuel|Caminal, Pere|Perera, Alexandre', 'Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu|Institut de Bioenginyeria de Catalunya, Departament dEnginyeria de Sistemes, Automàtica i Informàtica Industrial, Universitat Politècnica de Catalunya, Pau Gargallo 5, 08028 Barcelona, Spain. helena.brunel@upc.edu', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain', 23, 'Algorithms|Chromosome Mapping|Computational Biology|Genetic Association Studies|Genetic Variation|Humans|Nonlinear Dynamics|Phenotype|Polymorphism, Single Nucleotide|Population Groups|Regression Analysis|Siblings|Thrombosis', 'Journal Article', '10.1093/bioinformatics/btq273', '20562420', 'Finding association between genetic variants and phenotypes related to disease has become an important vehicle for the study of complex disorders. In this context, multi-loci genetic association might unravel additional information when compared with single loci search. The main goal of this work is to propose a non-linear methodology based on information theory for finding combinatorial association between multi-SNPs and a given phenotype.'),
(75564, 2010, 'bio', 'Savant: genome browser for high-throughput sequencing data', 'Fiume, Marc|Williams, Vanessa|Brook, Andrew|Brudno, Michael', 'Department of Computer Science, University of Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Ontario, Canada.|Department of Computer Science, University of Toronto, Ontario, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Base Sequence|Genome|Genome, Human|Genomics|High-Throughput Screening Assays|Humans|Polymorphism, Single Nucleotide|Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq332', '20562449', 'The advent of high-throughput sequencing (HTS) technologies has made it affordable to sequence many individuals genomes. Simultaneously the computational analysis of the large volumes of data generated by the new sequencing machines remains a challenge. While a plethora of tools are available to map the resulting reads to a reference genome, and to conduct primary analysis of the mappings, it is often necessary to visually examine the results and underlying data to confirm predictions and understand the functional effects, especially in the context of other datasets.'),
(75565, 2010, 'bio', 'Bridges: a tool for identifying local similarities in long sequences', 'Kondrashov, Alexey S|Assis, Raquel', 'Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. kondrash@umich.edu|Center for Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA. kondrash@umich.edu', 'United States|United States', 0, 'Algorithms|Base Sequence|Genomics|Sequence Alignment|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btq320', '20562450', 'Bridges is a heuristic search tool that uses short word matches to rapidly identify local similarities between sequences. It consists of three stages: filtering input sequences, identifying local similarities and post-processing local similarities. As input sequence data are released from memory after the filtering stage, genome-scale datasets can be efficiently compared in a single run. Bridges also includes 20 parameters, which enable the user to dictate the sensitivity and specificity of a search.'),
(75566, 2010, 'bio', 'A support vector machine model for the prediction of proteotypic peptides for accurate mass and time proteomics', 'Webb-Robertson, Bobbie-Jo M|Cannon, William R|Oehmen, Christopher S|Shah, Anuj R|Gurumoorthi, Vidhya|Lipton, Mary S|Waters, Katrina M', 'Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov|Computational Biology & Bioinformatics, Pacific Northwest National Laboratory, USA. bj@pnl.gov', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Mass Spectrometry|Peptides|Proteomics|Salmonella typhimurium|Shewanella|Yersinia pestis', 'Corrected and Republished Article', '10.1093/bioinformatics/btq251', '20568665', 'The standard approach to identifying peptides based on accurate mass and elution time (AMT) compares profiles obtained from a high resolution mass spectrometer to a database of peptides previously identified from tandem mass spectrometry (MS/MS) studies. It would be advantageous, with respect to both accuracy and cost, to only search for those peptides that are detectable by MS (proteotypic).'),
(75567, 2010, 'bio', 'Cassis: detection of genomic rearrangement breakpoints', 'Baudet, Christian|Lemaitre, Claire|Dias, Zanoni|Gautier, Christian|Tannier, Eric|Sagot, Marie-France', 'Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.|Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.|Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.|Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.|Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.|Equipe BAMBOO, INRIA Grenoble Rhône-Alpes et Laboratoire de Biométrie et Biologie Evolutive (UMR 5558) CNRS, Université Lyon 1, Villeurbanne, France.', 'France|France|France|France|France|France', 18, 'Algorithms|Chromosome Breakpoints|Chromosomes|Computational Biology|Genome|Recombination, Genetic|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btq301', '20576622', 'Genomes undergo large structural changes that alter their organization. The chromosomal regions affected by these rearrangements are called breakpoints, while those which have not been rearranged are called synteny blocks. Lemaitre et al. presented a new method to precisely delimit rearrangement breakpoints in a genome by comparison with the genome of a related species. Receiving as input a list of one2one orthologous genes found in the genomes of two species, the method builds a set of reliable and non-overlapping synteny blocks and refines the regions that are not contained into them. Through the alignment of each breakpoint sequence against its specific orthologous sequences in the other species, we can look for weak similarities inside the breakpoint, thus extending the synteny blocks and narrowing the breakpoints. The identification of the narrowed breakpoints relies on a segmentation algorithm and is statistically assessed. Here, we present the package Cassis that implements this method of precise detection of genomic rearrangement breakpoints.'),
(75568, 2010, 'bio', 'Chromaligner: a web server for chromatogram alignment', 'Wang, San-Yuan|Ho, Tsung-Jung|Kuo, Ching-Hua|Tseng, Yufeng J', 'Department of Computer Science and Information Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan.|Department of Computer Science and Information Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan.|Department of Computer Science and Information Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan.|Department of Computer Science and Information Engineering, College of Medicine, National Taiwan University, Taipei, Taiwan.', '-|-|-|-', 14, 'Algorithms|Chromatography|Internet|Rheum|Scutellaria', 'Journal Article', '10.1093/bioinformatics/btq337', '20576623', 'Chromaligner is a tool for chromatogram alignment to align retention time for chromatographic methods coupled to spectrophotometers such as high performance liquid chromatography and capillary electrophoresis for metabolomics works. Chromaligner resolves peak shifts by a constrained chromatogram alignment. For a collection of chromatograms and a set of defined peaks, Chromaligner aligns the chromatograms on defined peaks using correlation warping (COW). Chromaligner is faster than the original COW algorithm by k(2) times, where k is the number of defined peaks in a chromatogram. It also provides alignments based on known component peaks to reach the best results for further chemometric analysis.'),
(75569, 2010, 'bio', 'EpiTOP--a proteochemometric tool for MHC class II binding prediction', 'Dimitrov, Ivan|Garnev, Panayot|Flower, Darren R|Doytchinova, Irini', 'Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria.|Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria.|Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria.|Faculty of Pharmacy, Medical University of Sofia, Sofia, Bulgaria.', 'Bulgaria|Bulgaria|Bulgaria|Bulgaria', 0, 'Alleles|Epitopes, T-Lymphocyte|HLA-DR Antigens|HLA-DRB1 Chains|Histocompatibility Antigens Class II|Ligands|Peptides|Software', 'Journal Article', '10.1093/bioinformatics/btq324', '20576624', 'T-cell epitope identification is a critical immunoinformatic problem within vaccine design. To be an epitope, a peptide must bind an MHC protein.'),
(75570, 2010, 'bio', 'A probabilistic framework for aligning paired-end RNA-seq data', 'Hu, Yin|Wang, Kai|He, Xiaping|Chiang, Derek Y|Prins, Jan F|Liu, Jinze', 'Department of Computer Science, University of Kentucky, Lexington, KY, USA.|Department of Computer Science, University of Kentucky, Lexington, KY, USA.|Department of Computer Science, University of Kentucky, Lexington, KY, USA.|Department of Computer Science, University of Kentucky, Lexington, KY, USA.|Department of Computer Science, University of Kentucky, Lexington, KY, USA.|Department of Computer Science, University of Kentucky, Lexington, KY, USA.', 'United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Alternative Splicing|Base Sequence|Exons|Gene Expression Profiling|Genome|Humans|Probability|RNA, Messenger|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq336', '20576625', 'The RNA-seq paired-end read (PER) protocol samples transcript fragments longer than the sequencing capability of todays technology by sequencing just the two ends of each fragment. Deep sampling of the transcriptome using the PER protocol presents the opportunity to reconstruct the unsequenced portion of each transcript fragment using end reads from overlapping PERs, guided by the expected length of the fragment.'),
(75571, 2010, 'bio', 'Single feature polymorphism detection using recombinant inbred line microarray expression data', 'Cui, Xinping|You, Na|Girke, Thomas|Michelmore, Richard|Van Deynze, Allen', 'Department of Statistics, University of California, Riverside, CA, USA. xinping.cui@ucr.edu|Department of Statistics, University of California, Riverside, CA, USA. xinping.cui@ucr.edu|Department of Statistics, University of California, Riverside, CA, USA. xinping.cui@ucr.edu|Department of Statistics, University of California, Riverside, CA, USA. xinping.cui@ucr.edu|Department of Statistics, University of California, Riverside, CA, USA. xinping.cui@ucr.edu', 'United States|United States|United States|United States|United States', 1, 'Chromosome Mapping|Computational Biology|Gene Expression Profiling|Genomics|Oligonucleotide Array Sequence Analysis|Polymorphism, Genetic', 'Journal Article', '10.1093/bioinformatics/btq316', '20576626', 'The Affymetrix GeneChip microarray is currently providing a high-density and economical platform for discovery of genetic polymorphisms. Microarray data for single feature polymorphism (SFP) detection in recombinant inbred lines (RILs) can capitalize on the high level of replication available for each locus in the RIL population. It was suggested that the binding affinities from all of the RILs would form a multimodal distribution for a SFP. This motivated us to estimate the binding affinities from the robust multi-array analysis (RMA) method and formulate the SFP detection problem as a hypothesis testing problem, i.e. testing whether the underlying distribution of the estimated binding affinity (EBA) values of a probe is unimodal or multimodal.'),
(75572, 2010, 'bio', 'MSAProbs: multiple sequence alignment based on pair hidden Markov models and partition function posterior probabilities', 'Liu, Yongchao|Schmidt, Bertil|Maskell, Douglas L', 'School of Computer Engineering, Nanyang Technological University, Singapore. liuy0039@ntu.edu.sg|School of Computer Engineering, Nanyang Technological University, Singapore. liuy0039@ntu.edu.sg|School of Computer Engineering, Nanyang Technological University, Singapore. liuy0039@ntu.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Amino Acid Sequence|Computational Biology|Markov Chains|Probability|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq338', '20576627', 'Multiple sequence alignment is of central importance to bioinformatics and computational biology. Although a large number of algorithms for computing a multiple sequence alignment have been designed, the efficient computation of highly accurate multiple alignments is still a challenge.'),
(75573, 2010, 'bio', 'EGM: encapsulated gene-by-gene matching to identify gene orthologs and homologous segments in genomes', 'Mahmood, Khalid|Konagurthu, Arun S|Song, Jiangning|Buckle, Ashley M|Webb, Geoffrey I|Whisstock, James C', 'Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.|Department of Biochemistry and Molecular Biology, Monash University, Clayton, VIC 3800, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 6, 'Algorithms|Animals|Chromosome Mapping|Comparative Genomic Hybridization|Conserved Sequence|Humans|Mice|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btq339', '20581400', 'Identification of functionally equivalent genes in different species is essential to understand the evolution of biological pathways and processes. At the same time, identification of strings of conserved orthologous genes helps identify complex genomic rearrangements across different organisms. Such an insight is particularly useful, for example, in the transfer of experimental results between different experimental systems such as Drosophila and mammals.'),
(75574, 2010, 'bio', 'Deciphering subcellular processes in live imaging datasets via dynamic probabilistic networks', 'Letinic, Kresimir|Sebastian, Rafael|Barthel, Andrew|Toomre, Derek', 'Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA. kresimir.letinic@yale.edu|Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA. kresimir.letinic@yale.edu|Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA. kresimir.letinic@yale.edu|Department of Neurobiology, Yale University School of Medicine, New Haven, CT 06510, USA. kresimir.letinic@yale.edu', 'United States|United States|United States|United States', 4, 'Adipocytes|Animals|Exocytosis|Insulin|Markov Chains|Microscopy, Fluorescence|Probability|Secretory Vesicles|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btq331', '20581401', 'Designing mathematical tools that can formally describe the dynamics of complex intracellular processes remains a challenge. Live cell imaging reveals changes in the cellular states, but current simple approaches extract only minimal information of a static snapshot.'),
(75575, 2010, 'bio', 'Over-optimism in bioinformatics: an illustration', 'Jelizarow, Monika|Guillemot, Vincent|Tenenhaus, Arthur|Strimmer, Korbinian|Boulesteix, Anne-Laure', 'Department of Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.|Department of Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.|Department of Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.|Department of Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.|Department of Medical Informatics, Biometry and Epidemiology, University of Munich, Munich, Germany.', 'Germany|Germany|Germany|Germany|Germany', 59, 'Algorithms|Computational Biology|Discriminant Analysis|Gene Expression Profiling', 'Journal Article', '10.1093/bioinformatics/btq323', '20581402', 'In statistical bioinformatics research, different optimization mechanisms potentially lead to over-optimism in published papers. So far, however, a systematic critical study concerning the various sources underlying this over-optimism is lacking.'),
(75576, 2010, 'bio', 'Mining metabolic pathways through gene expression', 'Hancock, Timothy|Takigawa, Ichigaku|Mamitsuka, Hiroshi', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan. timhancock@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan. timhancock@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan. timhancock@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan', 14, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Humans|Markov Chains|Metabolic Networks and Pathways|Models, Statistical|Oligonucleotide Array Sequence Analysis|Statistics, Nonparametric|Yeasts', 'Journal Article', '10.1093/bioinformatics/btq344', '20587705', 'An observed metabolic response is the result of the coordinated activation and interaction between multiple genetic pathways. However, the complex structure of metabolism has meant that a compete understanding of which pathways are required to produce an observed metabolic response is not fully understood. In this article, we propose an approach that can identify the genetic pathways which dictate the response of metabolic network to specific experimental conditions.'),
(75577, 2010, 'bio', 'MIReNA: finding microRNAs with high accuracy and no learning at genome scale and from deep sequencing data', 'Mathelier, Anthony|Carbone, Alessandra', 'UPMC Université Paris 06, FRE3214, Génomique Analytique, Paris, France.|UPMC Université Paris 06, FRE3214, Génomique Analytique, Paris, France.', 'France|France', 0, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Genome|Humans|MicroRNAs', 'Comparative Study', '10.1093/bioinformatics/btq329', '20591903', 'MicroRNAs (miRNAs) are a class of endogenes derived from a precursor (pre-miRNA) and involved in post-transcriptional regulation. Experimental identification of novel miRNAs is difficult because they are often transcribed under specific conditions and cell types. Several computational methods were developed to detect new miRNAs starting from known ones or from deep sequencing data, and to validate their pre-miRNAs.'),
(75578, 2010, 'bio', 'MSMS: a coalescent simulation program including recombination, demographic structure and selection at a single locus', 'Ewing, Gregory|Hermisson, Joachim', 'Department of Mathematics, University of Vienna, Vienna, Austria. gregory.ewing@univie.ac.at|Department of Mathematics, University of Vienna, Vienna, Austria. gregory.ewing@univie.ac.at', 'Austria|Austria', 201, 'Computer Simulation|Demography|Genetic Loci|Humans|Population|Recombination, Genetic|Selection, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btq322', '20591904', 'We have implemented a coalescent simulation program for a structured population with selection at a single diploid locus. The program includes the functionality of the simulator ms to model population structure and demography, but adds a model for deme- and time-dependent selection using forward simulations. The program can be used, e.g. to study hard and soft selective sweeps in structured populations or the genetic footprint of local adaptation. The implementation is designed to be easily extendable and widely deployable. The interface and output format are compatible with ms. Performance is comparable even with selection included.'),
(75579, 2010, 'bio', 'Integration of pathway knowledge into a reweighted recursive feature elimination approach for risk stratification of cancer patients', 'Johannes, Marc|Brase, Jan C|Fröhlich, Holger|Gade, Stephan|Gehrmann, Mathias|Fälth, Maria|Sültmann, Holger|Beissbarth, Tim', 'German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de|German Cancer Research Center, Cancer Genome Research, Im Neuenheimer Feld 280, 69120 Heidelberg. m.johannes@DKFZ-heidelberg.de', '-|-|-|-|-|-|-|-', 61, 'Algorithms|Artificial Intelligence|Breast Neoplasms|Female|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Prognosis|ROC Curve|Receptor, ErbB-2|Risk Factors', 'Comparative Study', '10.1093/bioinformatics/btq345', '20591905', 'One of the main goals of high-throughput gene-expression studies in cancer research is to identify prognostic gene signatures, which have the potential to predict the clinical outcome. It is common practice to investigate these questions using classification methods. However, standard methods merely rely on gene-expression data and assume the genes to be independent. Including pathway knowledge a priori into the classification process has recently been indicated as a promising way to increase classification accuracy as well as the interpretability and reproducibility of prognostic gene signatures.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75580, 2010, 'bio', 'Biological knowledge bases using Wikis: combining the flexibility of Wikis with the structure of databases', 'Brohée, Sylvain|Barriot, Roland|Moreau, Yves', 'ESAT-SCD. Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. sbrohee@esat.kuleuven.be|ESAT-SCD. Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. sbrohee@esat.kuleuven.be|ESAT-SCD. Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, B-3001 Leuven, Belgium. sbrohee@esat.kuleuven.be', 'Belgium|Belgium|Belgium', 5, 'Computational Biology|Databases, Factual|Internet|Knowledge Bases|Software', 'Journal Article', '10.1093/bioinformatics/btq348', '20591906', 'In recent years, the number of knowledge bases developed using Wiki technology has exploded. Unfortunately, next to their numerous advantages, classical Wikis present a critical limitation: the invaluable knowledge they gather is represented as free text, which hinders their computational exploitation. This is in sharp contrast with the current practice for biological databases where the data is made available in a structured way. Here, we present WikiOpener an extension for the classical MediaWiki engine that augments Wiki pages by allowing on-the-fly querying and formatting resources external to the Wiki. Those resources may provide data extracted from databases or DAS tracks, or even results returned by local or remote bioinformatics analysis tools. This also implies that structured data can be edited via dedicated forms. Hence, this generic resource combines the structure of biological databases with the flexibility of collaborative Wikis.'),
(75581, 2010, 'bio', 'ABC-SysBio--approximate Bayesian computation in Python with GPU support', 'Liepe, Juliane|Barnes, Chris|Cule, Erika|Erguler, Kamil|Kirk, Paul|Toni, Tina|Stumpf, Michael P H', 'Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.|Centre for Bioinformatics, Division of Molecular Biosciences, Imperial College London, London, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 92, 'Bayes Theorem|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq278', '20591907', 'The growing field of systems biology has driven demand for flexible tools to model and simulate biological systems. Two established problems in the modeling of biological processes are model selection and the estimation of associated parameters. A number of statistical approaches, both frequentist and Bayesian, have been proposed to answer these questions.'),
(75582, 2010, 'bio', 'mbmdr: an R package for exploring gene-gene interactions associated with binary or quantitative traits', 'Calle, M Luz|Urrea, Víctor|Malats, Núria|Van Steen, Kristel', 'Department of Systems Biology, Universitat de Vic. malu.calle@uvic.cat|Department of Systems Biology, Universitat de Vic. malu.calle@uvic.cat|Department of Systems Biology, Universitat de Vic. malu.calle@uvic.cat|Department of Systems Biology, Universitat de Vic. malu.calle@uvic.cat', '-|-|-|-', 63, 'Algorithms|Case-Control Studies|Epistasis, Genetic|Gene Expression|Genotype|Models, Genetic|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Regression Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq352', '20595460', 'We describe mbmdr, an R package for implementing the model-based multifactor dimensionality reduction (MB-MDR) method. MB-MDR has been proposed by Calle et al. as a dimension reduction method for exploring gene-gene interactions in case-control association studies. It is an extension of the popular multifactor dimensionality reduction (MDR) method of Ritchie et al. allowing a more flexible definition of risk cells. In MB-MDR, risk categories are defined using a regression model which allows adjustment for covariates and main effects and, in addition to the classical low risk and high risk categories, MB-MDR considers a third category of indeterminate or not informative cells. An important improvement added to the current mbmdr algorithm with respect to the original MB-MDR formulation in Calle et al. and also to the classical MDR approach, is the extension of the methodology to different outcome types. While MB-MDR was initially proposed for binary traits in the context of case-control studies, the mbmdr package provides options to analyze both binary or quantitative traits for unrelated individuals.'),
(75583, 2010, 'bio', 'Rapid match-searching for gene silencing assessment', 'Horn, Mark E T|Waterhouse, Peter M', 'Division of Mathematics, Informatics and Statistics, CSIRO, North Ryde NSW 1670, Australia. mark.horn@csiro.au|Division of Mathematics, Informatics and Statistics, CSIRO, North Ryde NSW 1670, Australia. mark.horn@csiro.au', 'Australia|Australia', 0, 'Algorithms|Databases, Nucleic Acid|Genome|RNA Interference|RNA, Untranslated|Software', 'Journal Article', '10.1093/bioinformatics/btq318', '20601440', 'Gene silencing, also called RNA interference, requires reliable assessment of silencer impacts. A critical task is to find matches between silencer oligomers and sites in the genome, in accordance with one-to-many matching rules (G-U matching, with provision for mismatches). Fast search algorithms are required to support silencer impact assessments in procedures for designing effective silencer sequences.'),
(75584, 2010, 'bio', 'Modeling and analyzing complex biological networks incooperating experimental information on both network topology and stable states', 'Zou, Yi Ming', 'Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA. ymzou@uwm.edu', 'United States', 0, 'Algorithms|Animals|Drosophila melanogaster|Gene Regulatory Networks|Models, Genetic|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq333', '20601441', 'Linking the topology of a complex network to its long-term behavior is a basic problem in network theory, which has been on the focus of many recent research publications. To obtain a suitable Boolean model for a biological system, one must analyze the initial model and compare it with other experimental evidence, and if necessary, make adjustments by changing the topology of the wiring diagram. However, our knowledge on how to link the topology of a network to its long-term behavior is very limited due to the complexity of the problem. Since the need to consider complex biological networks has become ever greater, develop both theoretical foundation and algorithms for model selection and analysis has been brought to the forefront of biological network study.'),
(75585, 2010, 'bio', 'ExTopoDB: a database of experimentally derived topological models of transmembrane proteins', 'Tsaousis, Georgios N|Tsirigos, Konstantinos D|Andrianou, Xanthi D|Liakopoulos, Theodore D|Bagos, Pantelis G|Hamodrakas, Stavros J', 'Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.|Department of Cell Biology and Biophysics, Faculty of Biology, University of Athens, Panepistimiopolis Athens, Greece.', 'Greece|Greece|Greece|Greece|Greece|Greece', 17, 'Databases, Protein|Membrane Proteins|Protein Conformation|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq362', '20601677', 'ExTopoDB is a publicly accessible database of experimentally derived topological models of transmembrane proteins. It contains information collected from studies in the literature that report the use of biochemical methods for the determination of the topology of xcexb1-helical transmembrane proteins. Transmembrane protein topology is highly important in order to understand their function and ExTopoDB provides an up to date, complete and comprehensive dataset of experimentally determined topologies of xcexb1-helical transmembrane proteins. Topological information is combined with transmembrane topology prediction resulting in more reliable topological models.'),
(75586, 2010, 'bio', 'G-SQZ: compact encoding of genomic sequence and quality data', 'Tembe, Waibhav|Lowey, James|Suh, Edward', 'Translational Genomics Research Institute, 445 N 5th Street, Phoenix, AZ 85004, USA. wtembe@tgen.org|Translational Genomics Research Institute, 445 N 5th Street, Phoenix, AZ 85004, USA. wtembe@tgen.org|Translational Genomics Research Institute, 445 N 5th Street, Phoenix, AZ 85004, USA. wtembe@tgen.org', 'United States|United States|United States', 66, 'Algorithms|Computational Biology|Data Compression|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq346', '20605925', 'Large volumes of data generated by high-throughput sequencing instruments present non-trivial challenges in data storage, content access and transfer. We present G-SQZ, a Huffman coding-based sequencing-reads-specific representation scheme that compresses data without altering the relative order. G-SQZ has achieved from 65% to 81% compression on benchmark datasets, and it allows selective access without scanning and decoding from start. This article focuses on describing the underlying encoding scheme and its software implementation, and a more theoretical problem of optimal compression is out of scope. The immediate practical benefits include reduced infrastructure and informatics costs in managing and analyzing large sequencing data.'),
(75587, 2010, 'bio', 'PERMORY: an LD-exploiting permutation test algorithm for powerful genome-wide association testing', 'Pahl, Roman|Schäfer, Helmut', 'Institut für Medizinische Biometrie und Epidemiologie, Philipps-Universität Marburg, Germany. rpahl@staff.uni-marburg.de|Institut für Medizinische Biometrie und Epidemiologie, Philipps-Universität Marburg, Germany. rpahl@staff.uni-marburg.de', 'Germany|Germany', 31, 'Algorithms|Genetic Markers|Genome-Wide Association Study|Genotype|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btq399', '20605926', 'In genome-wide association studies (GWAS) examining hundreds of thousands of genetic markers, the potentially high number of false positive findings requires statistical correction for multiple testing. Permutation tests are considered the gold standard for multiple testing correction in GWAS, because they simultaneously provide unbiased type I error control and high power. At the same time, they demand heavy computational effort, especially with large-scale datasets of modern GWAS. In recent years, the computational problem has been circumvented by using approximations to permutation tests, which, however, may be biased.'),
(75588, 2010, 'bio', 'TRANSWESD: inferring cellular networks with transitive reduction', 'Klamt, Steffen|Flassig, Robert J|Sundmacher, Kai', 'Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg Centre for SystemsBiology, Sandtorstrasse 1, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg Centre for SystemsBiology, Sandtorstrasse 1, Germany. klamt@mpi-magdeburg.mpg.de|Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg Centre for SystemsBiology, Sandtorstrasse 1, Germany. klamt@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Gene Regulatory Networks|Models, Theoretical', 'Journal Article', '10.1093/bioinformatics/btq342', '20605927', 'Distinguishing direct from indirect influences is a central issue in reverse engineering of biological networks because it facilitates detection and removal of false positive edges. Transitive reduction is one approach for eliminating edges reflecting indirect effects but its use in reconstructing cyclic interaction graphs with true redundant structures is problematic.'),
(75589, 2010, 'bio', 'MamPhEA: a web tool for mammalian phenotype enrichment analysis', 'Weng, Meng-Pin|Liao, Ben-Yang', 'Division of Biostatistics & Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan, ROC.|Division of Biostatistics & Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Miaoli County 350, Taiwan, ROC.', '-|-', 0, 'Animals|Databases, Genetic|Gene Expression|Internet|Mice|Mutation|Phenotype|Software', 'Journal Article', '10.1093/bioinformatics/btq359', '20605928', 'MamPhEA is a web application dedicated to understanding functional properties of mammalian gene sets based on mouse-mutant phenotypes. It allows users to conduct enrichment analysis on predefined or user-defined phenotypes, gives users the option to specify phenotypes derived from null mutations, produces easily comprehensible results and supports analyses on genes of all mammalian species with a fully sequenced genome.'),
(75590, 2010, 'bio', 'Cloud-Coffee: implementation of a parallel consistency-based multiple alignment algorithm in the T-Coffee package and its benchmarking on the Amazon Elastic-Cloud', 'Di Tommaso, Paolo|Orobitg, Miquel|Guirado, Fernando|Cores, Fernado|Espinosa, Toni|Notredame, Cedric', 'Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.|Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.|Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.|Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.|Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.|Centre For Genomic Regulation (Pompeu Fabra University), Carrer del Doctor Aiguader 88, Barcelona, Spain.', 'Spain|Spain|Spain|Spain|Spain|Spain', 20, 'Algorithms|Internet|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq304', '20605929', 'We present the first parallel implementation of the T-Coffee consistency-based multiple aligner. We benchmark it on the Amazon Elastic Cloud (EC2) and show that the parallelization procedure is reasonably effective. We also conclude that for a web server with moderate usage (10K hits/month) the cloud provides a cost-effective alternative to in-house deployment.'),
(75591, 2010, 'bio', 'CNVineta: a data mining tool for large case-control copy number variation datasets', 'Wittig, Michael|Helbig, Ingo|Schreiber, Stefan|Franke, Andre', 'Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, 24105 Kiel, Germany. m.wittig@mucosa.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, 24105 Kiel, Germany. m.wittig@mucosa.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, 24105 Kiel, Germany. m.wittig@mucosa.de|Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel, Schittenhelmstrasse 12, 24105 Kiel, Germany. m.wittig@mucosa.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Data Mining|Gene Dosage|Gene Frequency|Genetic Variation|Genome, Human|Genome-Wide Association Study|Genotype|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq356', '20605930', 'Copy number variation (CNV), a major contributor to human genetic variation, comprises >/= 1 kb genomic deletions and insertions. Yet, the identification of CNVs from microarray data is still hampered by high false negative and positive prediction rates due to the noisy nature of the raw data. Here, we present CNVineta, an R package for rapid data mining and visualization of CNVs in large case-control datasets genotyped with single nucleotide polymorphism oligonucleotide arrays. CNVineta is compatible with various established CNV prediction algorithms, can be used for genome-wide association analysis of rare and common CNVs and enables rapid and serial display of log(2) of raw data ratios as well as B-allele frequencies for visual quality inspection. In summary, CNVineta aides in the interpretation of large-scale CNV datasets and prioritization of target regions for follow-up experiments.'),
(75592, 2010, 'bio', 'Genome-wide functional element detection using pairwise statistical alignment outperforms multiple genome footprinting techniques', 'Satija, R|Hein, J|Lunter, G A', 'Department of Statistics, Oxford University, Oxford, UK. satija@stats.ox.ac.uk|Department of Statistics, Oxford University, Oxford, UK. satija@stats.ox.ac.uk|Department of Statistics, Oxford University, Oxford, UK. satija@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 6, 'Animals|DNA Footprinting|Genome|Humans|Mice|Models, Genetic|ROC Curve|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq360', '20610610', 'Comparative genomic sequence analysis is a powerful approach for identifying putative functional elements in silico. The availability of full-genome sequences from many vertebrate species has resulted in the development of popular tools, for example, the phastCons software package that search large numbers of genomes to identify conserved elements. While phastCons can analyze many genomes simultaneously, it ignores potentially informative insertion and deletion events and relies on a fixed, precomputed multiple sequence alignment.'),
(75593, 2010, 'bio', 'ROAST: rotation gene set tests for complex microarray experiments', 'Wu, Di|Lim, Elgene|Vaillant, François|Asselin-Labat, Marie-Liesse|Visvader, Jane E|Smyth, Gordon K', 'The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.|The Walter and Eliza Hall Institute of Medical Research, 1G Royal Parade, Parkville, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia', 0, 'Algorithms|Animals|Gene Expression Profiling|Humans|Linear Models|Mice|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq401', '20610611', 'A gene set test is a differential expression analysis in which a P-value is assigned to a set of genes as a unit. Gene set tests are valuable for increasing statistical power, organizing and interpreting results and for relating expression patterns across different experiments. Existing methods are based on permutation. Methods that rely on permutation of probes unrealistically assume independence of genes, while those that rely on permutation of sample are suitable only for two-group comparisons with a good number of replicates in each group.'),
(75594, 2010, 'bio', 'Fast overlapping of protein contact maps by alignment of eigenvectors', 'Di Lena, Pietro|Fariselli, Piero|Margara, Luciano|Vassura, Marco|Casadio, Rita', 'Department of Computer Science, University of Bologna, Bologna, Italy. dilena@cs.unibo.it|Department of Computer Science, University of Bologna, Bologna, Italy. dilena@cs.unibo.it|Department of Computer Science, University of Bologna, Bologna, Italy. dilena@cs.unibo.it|Department of Computer Science, University of Bologna, Bologna, Italy. dilena@cs.unibo.it|Department of Computer Science, University of Bologna, Bologna, Italy. dilena@cs.unibo.it', 'Italy|Italy|Italy|Italy|Italy', 20, 'Algorithms|Computational Biology|Protein Conformation|Proteins', 'Comparative Study', '10.1093/bioinformatics/btq402', '20610612', 'Searching for structural similarity is a key issue of protein functional annotation. The maximum contact map overlap (CMO) is one of the possible measures of protein structure similarity. Exact and approximate methods known to optimize the CMO are computationally expensive and this hampers their applicability to large-scale comparison of protein structures.'),
(75595, 2010, 'bio', 'A system-level investigation into the cellular toxic response mechanism mediated by AhR signal transduction pathway', 'Gim, Jungsoo|Kim, Ho-Shik|Kim, Junil|Choi, Minsoo|Kim, Jeong-Rae|Chung, Yeun Jun|Cho, Kwang-Hyun', 'Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology (KAIST), 335 Gwahangno, Yuseong-gu, Daejeon 305-701, Republic of Korea.', '-|-|-|-|-|-|-', 7, 'Cell Hypoxia|Computer Simulation|DNA Damage|Gene Expression Regulation|Hep G2 Cells|Humans|Models, Theoretical|Polychlorinated Dibenzodioxins|Receptors, Aryl Hydrocarbon|Signal Transduction|Tumor Suppressor Protein p53|Up-Regulation', 'Journal Article', '10.1093/bioinformatics/btq400', '20610613', 'Viewing a cellular system as a collection of interacting parts can lead to new insights into the complex cellular behavior. In this study, we have investigated aryl hydrocarbon receptor (AhR) signal transduction pathway from such a system-level perspective. AhR detects various xenobiotics, such as drugs or endocrine disruptors (e.g. dioxin), and mediates transcriptional regulation of target genes such as those in the cytochrome P450 (CYP450) family. On binding with 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), however, AhR becomes abnormally activated and conveys toxic effects on cells. Despite many related studies on the TCDD-mediated toxicity, quantitative system-level understanding of how TCDD-mediated toxicity generates various toxic responses is still lacking.'),
(75596, 2010, 'bio', 'METAL: fast and efficient meta-analysis of genomewide association scans', 'Willer, Cristen J|Li, Yun|Abecasis, Gonçalo R', 'Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109, USA.|Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109, USA.|Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, Michigan 48109, USA.', 'United States|United States|United States', 1835, 'Chromosome Mapping|Computational Biology|Genome-Wide Association Study|Software', 'Journal Article', '10.1093/bioinformatics/btq340', '20616382', 'METAL provides a computationally efficient tool for meta-analysis of genome-wide association scans, which is a commonly used approach for improving power complex traits gene mapping studies. METAL provides a rich scripting interface and implements efficient memory management to allow analyses of very large data sets and to support a variety of input file formats.'),
(75597, 2010, 'bio', 'Global sequence characterization of rice centromeric satellite based on oligomer frequency analysis in large-scale sequencing data', 'Macas, Jirí|Neumann, Pavel|Novák, Petr|Jiang, Jiming', 'Institute of Plant Molecular Biology, Biology Centre ASCR, Branisovska 31, CZ-37005, Ceske Budejovice, Czech Republic. macas@umbr.cas.cz|Institute of Plant Molecular Biology, Biology Centre ASCR, Branisovska 31, CZ-37005, Ceske Budejovice, Czech Republic. macas@umbr.cas.cz|Institute of Plant Molecular Biology, Biology Centre ASCR, Branisovska 31, CZ-37005, Ceske Budejovice, Czech Republic. macas@umbr.cas.cz|Institute of Plant Molecular Biology, Biology Centre ASCR, Branisovska 31, CZ-37005, Ceske Budejovice, Czech Republic. macas@umbr.cas.cz', '-|-|-|-', 30, 'Base Sequence|Centromere|Chromosomes, Plant|Conserved Sequence|DNA, Plant|DNA, Satellite|Molecular Sequence Data|Oryza|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq343', '20616383', 'Satellite DNA makes up significant portion of many eukaryotic genomes, yet it is relatively poorly characterized even in extensively sequenced species. This is, in part, due to methodological limitations of traditional methods of satellite repeat analysis, which are based on multiple alignments of monomer sequences. Therefore, we employed an alternative, alignment-free, approach utilizing k-mer frequency statistics, which is in principle more suitable for analyzing large sets of satellite repeat data, including sequence reads from next generation sequencing technologies.'),
(75598, 2010, 'bio', 'Ontogenomic study of the relationship between number of gene splice variants and GO categorization', 'Kahn, Ari B|Zeeberg, Barry R|Ryan, Michael C|Jamison, D Curtis|Rockoff, David M|Pommier, Yves|Weinstein, John N', 'Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.|Department of Bioinformatics, George Mason University, Fairfax, VA, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Alternative Splicing|Cluster Analysis|Databases, Nucleic Acid|Genes|Genetic Variation|Genome|Genomics|Humans|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btq335', '20616384', 'Splice variation plays important roles in evolution and cancer. Different splice variants of a gene may be characteristic of particular cellular processes, subcellular locations or organs. Although several genomic projects have identified splice variants, there have been no large-scale computational studies of the relationship between number of splice variants and biological function. The Gene Ontology (GO) and tools for leveraging GO, such as GoMiner, now make such a study feasible.'),
(75599, 2010, 'bio', 'First insight into the prediction of protein folding rate change upon point mutation', 'Huang, Liang-Tsung|Gromiha, M Michael', 'Department of Information Communication, Mingdao University, Changhua 523, Taiwan.|Department of Information Communication, Mingdao University, Changhua 523, Taiwan.', '-|-', 20, 'Computational Biology|Point Mutation|Protein Folding|Protein Structure, Secondary|Regression Analysis|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btq350', '20616385', 'The accurate prediction of protein folding rate change upon mutation is an important and challenging problem in protein folding kinetics and design. In this work, we have collected experimental data on protein folding rate change upon mutation from various sources and constructed a reliable and non-redundant dataset with 467 mutants. These mutants are widely distributed based on secondary structure, solvent accessibility, conservation score and long-range contacts. From systematic analysis of these parameters along with a set of 49 amino acid properties, we have selected a set of 12 features for discriminating the mutants that speed up or slow down the folding process. We have developed a method based on quadratic regression models for discriminating the accelerating and decelerating mutants, which showed an accuracy of 74% using the 10-fold cross-validation test. The sensitivity and specificity are 63% and 76%, respectively. The method can be improved with the inclusion of physical interactions and structure-based parameters.'),
(75600, 2010, 'bio', 'Computational analysis of tissue-specific gene networks: application to murine retinal functional studies', 'Hu, Jianfei|Wan, Jun|Hackler, Laszlo|Zack, Donald J|Qian, Jiang', 'Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.|Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA.', 'United States|United States|United States|United States|United States', 0, 'Animals|Bayes Theorem|Databases, Genetic|Databases, Protein|Gene Regulatory Networks|Internet|Mice|ROC Curve|Retina|Retinal Diseases|Software', 'Journal Article', '10.1093/bioinformatics/btq408', '20616386', 'The vertebrate retina is a complex neuronal tissue, and its development, normal functioning and response to injury and disease is subject to a variety of genetic factors. To understand better the regulatory and functional relationships between the genes expressed within the retina, we constructed an interactive gene network of the mouse retina by applying a Bayesian statistics approach to information derived from a variety of gene expression, protein-protein interaction and gene ontology annotation databases.'),
(75601, 2010, 'bio', 'Analyzing taxonomic classification using extensible Markov models', 'Kotamarti, Rao M|Hahsler, Michael|Raiford, Douglas|McGee, Monnie|Dunham, Margaret H', 'Department of Computer Science and Engineering, University of Montana, MT 59812, USA. mallik@kotamarti.com|Department of Computer Science and Engineering, University of Montana, MT 59812, USA. mallik@kotamarti.com|Department of Computer Science and Engineering, University of Montana, MT 59812, USA. mallik@kotamarti.com|Department of Computer Science and Engineering, University of Montana, MT 59812, USA. mallik@kotamarti.com|Department of Computer Science and Engineering, University of Montana, MT 59812, USA. mallik@kotamarti.com', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Markov Chains|Models, Biological|Phylogeny|Proteobacteria|RNA, Ribosomal, 16S|Sequence Alignment', 'Comparative Study', '10.1093/bioinformatics/btq349', '20624777', 'As next generation sequencing is rapidly adding new genomes, their correct placement in the taxonomy needs verification. However, the current methods for confirming classification of a taxon or suggesting revision for a potential misplacement relies on computationally intense multi-sequence alignment followed by an iterative adjustment of the distance matrix. Due to intra-heterogeneity issues with the 16S rRNA marker, no classifier is available for sub-genus level, which could readily suggest a classification for a novel 16S rRNA sequence. Metagenomics further complicates the issue by generating fragmented 16S rRNA sequences. This article proposes a novel alignment-free method for representing the microbial profiles using extensible Markov models (EMMs) with an extended Karlin-Altschul statistical framework similar to the classic alignment paradigm. We propose a log odds (LODs) score classifier based on Gumbel difference distribution that confirms correct classifications with statistical significance qualifications and suggests revisions where necessary.'),
(75602, 2010, 'bio', 'Interactive and fuzzy search: a dynamic way to explore MEDLINE', 'Wang, Jiannan|Cetindil, Inci|Ji, Shengyue|Li, Chen|Xie, Xiaohui|Li, Guoliang|Feng, Jianhua', 'Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.|Department of Computer Science, Tsinghua University, Beijing, China.', 'China|China|China|China|China|China|China', 0, 'Abstracting and Indexing as Topic|Algorithms|Information Storage and Retrieval|Internet|MEDLINE|PubMed|Software|United States', 'Journal Article', '10.1093/bioinformatics/btq414', '20624778', 'The MEDLINE database, consisting of over 19 million publication records, is the primary source of information for biomedicine and health questions. Although the database itself has been growing rapidly, the search paradigm of MEDLINE has remained largely unchanged.'),
(75603, 2010, 'bio', 'Dealing with sparse data in predicting outcomes of HIV combination therapies', 'Bogojeska, Jasmina|Bickel, Steffen|Altmann, André|Lengauer, Thomas', 'Max Planck Institute for Informatics, Campus E1 4, 66123, Saarbrücken and Nokia Gate 5, Berlin, Germany. jasmina@mpi-inf.mpg.de|Max Planck Institute for Informatics, Campus E1 4, 66123, Saarbrücken and Nokia Gate 5, Berlin, Germany. jasmina@mpi-inf.mpg.de|Max Planck Institute for Informatics, Campus E1 4, 66123, Saarbrücken and Nokia Gate 5, Berlin, Germany. jasmina@mpi-inf.mpg.de|Max Planck Institute for Informatics, Campus E1 4, 66123, Saarbrücken and Nokia Gate 5, Berlin, Germany. jasmina@mpi-inf.mpg.de', 'Germany|Germany|Germany|Germany', 8, 'Anti-HIV Agents|Artificial Intelligence|Drug Therapy, Combination|Genotype|HIV|HIV Infections|Humans|Logistic Models|Treatment Outcome', 'Journal Article', '10.1093/bioinformatics/btq361', '20624779', 'As there exists no cure or vaccine for the infection with human immunodeficiency virus (HIV), the standard approach to treating HIV patients is to repeatedly administer different combinations of several antiretroviral drugs. Because of the large number of possible drug combinations, manually finding a successful regimen becomes practically impossible. This presents a major challenge for HIV treatment. The application of machine learning methods for predicting virological responses to potential therapies is a possible approach to solving this problem. However, due to evolving trends in treating HIV patients the available clinical datasets have a highly unbalanced representation, which might negatively affect the usefulness of derived statistical models.'),
(75604, 2010, 'bio', 'An alignment-free method to identify candidate orthologous enhancers in multiple Drosophila genomes', 'Arunachalam, Manonmani|Jayasurya, Karthik|Tomancak, Pavel|Ohler, Uwe', 'Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany.|Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany.|Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany.|Max Planck Institute for Molecular Cell Biology and Genetics, Dresden, Germany.', 'Germany|Germany|Germany|Germany', 12, 'Animals|Drosophila|Enhancer Elements, Genetic|Evolution, Molecular|Genome, Insect|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btq358', '20624780', 'Evolutionarily conserved non-coding genomic sequences represent a potentially rich source for the discovery of gene regulatory region such as transcriptional enhancers. However, detecting orthologous enhancers using alignment-based methods in higher eukaryotic genomes is particularly challenging, as regulatory regions can undergo considerable sequence changes while maintaining their functionality.'),
(75605, 2010, 'bio', 'A comparison of several algorithms for the single individual SNP haplotyping reconstruction problem', 'Geraci, Filippo', 'Istituto di Informatica e Telemetica, CNR, Pisa, Italy. filippo.geraci@iit.cnr.it', 'Italy', 0, 'Algorithms|Base Sequence|Haplotypes|Humans|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1093/bioinformatics/btq411', '20624781', 'Single nucleotide polymorphisms are the most common form of variation in human DNA, and are involved in many research fields, from molecular biology to medical therapy. The technological opportunity to deal with long DNA sequences using shotgun sequencing has raised the problem of fragment recombination. In this regard, Single Individual Haplotyping (SIH) problem has received considerable attention over the past few years.'),
(75606, 2010, 'bio', 'iAlign: a method for the structural comparison of protein-protein interfaces', 'Gao, Mu|Skolnick, Jeffrey', 'Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA, USA.|Center for the Study of Systems Biology, School of Biology, Georgia Institute of Technology, Atlanta, GA, USA.', 'Georgia|Georgia', 2, 'Algorithms|Benchmarking|Humans|Male|Models, Statistical|Protein Conformation|Proteins|Sequence Alignment|Software', 'Comparative Study', '10.1093/bioinformatics/btq404', '20624782', 'Protein-protein interactions play an essential role in many cellular processes. The rapid accumulation of protein-protein complex structures provides an unprecedented opportunity for comparative studies of protein-protein interactions. To facilitate such studies, it is necessary to develop an accurate and efficient computational algorithm for the comparison of protein-protein interaction modes. While there are many structural comparison approaches developed for individual proteins, very few methods are available for protein-protein complexes.'),
(75607, 2010, 'bio', 'genoPlotR: comparative gene and genome visualization in R', 'Guy, Lionel|Kultima, Jens Roat|Andersson, Siv G E', 'Department of Molecular Evolution, Uppsala University, Uppsala, Sweden. lionel.guy@ebc.uu.se|Department of Molecular Evolution, Uppsala University, Uppsala, Sweden. lionel.guy@ebc.uu.se|Department of Molecular Evolution, Uppsala University, Uppsala, Sweden. lionel.guy@ebc.uu.se', 'Sweden|Sweden|Sweden', 9, 'Animals|Chromosome Mapping|Genes|Genome|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btq413', '20624783', 'The amount of gene and genome data obtained by next-generation sequencing technologies generates a need for comparative visualization tools. Complementing existing software for comparison and exploration of genomics data, genoPlotR automatically creates publication-grade linear maps of gene and genomes, in a highly automatic, flexible and reproducible way.'),
(75608, 2010, 'bio', 'Logic Forest: an ensemble classifier for discovering logical combinations of binary markers', 'Wolf, Bethany J|Hill, Elizabeth G|Slate, Elizabeth H', 'Division of Biostatistics and Epidemiology, Medical University of South Carolina, 135 Cannon St., Charleston, SC, USA. wolfb@musc.edu|Division of Biostatistics and Epidemiology, Medical University of South Carolina, 135 Cannon St., Charleston, SC, USA. wolfb@musc.edu|Division of Biostatistics and Epidemiology, Medical University of South Carolina, 135 Cannon St., Charleston, SC, USA. wolfb@musc.edu', 'United States|United States|United States', 13, 'Biomarkers|Computer Simulation|Humans|Models, Biological|Multivariate Analysis|Periodontal Diseases|Polymorphism, Single Nucleotide|Regression Analysis', 'Comparative Study', '10.1093/bioinformatics/btq354', '20628070', 'Highly sensitive and specific screening tools may reduce disease -related mortality by enabling physicians to diagnose diseases in asymptomatic patients or at-risk individuals. Diagnostic tests based on multiple biomarkers may achieve the needed sensitivity and specificity to realize this clinical gain.'),
(75609, 2010, 'bio', 'C-It: a knowledge database for tissue-enriched genes', 'Gellert, Pascal|Jenniches, Katharina|Braun, Thomas|Uchida, Shizuka', 'Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany.|Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany.|Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany.|Max-Planck-Institute for Heart and Lung Research, Bad Nauheim, Germany.', 'Germany|Germany|Germany|Germany', 1, 'Algorithms|Animals|Databases, Genetic|Expressed Sequence Tags|Gene Expression|Gene Expression Profiling|Humans|Internet|Mice|Oligonucleotide Array Sequence Analysis|Rats|User-Computer Interface|Zebrafish', 'Comparative Study', '10.1093/bioinformatics/btq417', '20628071', 'Due to the development of high-throughput technologies such as microarrays, it has become possible to determine genome-wide expression changes in a single experiment. Although much attention has been paid to identify differentially expressed genes, the functions of tens of thousands of genes in different species still remain unknown.'),
(75610, 2010, 'bio', 'A dynamic wavelet-based algorithm for pre-processing tandem mass spectrometry data', 'Wang, Penghao|Yang, Pengyi|Arthur, Jonathan|Yang, Jean Yee Hwa', 'School of Mathematics and Statistics, University of Sydney, Sydney, Australia. penghao.wang@sydney.edu.au|School of Mathematics and Statistics, University of Sydney, Sydney, Australia. penghao.wang@sydney.edu.au|School of Mathematics and Statistics, University of Sydney, Sydney, Australia. penghao.wang@sydney.edu.au|School of Mathematics and Statistics, University of Sydney, Sydney, Australia. penghao.wang@sydney.edu.au', 'Australia|Australia|Australia|Australia', 2, 'Algorithms|Humans|Mass Spectrometry|Models, Statistical|Proteins|Proteomics|Tandem Mass Spectrometry', 'Comparative Study', '10.1093/bioinformatics/btq403', '20628072', 'Mass spectrometry (MS)-based proteomics is one of the most commonly used research techniques for identifying and characterizing proteins in biological and medical research. The identification of a protein is the critical first step in elucidating its biological function. Successful protein identification depends on various interrelated factors, including effective analysis of MS data generated in a proteomic experiment. This analysis comprises several stages, often combined in a pipeline or workflow. The first component of the analysis is known as spectra pre-processing. In this component, the raw data generated by the mass spectrometer is processed to eliminate noise and identify the mass-to-charge ratio (m/z) and intensity for the peaks in the spectrum corresponding to the presence of certain peptides or peptide fragments. Since all downstream analyses depend on the pre-processed data, effective pre-processing is critical to protein identification and characterization. There is a critical need for more robust pre-processing algorithms that perform well on tandem mass spectra under a variety of different conditions and can be easily integrated into sophisticated data analysis pipelines for practical wet-lab applications.'),
(75611, 2010, 'bio', 'BioNetCAD: design, simulation and experimental validation of synthetic biochemical networks', 'Rialle, Stéphanie|Felicori, Liza|Dias-Lopes, Camila|Pérès, Sabine|El Atia, Sanaâ|Thierry, Alain R|Amar, Patrick|Molina, Franck', 'SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr|SysDiag UMR 3145 CNRS/Bio-Rad, Modélisation et ingénierie de systèmes complexes biologiques pour le diagnostic, Cap Delta/Parc Euromédecine, Montpellier, France. stephanie.rialle@sysdiag.cnrs.fr', 'France|France|France|France|France|France|France|France', 0, 'Computational Biology|Computer Simulation|Computer-Aided Design|Databases, Factual|Models, Biological|Programming Languages|Protein Biosynthesis|Proteins|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq409', '20628073', 'Synthetic biology studies how to design and construct biological systems with functions that do not exist in nature. Biochemical networks, although easier to control, have been used less frequently than genetic networks as a base to build a synthetic system. To date, no clear engineering principles exist to design such cell-free biochemical networks.'),
(75612, 2010, 'bio', 'OWL2Perl: creating Perl modules from OWL class definitions', 'Kawas, Edward|Wilkinson, Mark D', 'Heart + Lung Institute at St. Pauls Hospital, Vancouver, BC, Canada. edward.kawas@gmail.com|Heart + Lung Institute at St. Pauls Hospital, Vancouver, BC, Canada. edward.kawas@gmail.com', 'Canada|Canada', 0, 'Internet|Programming Languages|Semantics|Software', 'Journal Article', '10.1093/bioinformatics/btq416', '20628074', 'Support for utilizing OWL ontologies in Perl is extremely limited, despite the growing importance of the Semantic Web in Healthcare and Life Sciences. Here, we present a Perl framework that generates Perl modules based on OWL Class definitions. These modules can then be used by other software applications to create resource description framework (RDF) data compliant with these OWL models.'),
(75613, 2010, 'bio', 'Editing, validating and translating of SBGN maps', 'Czauderna, Tobias|Klukas, Christian|Schreiber, Falk', 'Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Martin Luther University of Halle-Wittenberg, Halle, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Martin Luther University of Halle-Wittenberg, Halle, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research (IPK) Gatersleben, Martin Luther University of Halle-Wittenberg, Halle, Germany.', 'Germany|Germany|Germany', 0, 'Computer Graphics|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq407', '20628075', 'The recently proposed Systems Biology Graphical Notation (SBGN) provides a standard for the visual representation of biochemical and cellular processes. It aims to support more efficient and accurate communication of biological knowledge between different research communities in the life sciences. However, to increase the use of SBGN, tools for editing, validating and translating SBGN maps are desirable.'),
(75614, 2010, 'bio', 'PriorsEditor: a tool for the creation and use of positional priors in motif discovery', 'Klepper, Kjetil|Drabløs, Finn', 'Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no|Department of Cancer Research and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway. kjetil.klepper@ntnu.no', 'Norway|Norway', 0, 'Algorithms|Amino Acid Motifs|Binding Sites|Sequence Analysis, DNA|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq357', '20628076', 'Computational methods designed to discover transcription factor binding sites in DNA sequences often have a tendency to make a lot of false predictions. One way to improve accuracy in motif discovery is to rely on positional priors to focus the search to parts of a sequence that are considered more likely to contain functional binding sites. We present here a program called PriorsEditor that can be used to create such positional priors tracks based on a combination of several features, including phylogenetic conservation, nucleosome occupancy, histone modifications, physical properties of the DNA helix and many more.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75615, 2010, 'bio', 'MetPA: a web-based metabolomics tool for pathway analysis and visualization', 'Xia, Jianguo|Wishart, David S', 'Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.|Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.', 'Canada|Canada', 139, 'Humans|Internet|Metabolic Networks and Pathways|Metabolomics|Neoplasms|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq418', '20628077', 'MetPA (Metabolomics Pathway Analysis) is a user-friendly, web-based tool dedicated to the analysis and visualization of metabolomic data within the biological context of metabolic pathways. MetPA combines several advanced pathway enrichment analysis procedures along with the analysis of pathway topological characteristics to help identify the most relevant metabolic pathways involved in a given metabolomic study. The results are presented in a Google-map style network visualization system that supports intuitive and interactive data exploration through point-and-click, dragging and lossless zooming. Additional features include a comprehensive compound library for metabolite name conversion, automatic generation of analysis report, as well as the implementation of various univariate statistical procedures that can be accessed when users click on any metabolite node on a pathway map. MetPA currently enables analysis and visualization of 874 metabolic pathways, covering 11 common model organisms.'),
(75616, 2010, 'bio', 'ANAIS: analysis of NimbleGen arrays interface', 'Simon, Adeline|Biot, Eric', 'UR1290 BIOGER-CPP, INRA, Grignon, France. simon@versailles.inra.fr|UR1290 BIOGER-CPP, INRA, Grignon, France. simon@versailles.inra.fr', 'France|France', 31, 'Algorithms|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq410', '20631159', 'ANAIS is a user-friendly web-based tool for the processing of NimbleGen expression data. The interface reads single-channel microarray files generated by NimbleGen platforms and produces easily interpretable graphical and numerical results. It provides biologists six turnkey analysis modules-normalization, probe to gene, quality controls, differential expression, detection, queries and clustering-to explore quickly, freely and without the need for computer programming, NimbleGen transcriptome data.'),
(75617, 2010, 'bio', 'Probabilistic analysis of gene expression measurements from heterogeneous tissues', 'Erkkilxc3xa4, Timo|Lehmusvaara, Saara|Ruusuvuori, Pekka|Visakorpi, Tapio|Shmulevich, Ilya|Lxc3xa4hdesmxc3xa4ki, Harri', 'Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi|Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi|Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi|Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi|Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi|Department of Signal Processing, Tampere University of Technology, Finland. timo.p.erkkila@tut.fi', 'Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Biomarkers|Gene Expression Profiling|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq406', '20631160', 'Tissue heterogeneity, arising from multiple cell types, is a major confounding factor in experiments that focus on studying cell types, e.g. their expression profiles, in isolation. Although sample heterogeneity can be addressed by manual microdissection, prior to conducting experiments, computational treatment on heterogeneous measurements have become a reliable alternative to perform this microdissection in silico. Favoring computation over manual purification has its advantages, such as time consumption, measuring responses of multiple cell types simultaneously, keeping samples intact of external perturbations and unaltered yield of molecular content.'),
(75618, 2010, 'bio', 'LocusZoom: regional visualization of genome-wide association scan results', 'Pruim, Randall J|Welch, Ryan P|Sanna, Serena|Teslovich, Tanya M|Chines, Peter S|Gliedt, Terry P|Boehnke, Michael|Abecasis, Gonçalo R|Willer, Cristen J', 'Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.|Department of Mathematics and Statistics, Calvin College, Grand Rapids, MI 49546, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 46, 'Computer Graphics|Genome-Wide Association Study|Humans|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btq419', '20634204', 'Genome-wide association studies (GWAS) have revealed hundreds of loci associated with common human genetic diseases and traits. We have developed a web-based plotting tool that provides fast visual display of GWAS results in a publication-ready format. LocusZoom visually displays regional information such as the strength and extent of the association signal relative to genomic position, local linkage disequilibrium (LD) and recombination patterns and the positions of genes in the region.'),
(75619, 2010, 'bio', 'RPPanalyzer: Analysis of reverse-phase protein array data', 'Mannsperger, Heiko A|Gade, Stephan|Henjes, Frauke|Beissbarth, Tim|Korf, Ulrike', 'Department of Molecular Genome Analysis, German Cancer Research Center Heidelberg, Germany. h.mannsperger@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center Heidelberg, Germany. h.mannsperger@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center Heidelberg, Germany. h.mannsperger@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center Heidelberg, Germany. h.mannsperger@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center Heidelberg, Germany. h.mannsperger@dkfz.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Protein Array Analysis|Proteomics|Software', 'Journal Article', '10.1093/bioinformatics/btq347', '20634205', 'RPPanalyzer is a statistical tool developed to read reverse-phase protein array data, to perform the basic data analysis and to visualize the resulting biological information. The R-package provides different functions to compare protein expression levels of different samples and to normalize the data. Implemented plotting functions permit a quality control by monitoring data distribution and signal validity. Finally, the data can be visualized in heatmaps, boxplots, time course plots and correlation plots. RPPanalyzer is a flexible tool and tolerates a huge variety of different experimental designs.'),
(75620, 2010, 'bio', 'On reverse engineering of gene interaction networks using time course data with repeated measurements', 'Morrissey, E R|Juárez, M A|Denby, K J|Burroughs, N J', 'Warwick Systems Biology Centre and Warwick HRI, University of Warwick, Coventry, UK.|Warwick Systems Biology Centre and Warwick HRI, University of Warwick, Coventry, UK.|Warwick Systems Biology Centre and Warwick HRI, University of Warwick, Coventry, UK.|Warwick Systems Biology Centre and Warwick HRI, University of Warwick, Coventry, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Arabidopsis|Bayes Theorem|Circadian Rhythm|Computer Simulation|Gene Expression Profiling|Gene Regulatory Networks|Models, Genetic|Uncertainty', 'Journal Article', '10.1093/bioinformatics/btq421', '20639410', 'Gene expression measurements are the most common data source for reverse engineering gene interaction networks. When dealing with destructive sampling in time course experiments, it is common to average any available measurements for each time point and to treat this as the actual time series data for fitting the network, neglecting the variability contained in the repeated measurements. Proceeding in such a way can affect the retrieved network topology.'),
(75621, 2010, 'bio', 'Multiple gene expression profile alignment for microarray time-series data clustering', 'Subhani, Numanul|Rueda, Luis|Ngom, Alioune|Burden, Conrad J', 'School of Computer Science, University of Windsor, Windsor, Ontario, Canada.|School of Computer Science, University of Windsor, Windsor, Ontario, Canada.|School of Computer Science, University of Windsor, Windsor, Ontario, Canada.|School of Computer Science, University of Windsor, Windsor, Ontario, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Cluster Analysis|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq422', '20639411', 'Clustering gene expression data given in terms of time-series is a challenging problem that imposes its own particular constraints. Traditional clustering methods based on conventional similarity measures are not always suitable for clustering time-series data. A few methods have been proposed recently for clustering microarray time-series, which take the temporal dimension of the data into account. The inherent principle behind these methods is to either define a similarity measure appropriate for temporal expression data, or pre-process the data in such a way that the temporal relationships between and within the time-series are considered during the subsequent clustering phase.'),
(75622, 2010, 'bio', 'BigWig and BigBed: enabling browsing of large distributed datasets', 'Kent, W J|Zweig, A S|Barber, G|Hinrichs, A S|Karolchik, D', 'Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.|Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz (UCSC), Santa Cruz, CA 95064, USA.', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Data Compression|Data Mining|Genomics|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btq351', '20639541', 'BigWig and BigBed files are compressed binary indexed files containing data at several resolutions that allow the high-performance display of next-generation sequencing experiment results in the UCSC Genome Browser. The visualization is implemented using a multi-layered software approach that takes advantage of specific capabilities of web-based protocols and Linux and UNIX operating systems files, R trees and various indexing and compression tricks. As a result, only the data needed to support the current browser view is transmitted rather than the entire file, enabling fast remote access to large distributed data sets.'),
(75623, 2010, 'bio', 'Predictive models for population performance on real biological fitness landscapes', 'Rowe, William|Wedge, David C|Platt, Mark|Kell, Douglas B|Knowles, Joshua', 'Faculty of Life Sciences, The University of Manchester, Michael Smith Building, UK. william.rowe@manchester.ac.uk|Faculty of Life Sciences, The University of Manchester, Michael Smith Building, UK. william.rowe@manchester.ac.uk|Faculty of Life Sciences, The University of Manchester, Michael Smith Building, UK. william.rowe@manchester.ac.uk|Faculty of Life Sciences, The University of Manchester, Michael Smith Building, UK. william.rowe@manchester.ac.uk|Faculty of Life Sciences, The University of Manchester, Michael Smith Building, UK. william.rowe@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Crossing Over, Genetic|Directed Molecular Evolution|Finite Element Analysis|Genetic Fitness|Models, Statistical|Mutation|Phycocyanin', 'Journal Article', '10.1093/bioinformatics/btq353', '20639542', 'Directed evolution, in addition to its principal application of obtaining novel biomolecules, offers significant potential as a vehicle for obtaining useful information about the topologies of biomolecular fitness landscapes. In this article, we make use of a special type of model of fitness landscapes-based on finite state machines-which can be inferred from directed evolution experiments. Importantly, the model is constructed only from the fitness data and phylogeny, not sequence or structural information, which is often absent. The model, called a landscape state machine (LSM), has already been used successfully in the evolutionary computation literature to model the landscapes of artificial optimization problems. Here, we use the method for the first time to simulate a biological fitness landscape based on experimental evaluation.'),
(75624, 2010, 'bio', 'Towards optimal alignment of protein structure distance matrices', 'Wohlers, Inken|Domingues, Francisco S|Klau, Gunnar W', 'CWI, Life Sciences Group, Amsterdam, The Netherlands. Inken.Wohlers@cwi.nl|CWI, Life Sciences Group, Amsterdam, The Netherlands. Inken.Wohlers@cwi.nl|CWI, Life Sciences Group, Amsterdam, The Netherlands. Inken.Wohlers@cwi.nl', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Humans|Models, Chemical|Protein Conformation|Proteins|Sequence Alignment|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq420', '20639543', 'Structural alignments of proteins are important for identification of structural similarities, homology detection and functional annotation. The structural alignment problem is well studied and computationally difficult. Many different scoring schemes for structural similarity as well as many algorithms for finding high-scoring alignments have been proposed. Algorithms using contact map overlap (CMO) as scoring function are currently the only practical algorithms able to compute provably optimal alignments.'),
(75625, 2010, 'bio', 'SVDetect: a tool to identify genomic structural variations from paired-end and mate-pair sequencing data', 'Zeitouni, Bruno|Boeva, Valentina|Janoueix-Lerosey, Isabelle|Loeillet, Sophie|Legoix-né, Patricia|Nicolas, Alain|Delattre, Olivier|Barillot, Emmanuel', 'INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr|INSERM U900, Institut Curie, Paris, France. svdetect@curie.fr', 'France|France|France|France|France|France|France|France', 138, 'Genome|Genomic Structural Variation|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btq293', '20639544', 'We present SVDetect, a program designed to identify genomic structural variations from paired-end and mate-pair next-generation sequencing data produced by the Illumina GA and ABI SOLiD platforms. Applying both sliding-window and clustering strategies, we use anomalously mapped read pairs provided by current short read aligners to localize genomic rearrangements and classify them according to their type, e.g. large insertions-deletions, inversions, duplications and balanced or unbalanced inter-chromosomal translocations. SVDetect outputs predicted structural variants in various file formats for appropriate graphical visualization.'),
(75626, 2010, 'bio', 'Ontology for medicinal materials based on traditional Korean medicine', 'Jang, Hyunchul|Kim, Jinhyun|Kim, Sang-Kyun|Kim, Chul|Bae, Soon-Hee|Kim, Anna|Eom, Dong-Myung|Song, Mi-Young', 'Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.|Information Research Center, Korea Institute of Oriental Medicine, Yuseong-gu, Daejeon, Republic of Korea.', '-|-|-|-|-|-|-|-', 1, 'Disease|Humans|Internet|Medicine, Korean Traditional', 'Journal Article', '10.1093/bioinformatics/btq424', '20647520', 'We are constructing an ontology for traditional Korean medicine, and we started with medicinal materials to express the relationships between patients symptoms, diseases and treatments. Biological materials and mineral resources have been used traditionally for patient treatments. The ontology includes various data related to these materials, such as their scientific names, parts of materials used, effectiveness and related oriental organ of the human body.'),
(75627, 2010, 'bio', 'PathwayAccess: CellDesigner plugins for pathway databases', 'Van Hemert, John L|Dickerson, Julie A', 'Bioinformatics and Computational Biology Department, Iowa State University, Ames, IA 50011, USA.|Bioinformatics and Computational Biology Department, Iowa State University, Ames, IA 50011, USA.', 'United States|United States', 0, 'Databases, Factual|Metabolic Networks and Pathways|Software', 'Journal Article', '10.1093/bioinformatics/btq423', '20647521', 'CellDesigner provides a user-friendly interface for graphical biochemical pathway description. Many pathway databases are not directly exportable to CellDesigner models. PathwayAccess is an extensible suite of CellDesigner plugins, which connect CellDesigner directly to pathway databases using respective Java application programming interfaces. The process is streamlined for creating new PathwayAccess plugins for specific pathway databases. Three PathwayAccess plugins, MetNetAccess, BioCycAccess and ReactomeAccess, directly connect CellDesigner to the pathway databases MetNetDB, BioCyc and Reactome. PathwayAccess plugins enable CellDesigner users to expose pathway data to analytical CellDesigner functions, curate their pathway databases and visually integrate pathway data from different databases using standard Systems Biology Markup Language and Systems Biology Graphical Notation.'),
(75628, 2010, 'bio', 'Prophossi: automating expert validation of phosphopeptide-spectrum matches from tandem mass spectrometry', 'Martin, David M A|Nett, Isabelle R E|Vandermoere, Franck|Barber, Jonathan D|Morrice, Nicholas A|Ferguson, Michael A J', 'Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of LifeSciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. d.m.a.martin@dundee.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Algorithms|Automation|Databases, Factual|Phosphopeptides|Phosphorylation|Protein Processing, Post-Translational|Software|Tandem Mass Spectrometry|Trypanosoma brucei brucei', 'Comparative Study', '10.1093/bioinformatics/btq341', '20651112', 'Complex patterns of protein phosphorylation mediate many cellular processes. Tandem mass spectrometry (MS/MS) is a powerful tool for identifying these post-translational modifications. In high-throughput experiments, mass spectrometry database search engines, such as MASCOT provide a ranked list of peptide identifications based on hundreds of thousands of MS/MS spectra obtained in a mass spectrometry experiment. These search results are not in themselves sufficient for confident assignment of phosphorylation sites as identification of characteristic mass differences requires time-consuming manual assessment of the spectra by an experienced analyst. The time required for manual assessment has previously rendered high-throughput confident assignment of phosphorylation sites challenging.'),
(75629, 2010, 'bio', 'Cytoscape Web: an interactive web-based network browser', 'Lopes, Christian T|Franz, Max|Kazi, Farzana|Donaldson, Sylva L|Morris, Quaid|Bader, Gary D', 'Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 24, 'Internet|Software', 'Journal Article', '10.1093/bioinformatics/btq430', '20656902', 'Cytoscape Web is a web-based network visualization tool-modeled after Cytoscape-which is open source, interactive, customizable and easily integrated into web sites. Multiple file exchange formats can be used to load data into Cytoscape Web, including GraphML, XGMML and SIF.'),
(75630, 2010, 'bio', 'A fast and robust statistical test based on likelihood ratio with Bartlett correction to identify Granger causality between gene sets', 'Fujita, André|Kojima, Kaname|Patriota, Alexandre G|Sato, João R|Severino, Patricia|Miyano, Satoru', 'Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp|Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp|Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp|Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp|Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp|Computational Science Research Program, RIKEN, Wako, Saitama, Japan. andrefujita@riken.jp', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Computer Simulation|Gene Expression|Likelihood Functions|Models, Statistical', 'Evaluation Studies', '10.1093/bioinformatics/btq427', '20660295', 'We propose a likelihood ratio test (LRT) with Bartlett correction in order to identify Granger causality between sets of time series gene expression data. The performance of the proposed test is compared to a previously published bootstrap-based approach. LRT is shown to be significantly faster and statistically powerful even within non-Normal distributions. An R package named gGranger containing an implementation for both Granger causality identification tests is also provided.'),
(75631, 2010, 'bio', 'Integrative classification and analysis of multiple arrayCGH datasets with probe alignment', 'Tian, Ze|Kuang, Rui', 'Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA.|Department of Computer Science and Engineering, University of Minnesota Twin Cities, Minneapolis, MN, USA.', 'United States|United States', 0, 'Algorithms|Comparative Genomic Hybridization|Computer Simulation|DNA Copy Number Variations|DNA Probes|DNA, Neoplasm|Humans|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Software|Urinary Bladder Neoplasms', 'Comparative Study', '10.1093/bioinformatics/btq428', '20660296', 'Array comparative genomic hybridization (arrayCGH) is widely used to measure DNA copy numbers in cancer research. ArrayCGH data report log-ratio intensities of thousands of probes sampled along the chromosomes. Typically, the choices of the locations and the lengths of the probes vary in different experiments. This discrepancy in choosing probes poses a challenge in integrated classification or analysis across multiple arrayCGH datasets. We propose an alignment-based framework to integrate arrayCGH samples generated from different probe sets. The alignment framework seeks an optimal alignment between the probe series of one arrayCGH sample and the probe series of another sample, intended to find the maximum possible overlap of DNA copy number variations between the two measured chromosomes. An alignment kernel is introduced for integrative patient sample classification and a multiple alignment algorithm is also introduced for identifying common regions with copy number aberrations.'),
(75632, 2010, 'bio', 'Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites', 'Ramsey, Stephen A|Knijnenburg, Theo A|Kennedy, Kathleen A|Zak, Daniel E|Gilchrist, Mark|Gold, Elizabeth S|Johnson, Carrie D|Lampano, Aaron E|Litvak, Vladimir|Navarro, Garnet|Stolyar, Tetyana|Aderem, Alan|Shmulevich, Ilya', 'Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org|Institute for Systems Biology, 1441 North 34th Street, Seattle, WA 98103, USA. aderem@systemsbiology.org', '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', 49, 'Acetylation|Animals|Binding Sites|Chromatin Immunoprecipitation|Genome|Histones|Macrophage Activation|Mice|Models, Biological|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq405', '20663846', 'Histone acetylation (HAc) is associated with open chromatin, and HAc has been shown to facilitate transcription factor (TF) binding in mammalian cells. In the innate immune system context, epigenetic studies strongly implicate HAc in the transcriptional response of activated macrophages. We hypothesized that using data from large-scale sequencing of a HAc chromatin immunoprecipitation assay (ChIP-Seq) would improve the performance of computational prediction of binding locations of TFs mediating the response to a signaling event, namely, macrophage activation.'),
(75633, 2010, 'bio', 'proTF: a comprehensive data and phylogenomics resource for prokaryotic transcription factors', 'Bai, Jie|Wang, Junrong|Xue, Feng|Li, Jingsong|Bu, Lijing|Hu, Junming|Xu, Gang|Bao, Qiyu|Zhao, Guoping|Ding, Xiaoming|Yan, Jie|Wu, Jinyu', 'Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.|Institute of Genomic Medicine/Zhejiang Provincial Key Laboratory of Medical Genetics, Wenzhou Medical College, Wenzhou 325035, China.', 'China|China|China|China|China|China|China|China|China|China|China|China', 2, 'Archaeal Proteins|Bacterial Proteins|Databases, Genetic|Genome|Genomics|Internet|Phylogeny|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq432', '20663847', 'Investigation of transcription factors (TFs) is of extreme significance for gleaning more information about the mechanisms underlying the dynamic transcriptional regulatory network. Herein, proTF is constructed to serve as a comprehensive data resource and phylogenomics analysis platform for prokaryotic TFs. It has many prominent characteristics: (i) detailed annotation information, including basic sequence features, domain organization, sequence homolog and sequence composition, was extensively collected, and then visually displayed for each TF entry in all prokaryotic genomes, (ii) workset was employed as the basic frame to provide an efficient way to organize the retrieved data and save intermediate records, and (iii) a number of elaborated tools for phylogenomics analysis were implemented to investigate the evolutionary roles of specific TFs. In conclusion, proTF dedicates to the prokaryotic TFs with integrated multi-function, which will become a valuable resource for prokaryotic transcriptional regulatory network in the post-genomic era.'),
(75634, 2010, 'bio', 'RepMaestro: scalable repeat detection on disk-based genome sequences', 'Askitis, Nikolas|Sinha, Ranjan', 'Department of Computer Science and Software Engineering, University of Melbourne, Australia. askitisn@gmail.com|Department of Computer Science and Software Engineering, University of Melbourne, Australia. askitisn@gmail.com', 'Australia|Australia', 2, 'Algorithms|Base Sequence|Databases, Genetic|Genome|Genomics|Software', 'Journal Article', '10.1093/bioinformatics/btq433', '20663848', 'We investigate the problem of exact repeat detection on large genomic sequences. Most existing approaches based on suffix trees and suffix arrays (SAs) are limited either to small sequences or those that are memory resident. We introduce RepMaestro, a software that adapts existing in-memory-enhanced SA algorithms to enable them to scale efficiently to large sequences that are disk resident. Supermaximal repeats, maximal unique matches (MuMs) and pairwise branching tandem repeats have been used to demonstrate the practicality of our approach, the first such study to use an enhanced SA to detect these repeats in large genome sequences.'),
(75635, 2010, 'bio', 'MetNetMaker: a free and open-source tool for the creation of novel metabolic networks in SBML format', 'Forth, Thomas|McConkey, Glenn A|Westhead, David R', 'Faculty of Biological Sciences, University of Leeds, Leeds, UK. pytf@leeds.ac.uk|Faculty of Biological Sciences, University of Leeds, Leeds, UK. pytf@leeds.ac.uk|Faculty of Biological Sciences, University of Leeds, Leeds, UK. pytf@leeds.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 1, 'Metabolic Networks and Pathways|Programming Languages|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq425', '20671147', 'An application has been developed to help with the creation and editing of Systems Biology Markup Language (SBML) format metabolic networks up to the organism scale. Networks are defined as a collection of Kyoto Encyclopedia of Genes and Genomes (KEGG) LIGAND reactions with an optional associated Enzyme Classification (EC) number for each reaction. Additional custom reactions can be defined by the user. Reactions within the network can be assigned flux constraints and compartmentalization is supported for each reaction in addition to the support for reactions that occur across compartment boundaries. Exported networks are fully SBML L2V4 compatible with an optional L2V1 export for compatibility with old versions of the COBRA toolbox.'),
(75636, 2010, 'bio', 'Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data', 'Benton, H Paul|Want, Elizabeth J|Ebbels, Timothy M D', 'Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, Imperial College London, London, SW7 2AZ, UK. hpaul.benton08@imperial.ac.uk|Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, Imperial College London, London, SW7 2AZ, UK. hpaul.benton08@imperial.ac.uk|Biomolecular Medicine, Department of Surgery and Cancer, Faculty of Medicine, Sir Alexander Fleming Building, Imperial College London, London, SW7 2AZ, UK. hpaul.benton08@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 84, 'Calibration|Chromatography, Liquid|Databases, Factual|Mass Spectrometry|Metabolomics|Proteome', 'Journal Article', '10.1093/bioinformatics/btq441', '20671148', 'High mass accuracy is an important goal in liquid chromatography-mass spectrometry experiments. Some manufacturers employ a mass calibration system that regularly switches between the analyte and a standard reference compound, and leads to gaps in the analyte data. We present a method for correction of such gaps in global molecular profiling applications such as metabolomics. We demonstrate that it improves peak detection and quantification, successfully recovering the expected number of peaks and intensity distribution in an example metabolomics dataset.'),
(75637, 2010, 'bio', 'ExpressionView--an interactive viewer for modules identified in gene expression data', 'Lüscher, Andreas|Csárdi, Gábor|de Lachapelle, Aitana Morton|Kutalik, Zoltán|Peter, Bastian|Bergmann, Sven', 'Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.|Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.|Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.|Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.|Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.|Swiss Institute of Bioinformatics, University of Lausanne, Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 4, 'Algorithms|Computer Graphics|Gene Expression|Gene Expression Profiling|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq334', '20671149', 'ExpressionView is an R package that provides an interactive graphical environment to explore transcription modules identified in gene expression data. A sophisticated ordering algorithm is used to present the modules with the expression in a visually appealing layout that provides an intuitive summary of the results. From this overview, the user can select individual modules and access biologically relevant metadata associated with them.'),
(75638, 2010, 'bio', 'TreesimJ: a flexible, forward time population genetic simulator', 'OFallon, Brendan', 'Department of Genome Sciences, Foege Building S-250, Box 355065 3720 15th Ave NE, Seattle, WA 98195-5065, USA. brendano@u.washington.edu', 'United States', 12, 'Biological Evolution|Computer Simulation|Genetics, Population|Models, Genetic|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq355', '20671150', 'Most population genetic simulators fall into one of two classes, backward time simulators that quickly generate trees but accommodate only relatively simple selective and demographic regimes, and forward simulators that allow for a broader range of evolutionary scenarios but which cannot produce genealogies. Thus, few tools are available that allow for producing genealogies under arbitrarily complex selective and demographic models.'),
(75639, 2010, 'bio', 'Datamonkey 2010: a suite of phylogenetic analysis tools for evolutionary biology', 'Delport, Wayne|Poon, Art F Y|Frost, Simon D W|Kosakovsky Pond, Sergei L', 'Department of Pathology, Antiviral Research Center, University of California, San Diego, CA, USA.|Department of Pathology, Antiviral Research Center, University of California, San Diego, CA, USA.|Department of Pathology, Antiviral Research Center, University of California, San Diego, CA, USA.|Department of Pathology, Antiviral Research Center, University of California, San Diego, CA, USA.', 'United States|United States|United States|United States', 842, 'Algorithms|Computational Biology|Evolution, Molecular|HIV-1|Internet|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq429', '20671151', 'Datamonkey is a popular web-based suite of phylogenetic analysis tools for use in evolutionary biology. Since the original release in 2005, we have expanded the analysis options to include recently developed algorithmic methods for recombination detection, evolutionary fingerprinting of genes, codon model selection, co-evolution between sites, identification of sites, which rapidly escape host-immune pressure and HIV-1 subtype assignment. The traditional selection tools have also been augmented to include recent developments in the field. Here, we summarize the analyses options currently available on Datamonkey, and provide guidelines for their use in evolutionary biology. Availability and documentation: http://www.datamonkey.org.'),
(75640, 2010, 'bio', 'Multi-objective pairwise RNA sequence alignment', 'Taneda, Akito', 'Graduate School of Science and Technology, Hirosaki University, Hirosaki, Aomori 036-8561, Japan. taneda@cc.hirosaki-u.ac.jp', 'Japan', 26, 'Algorithms|Base Sequence|Databases, Genetic|RNA|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btq439', '20679330', 'With an increase in the number of known biological functions of non-coding RNAs, the importance of RNA sequence alignment has risen. RNA sequence alignment problem has been investigated by many researchers as a mono-objective optimization problem where contributions from sequence similarity and secondary structure are taken into account through a single objective function. Since there is a trade-off between these two objective functions, usually we cannot obtain a single solution that has both the best sequence similarity score and the best structure score simultaneously. Multi-objective optimization is a widely used framework for the optimization problems with conflicting objective functions. So far, no one has examined how good alignments we can obtain by applying multi-objective optimization to structural RNA sequence alignment problem.'),
(75641, 2010, 'bio', 'The CoFactor database: organic cofactors in enzyme catalysis', 'Fischer, Julia D|Holliday, Gemma L|Thornton, Janet M', 'EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. julia.fischer@ebi.ac.uk|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. julia.fischer@ebi.ac.uk|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK. julia.fischer@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 27, 'Biocatalysis|Catalysis|Coenzymes|Databases, Factual|Enzymes|Internet|Protein Conformation', 'Journal Article', '10.1093/bioinformatics/btq442', '20679331', 'Organic enzyme cofactors are involved in many enzyme reactions. Therefore, the analysis of cofactors is crucial to gain a better understanding of enzyme catalysis. To aid this, we have created the CoFactor database.'),
(75642, 2010, 'bio', 'Exposing the co-adaptive potential of protein-protein interfaces through computational sequence design', 'Fromer, Menachem|Linial, Michal', 'School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.', 'Israel|Israel', 5, 'Adaptation, Biological|Base Sequence|Computational Biology|Evolution, Molecular|Mutation|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/btq412', '20679332', 'In nature, protein-protein interactions are constantly evolving under various selective pressures. Nonetheless, it is expected that crucial interactions are maintained through compensatory mutations between interacting proteins. Thus, many studies have used evolutionary sequence data to extract such occurrences of correlated mutation. However, this research is confounded by other evolutionary pressures that contribute to sequence covariance, such as common ancestry.'),
(75643, 2010, 'bio', 'Multi-netclust: an efficient tool for finding connected clusters in multi-parametric networks', 'Kuzniar, Arnold|Dhir, Somdutta|Nijveen, Harm|Pongor, Sándor|Leunissen, Jack A M', 'Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.|Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.|Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.|Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.|Laboratory of Bioinformatics, Wageningen University and Research Centre, PO Box 569, 6700 AN Wageningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 2, 'Algorithms|Cluster Analysis|Databases, Factual|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq435', '20679333', 'Multi-netclust is a simple tool that allows users to extract connected clusters of data represented by different networks given in the form of matrices. The tool uses user-defined threshold values to combine the matrices, and uses a straightforward, memory-efficient graph algorithm to find clusters that are connected in all or in either of the networks. The tool is written in C/C++ and is available either as a form-based or as a command-line-based program running on Linux platforms. The algorithm is fast, processing a network of > 10(6) nodes and 10(8) edges takes only a few minutes on an ordinary computer.'),
(75644, 2010, 'bio', 'ISA software suite: supporting standards-compliant experimental annotation and enabling curation at the community level', 'Rocca-Serra, Philippe|Brandizi, Marco|Maguire, Eamonn|Sklyar, Nataliya|Taylor, Chris|Begley, Kimberly|Field, Dawn|Harris, Stephen|Hide, Winston|Hofmann, Oliver|Neumann, Steffen|Sterk, Peter|Tong, Weida|Sansone, Susanna-Assunta', 'The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, UK.|The European Bioinformatics Institute, Wellcome Trust Genome Campus, 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', 5, 'Checklist|Documentation|Software', 'Journal Article', '10.1093/bioinformatics/btq415', '20679334', 'The first open source software suite for experimentalists and curators that (i) assists in the annotation and local management of experimental metadata from high-throughput studies employing one or a combination of omics and other technologies, (ii) empowers users to uptake community-defined checklists and ontologies, and (iii) facilitates submission to international public repositories.'),
(75645, 2010, 'bio', 'PSExplorer: whole parameter space exploration for molecular signaling pathway dynamics', 'Tung, Thai Quang|Lee, Doheon', 'Department of Bio and Brain Engineering, KAIST 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.|Department of Bio and Brain Engineering, KAIST 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Republic of Korea.', '-|-', 0, 'Computer Simulation|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq440', '20679335', 'Mathematical models of biological systems often have a large number of parameters whose combinational variations can yield distinct qualitative behaviors. Since it is intractable to examine all possible combinations of parameters for non-trivial biological pathways, it is required to have a systematic strategy to explore the parameter space in a computational way so that dynamic behaviors of a given pathway are estimated.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75646, 2010, 'bio', 'DMDM: domain mapping of disease mutations', 'Peterson, Thomas A|Adadey, Asa|Santana-Cruz, Ivette|Sun, Yanan|Winder, Andrew|Kann, Maricel G', 'Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.|Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA.', 'United States|United States|United States|United States|United States|United States', 41, 'Computational Biology|Databases, Protein|Disease|Humans|Mutation|Polymorphism, Genetic|Protein Structure, Tertiary|Proteins|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btq447', '20685956', 'Domain mapping of disease mutations (DMDM) is a database in which each disease mutation can be displayed by its gene, protein or domain location. DMDM provides a unique domain-level view where all human coding mutations are mapped on the protein domain. To build DMDM, all human proteins were aligned to a database of conserved protein domains using a Hidden Markov Model-based sequence alignment tool (HMMer). The resulting protein-domain alignments were used to provide a domain location for all available human disease mutations and polymorphisms. The number of disease mutations and polymorphisms in each domain position are displayed alongside other relevant functional information (e.g. the binding and catalytic activity of the site and the conservation of that domain location). DMDMs protein domain view highlights molecular relationships among mutations from different diseases that might not be clearly observed with traditional gene-centric visualization tools.'),
(75647, 2010, 'bio', 'SPRINT: side-chain prediction inference toolbox for multistate protein design', 'Fromer, Menachem|Yanover, Chen|Harel, Amir|Shachar, Ori|Weiss, Yair|Linial, Michal', 'School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem, Israel. fromer@cs.huji.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel', 9, 'Algorithms|Amino Acid Sequence|Amino Acids|Models, Statistical|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq445', '20685957', 'SPRINT is a software package that performs computational multistate protein design using state-of-the-art inference on probabilistic graphical models. The input to SPRINT is a list of protein structures, the rotamers modeled for each structure and the pre-calculated rotamer energies. Probabilistic inference is performed using the belief propagation or A* algorithms, and dead-end elimination can be applied as pre-processing. The output can either be a list of amino acid sequences simultaneously compatible with these structures, or probabilistic amino acid profiles compatible with the structures. In addition, higher order (e.g. pairwise) amino acid probabilities can also be predicted. Finally, SPRINT also has a module for protein side-chain prediction and single-state design.'),
(75648, 2010, 'bio', 'Ultra-fast FFT protein docking on graphics processors', 'Ritchie, David W|Venkatraman, Vishwesh', 'INRIA Nancy-Grand Est, LORIA, 615 Rue du Jardin Botanique, 54506 Vandoeuvre-lès-Nancy, France. dave.ritchie@loria.fr|INRIA Nancy-Grand Est, LORIA, 615 Rue du Jardin Botanique, 54506 Vandoeuvre-lès-Nancy, France. dave.ritchie@loria.fr', 'France|France', 229, 'Algorithms|Computational Biology|Computer Graphics|Fourier Analysis|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btq444', '20685958', 'Modelling protein-protein interactions (PPIs) is an increasingly important aspect of structural bioinformatics. However, predicting PPIs using in silico docking techniques is computationally very expensive. Developing very fast protein docking tools will be useful for studying large-scale PPI networks, and could contribute to the rational design of new drugs.'),
(75649, 2010, 'bio', 'A framework for oligonucleotide microarray preprocessing', 'Carvalho, Benilton S|Irizarry, Rafael A', 'Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. benilton.carvalho@cancer.org.uk|Department of Oncology, University of Cambridge, CRUK Cambridge Research Institute, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, UK. benilton.carvalho@cancer.org.uk', 'United Kingdom|United Kingdom', 660, 'Algorithms|Databases, Factual|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq431', '20688976', 'The availability of flexible open source software for the analysis of gene expression raw level data has greatly facilitated the development of widely used preprocessing methods for these technologies. However, the expansion of microarray applications has exposed the limitation of existing tools.'),
(75650, 2010, 'bio', 'Gene function prediction using semantic similarity clustering and enrichment analysis in the malaria parasite Plasmodium falciparum', 'Tedder, Philip M R|Bradford, James R|Needham, Chris J|McConkey, Glenn A|Bulpitt, Andrew J|Westhead, David R', 'Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.|Institute of Molecular and Cellular Biology, University of Leeds, Leeds, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 12, 'Cluster Analysis|Computational Biology|Genome, Protozoan|Genomics|Plasmodium falciparum|Protozoan Proteins', 'Journal Article', '10.1093/bioinformatics/btq450', '20693320', 'Functional genomics data provides a rich source of information that can be used in the annotation of the thousands of genes of unknown function found in most sequenced genomes. However, previous gene function prediction programs are mostly produced for relatively well-annotated organisms that often have a large amount of functional genomics data. Here, we present a novel method for predicting gene function that uses clustering of genes by semantic similarity, a naxc3xafve Bayes classifier and enrichment analysis to predict gene function for a genome that is less well annotated but does has a severe effect on human health, that of the malaria parasite Plasmodium falciparum.'),
(75651, 2010, 'bio', 'Association screening of common and rare genetic variants by penalized regression', 'Zhou, Hua|Sehl, Mary E|Sinsheimer, Janet S|Lange, Kenneth', 'Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. huazhou@ucla.edu|Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. huazhou@ucla.edu|Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. huazhou@ucla.edu|Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. huazhou@ucla.edu', 'United States|United States|United States|United States', 91, 'Breast Neoplasms|Databases, Factual|Female|Genetic Predisposition to Disease|Genetic Variation|Genome-Wide Association Study|Humans|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btq448', '20693321', 'This article extends our recent research on penalized estimation methods in genome-wide association studies to the realm of rare variants.'),
(75652, 2010, 'bio', 'RefProtDom: a protein database with improved domain boundaries and homology relationships', 'Gonzalez, Mileidy W|Pearson, William R', 'Department of Biological Sciences, University of Maryland Baltimore County, Baltimore, MD 21250, USA. miledywgonzalez@gmail.com|Department of Biological Sciences, University of Maryland Baltimore County, Baltimore, MD 21250, USA. miledywgonzalez@gmail.com', 'United States|United States', 3, 'Databases, Protein|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq426', '20693322', 'RefProtDom provides a set of divergent query domains, originally selected from Pfam, and full-length proteins containing their homologous domains, with diverse architectures, for evaluating pair-wise and iterative sequence similarity searches. Pfam homology and domain boundary annotations in the target library were supplemented using local and semi-global searches, PSI-BLAST searches, and SCOP and CATH classifications.'),
(75653, 2010, 'bio', 'MASiVE: Mapping and Analysis of Sirevirus Elements in plant genome sequences', 'Darzentas, N|Bousios, A|Apostolidou, V|Tsaftaris, A S', 'Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr|Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr|Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr|Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr', 'Greece|Greece|Greece|Greece', 9, 'Base Sequence|Computational Biology|Databases, Genetic|Genome, Plant|Genome, Viral|Retroelements|Sequence Analysis, DNA|Software|Zea mays', 'Journal Article', '10.1093/bioinformatics/btq454', '20696734', 'We present MASiVE, an expertly built tool for the large-scale, yet sensitive and highly accurate, discovery, preliminary analysis and insertion age estimation of intact Sirevirus LTR-retrotransposons in plant genomic sequences. Validation was based on the recently available and annotated large maize chromosome one. Results show a considerable improvement in the annotation of Sireviruses, and support our approach as an important addition to the bioinformatics toolbox of plant biologists.'),
(75654, 2010, 'bio', 'The misuse of terms in scientific literature', 'Marabotti, Anna|Facchiano, Angelo', 'Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr|Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr', 'Greece|Greece', 1, 'Databases, Protein|Proteins|Sequence Analysis, Protein|Terminology as Topic', 'Comment', '10.1093/bioinformatics/btq438', '20696735', '-'),
(75655, 2010, 'bio', 'An alignment-free model for comparison of regulatory sequences', 'Koohy, Hashem|Dyer, Nigel P|Reid, John E|Koentges, Georgy|Ott, Sascha', 'MOAC Doctoral Training Centre, Coventry House, University of Warwick, Coventry, CV4 7AL, UK. hashem.koohy@warwick.ac.uk|MOAC Doctoral Training Centre, Coventry House, University of Warwick, Coventry, CV4 7AL, UK. hashem.koohy@warwick.ac.uk|MOAC Doctoral Training Centre, Coventry House, University of Warwick, Coventry, CV4 7AL, UK. hashem.koohy@warwick.ac.uk|MOAC Doctoral Training Centre, Coventry House, University of Warwick, Coventry, CV4 7AL, UK. hashem.koohy@warwick.ac.uk|MOAC Doctoral Training Centre, Coventry House, University of Warwick, Coventry, CV4 7AL, UK. hashem.koohy@warwick.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Algorithms|Base Sequence|Binding Sites|DNA|Databases, Genetic|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq453', '20696736', 'Some recent comparative studies have revealed that regulatory regions can retain function over large evolutionary distances, even though the DNA sequences are divergent and difficult to align. It is also known that such enhancers can drive very similar expression patterns. This poses a challenge for the in silico detection of biologically related sequences, as they can only be discovered using alignment-free methods.'),
(75656, 2010, 'bio', 'RBSDesigner: software for designing synthetic ribosome binding sites that yields a desired level of protein expression', 'Na, Dokyun|Lee, Doheon', 'Department of Bio and Brain Engineering, KAIST, 373-1 335-Gwahangno, Yuseong-gu, Daejeon 305-701, South Korea.|Department of Bio and Brain Engineering, KAIST, 373-1 335-Gwahangno, Yuseong-gu, Daejeon 305-701, South Korea.', '-|-', 84, 'Binding Sites|Codon|Proteins|RNA, Transfer|Ribosomes|Software', 'Journal Article', '10.1093/bioinformatics/btq458', '20702394', 'RBSDesigner predicts the translation efficiency of existing mRNA sequences and designs synthetic ribosome binding sites (RBSs) for a given coding sequence (CDS) to yield a desired level of protein expression. The program implements the mathematical model for translation initiation described in Na et al. (Mathematical modeling of translation initiation for the estimation of its efficiency to computationally design mRNA sequences with a desired expression level in prokaryotes. BMC Syst. Biol., 4, 71). The program additionally incorporates the effect on translation efficiency of the spacer length between a Shine-Dalgarno (SD) sequence and an AUG codon, which is crucial for the incorporation of fMet-tRNA into the ribosome. RBSDesigner provides a graphical user interface (GUI) for the convenient design of synthetic RBSs.'),
(75657, 2010, 'bio', 'BDVal: reproducible large-scale predictive model development and validation in high-throughput datasets', 'Dorff, Kevin C|Chambwe, Nyasha|Srdanovic, Marko|Campagne, Fabien', 'Department of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY, USA.|Department of Physiology and Biophysics, Weill Medical College of Cornell University, New York, NY, USA.', 'United States|United States|United States|United States', 6, 'Algorithms|Computational Biology|DNA Methylation|Databases, Genetic|Models, Biological|Software', 'Journal Article', '10.1093/bioinformatics/btq463', '20702395', 'High-throughput data can be used in conjunction with clinical information to develop predictive models. Automating the process of developing, evaluating and testing such predictive models on different datasets would minimize operator errors and facilitate the comparison of different modeling approaches on the same dataset. Complete automation would also yield unambiguous documentation of the process followed to develop each model. We present the BDVal suite of programs that fully automate the construction of predictive classification models from high-throughput data and generate detailed reports about the model construction process. We have used BDVal to construct models from microarray and proteomics data, as well as from DNA-methylation datasets. The programs are designed for scalability and support the construction of thousands of alternative models from a given dataset and prediction task.'),
(75658, 2010, 'bio', 'Cross-species queries of large gene expression databases', 'Le, Hai-Son|Oltvai, Zoltán N|Bar-Joseph, Ziv', 'Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.|Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.|Machine Learning Department, Carnegie Mellon University, Pittsburgh, PA, USA.', 'United States|United States|United States', 18, 'Animals|Databases, Genetic|Gene Expression Profiling|Genomics|Humans|Oligonucleotide Array Sequence Analysis|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btq451', '20702396', 'Expression databases, including the Gene Expression Omnibus and ArrayExpress, have experienced significant growth over the past decade and now hold hundreds of thousands of arrays from multiple species. Since most drugs are initially tested on model organisms, the ability to compare expression experiments across species may help identify pathways that are activated in a similar way in humans and other organisms. However, while several methods exist for finding co-expressed genes in the same species as a query gene, looking at co-expression of homologs or arbitrary genes in other species is challenging. Unlike sequence, which is static, expression is dynamic and changes between tissues, conditions and time. Thus, to carry out cross-species analysis using these databases, we need methods that can match experiments in one species with experiments in another species.'),
(75659, 2010, 'bio', 'A Bayesian method for 3D macromolecular structure inference using class average images from single particle electron microscopy', 'Jaitly, Navdeep|Brubaker, Marcus A|Rubinstein, John L|Lilien, Ryan H', 'Department of Computer Science, University of Toronto, Toronto, ON, Canada. ndjaitly@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, ON, Canada. ndjaitly@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, ON, Canada. ndjaitly@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, ON, Canada. ndjaitly@cs.toronto.edu', 'Canada|Canada|Canada|Canada', 16, 'Algorithms|Bayes Theorem|Cryoelectron Microscopy|Databases, Factual', 'Journal Article', '10.1093/bioinformatics/btq456', '20702397', 'Electron cryo-microscopy can be used to infer 3D structures of large macromolecules with high resolution, but the large amounts of data captured necessitate the development of appropriate statistical models to describe the data generation process, and to perform structure inference. We present a new method for performing ab initio inference of the 3D structures of macromolecules from single particle electron cryo-microscopy experiments using class average images.'),
(75660, 2010, 'bio', 'NoiseMaker: simulated screens for statistical assessment', 'Kwan, Phoenix|Birmingham, Amanda', 'Thermo Fisher Scientific, 2650 Crescent Drive, Lafayette, CO 80026, USA.|Thermo Fisher Scientific, 2650 Crescent Drive, Lafayette, CO 80026, USA.', 'United States|United States', 3, 'Computer Simulation|Data Interpretation, Statistical|MicroRNAs|RNA Interference|RNA, Small Interfering|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq457', '20702398', 'High-throughput screening (HTS) is a common technique for both drug discovery and basic research, but researchers often struggle with how best to derive hits from HTS data. While a wide range of hit identification techniques exist, little information is available about their sensitivity and specificity, especially in comparison to each other. To address this, we have developed the open-source NoiseMaker software tool for generation of realistically noisy virtual screens. By applying potential hit identification methods to NoiseMaker-simulated data and determining how many of the pre-defined true hits are recovered (as well as how many known non-hits are misidentified as hits), one can draw conclusions about the likely performance of these techniques on real data containing unknown true hits. Such simulations apply to a range of screens, such as those using small molecules, siRNAs, shRNAs, miRNA mimics or inhibitors, or gene over-expression, we demonstrate this utility by using it to explain apparently conflicting reports about the performance of the B score hit identification method.'),
(75661, 2010, 'bio', 'Automated analysis of time-lapse fluorescence microscopy images: from live cell images to intracellular foci', 'Dzyubachyk, Oleh|Essers, Jeroen|van Cappellen, Wiggert A|Baldeyron, Céline|Inagaki, Akiko|Niessen, Wiro J|Meijering, Erik', 'Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.|Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 30, 'Algorithms|Automation|DNA Damage|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Pattern Recognition, Automated|Software|Time-Lapse Imaging', 'Journal Article', '10.1093/bioinformatics/btq434', '20702399', 'Complete, accurate and reproducible analysis of intracellular foci from fluorescence microscopy image sequences of live cells requires full automation of all processing steps involved: cell segmentation and tracking followed by foci segmentation and pattern analysis. Integrated systems for this purpose are lacking.'),
(75662, 2010, 'bio', 'Identifying informative subsets of the Gene Ontology with information bottleneck methods', 'Jin, Bo|Lu, Xinghua', 'Department of Biochemistry and Molecular Biology, Medical University of South Carolina, 174 Ashley Ave, Charleston, SC 29425, USA.|Department of Biochemistry and Molecular Biology, Medical University of South Carolina, 174 Ashley Ave, Charleston, SC 29425, USA.', 'United States|United States', 12, 'Computational Biology|Databases, Genetic|Databases, Protein|Information Storage and Retrieval|Proteins|Semantics|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btq449', '20702400', 'The Gene Ontology (GO) is a controlled vocabulary designed to represent the biological concepts pertaining to gene products. This study investigates the methods for identifying informative subsets of GO terms in an automatic and objective fashion. This task in turn requires addressing the following issues: how to represent the semantic context of GO terms, what metrics are suitable for measuring the semantic differences between terms, how to identify an informative subset that retains as much as possible of the original semantic information of GO.'),
(75663, 2010, 'bio', 'MetDAT: a modular and workflow-based free online pipeline for mass spectrometry data processing, analysis and interpretation', 'Biswas, Ambarish|Mynampati, Kalyan C|Umashankar, Shivshankar|Reuben, Sheela|Parab, Gauri|Rao, Raghuraj|Kannan, Velayutham S|Swarup, Sanjay', 'Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.|Singapore-Delft Water Alliance, National University of Singapore, Singapore 117576.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Database Management Systems|Databases, Factual|Electronic Data Processing|Mass Spectrometry|Metabolomics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btq436', '20702401', 'Analysis of high throughput metabolomics experiments is a resource-intensive process that includes pre-processing, pre-treatment and post-processing at each level of experimental hierarchy. We developed an interactive user-friendly online software called Metabolite Data Analysis Tool (MetDAT) for mass spectrometry data. It offers a pipeline of tools for file handling, data pre-processing, univariate and multivariate statistical analyses, database searching and pathway mapping. Outputs are produced in the form of text and high-quality images in real-time. MetDAT allows users to combine data management and experiment-centric workflows for optimization of metabolomics methods and metabolite analysis.'),
(75664, 2010, 'bio', 'Genevar: a database and Java application for the analysis and visualization of SNP-gene associations in eQTL studies', 'Yang, Tsun-Po|Beazley, Claude|Montgomery, Stephen B|Dimas, Antigone S|Gutierrez-Arcelus, Maria|Stranger, Barbara E|Deloukas, Panos|Dermitzakis, Emmanouil T', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1HH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 251, 'Databases, Factual|Gene Expression Profiling|Genomics|Internet|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq452', '20702402', 'Genevar (GENe Expression VARiation) is a database and Java tool designed to integrate multiple datasets, and provides analysis and visualization of associations between sequence variation and gene expression. Genevar allows researchers to investigate expression quantitative trait loci (eQTL) associations within a gene locus of interest in real time. The database and application can be installed on a standard computer in database mode and, in addition, on a server to share discoveries among affiliations or the broader community over the Internet via web services protocols.'),
(75665, 2010, 'bio', 'QuantProReloaded: quantitative analysis of microspot immunoassays', 'Jöcker, Anika|Sonntag, Johanna|Henjes, Frauke|Götschel, Frank|Tresch, Achim|Beissbarth, Tim|Wiemann, Stefan|Korf, Ulrike', 'Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de|Division of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. a.joecker@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Immunoassay|Protein Array Analysis|Proteome|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq443', '20709689', 'Protein microarrays are well-established as sensitive tools for proteomics. Particularly, the microspot immunoassay (MIA) platform enables a quantitative analysis of (phospho-) proteins in complex solutions (e.g. cell lysates or blood plasma) and with low consumption of samples and reagents. Despite numerous biological and clinical applications of MIAs there is currently no user-friendly open source data analysis software available with versatile options for data analysis and data visualization. Here, we introduce the open source software QuantProReloaded that is specifically designed for the analysis of data from MIA experiments.'),
(75666, 2010, 'bio', 'Text mining meets workflow: linking U-Compare with Taverna', 'Kano, Yoshinobu|Dobson, Paul|Nakanishi, Mio|Tsujii, Junichi|Ananiadou, Sophia', 'Department of Computer Science, The University of Tokyo Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan. kano@is.s.u-tokyo.ac.jp|Department of Computer Science, The University of Tokyo Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan. kano@is.s.u-tokyo.ac.jp|Department of Computer Science, The University of Tokyo Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan. kano@is.s.u-tokyo.ac.jp|Department of Computer Science, The University of Tokyo Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan. kano@is.s.u-tokyo.ac.jp|Department of Computer Science, The University of Tokyo Hongo 7-3-1, Bunkyo-ku, Tokyo, 113-0033 Japan. kano@is.s.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 0, 'Computational Biology|Data Mining|Databases, Factual|User-Computer Interface|Workflow', 'Journal Article', '10.1093/bioinformatics/btq464', '20709690', 'Text mining from the biomedical literature is of increasing importance, yet it is not easy for the bioinformatics community to create and run text mining workflows due to the lack of accessibility and interoperability of the text mining resources. The U-Compare system provides a wide range of bio text mining resources in a highly interoperable workflow environment where workflows can very easily be created, executed, evaluated and visualized without coding. We have linked U-Compare to Taverna, a generic workflow system, to expose text mining functionality to the bioinformatics community.'),
(75667, 2010, 'bio', 'Search and clustering orders of magnitude faster than BLAST', 'Edgar, Robert C', 'Tiburon, CA 94920, USA. robert@drive5.com', 'United States', 9914, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btq461', '20709691', 'Biological sequence data is accumulating rapidly, motivating the development of improved high-throughput methods for sequence classification.'),
(75668, 2010, 'bio', 'A cell-based simulation software for multi-cellular systems', 'Hoehme, Stefan|Drasdo, Dirk', 'Interdisciplinary Centre for Bioinformatics, University of Leipzig, Germany. hoehme@izbi.uni-leipzig.de|Interdisciplinary Centre for Bioinformatics, University of Leipzig, Germany. hoehme@izbi.uni-leipzig.de', 'Germany|Germany', 0, 'Cell Movement|Cells|Computer Simulation|Phenotype|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq437', '20709692', 'CellSys is a modular software tool for efficient off-lattice simulation of growth and organization processes in multi-cellular systems in 2D and 3D. It implements an agent-based model that approximates cells as isotropic, elastic and adhesive objects. Cell migration is modeled by an equation of motion for each cell. The software includes many modules specifically tailored to support the simulation and analysis of virtual tissues including real-time 3D visualization and VRML 2.0 support. All cell and environment parameters can be independently varied which facilitates species specific simulations and allows for detailed analyses of growth dynamics and links between cellular and multi-cellular phenotypes.'),
(75669, 2010, 'bio', 'ChEA: transcription factor regulation inferred from integrating genome-wide ChIP-X experiments', 'Lachmann, Alexander|Xu, Huilei|Krishnan, Jayanth|Berger, Seth I|Mazloom, Amin R|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.|Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.', 'United States|United States|United States|United States|United States|United States', 352, 'Chromatin Immunoprecipitation|Databases, Genetic|Gene Expression Regulation|Genome|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq466', '20709693', 'Experiments such as ChIP-chip, ChIP-seq, ChIP-PET and DamID (the four methods referred herein as ChIP-X) are used to profile the binding of transcription factors to DNA at a genome-wide scale. Such experiments provide hundreds to thousands of potential binding sites for a given transcription factor in proximity to gene coding regions.'),
(75670, 2010, 'bio', 'Exchangeable random variables', 'Good, Phillip', 'Department of Pharmacology and Systems Therapeutics, Systems Biology Center New York (SBCNY), Mount Sinai School of Medicine, One Gustave Levy Place, New York, NY 10029, USA.', 'United States', 1, 'Models, Statistical|Statistics, Nonparametric', 'Comment', '10.1093/bioinformatics/btq297', '20716615', '-'),
(75671, 2010, 'bio', 'Module-based prediction approach for robust inter-study predictions in microarray data', 'Mi, Zhibao|Shen, Kui|Song, Nan|Cheng, Chunrong|Song, Chi|Kaminski, Naftali|Tseng, George C', 'Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.|Cooperative Studies Program, VA Maryland Health Care System, Perry Point, MD 21902, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Cluster Analysis|Computational Biology|Databases, Factual|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq472', '20719761', 'Traditional genomic prediction models based on individual genes suffer from low reproducibility across microarray studies due to the lack of robustness to expression measurement noise and gene missingness when they are matched across platforms. It is common that some of the genes in the prediction model established in a training study cannot be matched to another test study because a different platform is applied. The failure of inter-study predictions has severely hindered the clinical applications of microarray. To overcome the drawbacks of traditional gene-based prediction (GBP) models, we propose a module-based prediction (MBP) strategy via unsupervised gene clustering.'),
(75672, 2010, 'bio', 'A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling', 'Zhou, Weiqiang|Yan, Hong', 'Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. kenandzhou@hotmail.com|Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong. kenandzhou@hotmail.com', 'Hong Kong|Hong Kong', 19, 'Computational Biology|DNA|DNA-Binding Proteins|Databases, Nucleic Acid|Databases, Protein|Models, Molecular|Protein Conformation', 'Journal Article', '10.1093/bioinformatics/btq478', '20733060', 'Protein-DNA interaction has significant importance in many biological processes. However, the underlying principle of the molecular recognition process is still largely unknown. As more high-resolution 3D structures of protein-DNA complex are becoming available, the surface characteristics of the complex become an important research topic.'),
(75673, 2010, 'bio', 'GolgiP: prediction of Golgi-resident proteins in plants', 'Chou, Wen-Chi|Yin, Yanbin|Xu, Ying', 'Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, BioEnergy Science Center, GA, USA.|Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, BioEnergy Science Center, GA, USA.|Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology, and Institute of Bioinformatics, University of Georgia, BioEnergy Science Center, GA, USA.', 'Georgia|Georgia|Georgia', 10, 'Databases, Protein|Golgi Apparatus|Membrane Proteins|Plant Proteins|Protein Structure, Tertiary|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq446', '20733061', 'We present a novel Golgi-prediction server, GolgiP, for computational prediction of both membrane- and non-membrane-associated Golgi-resident proteins in plants. We have employed a support vector machine-based classification method for the prediction of such Golgi proteins, based on three types of information, dipeptide composition, transmembrane domain(s) (TMDs) and functional domain(s) of a protein, where the functional domain information is generated through searching against the Conserved Domains Database, and the TMD information includes the number of TMDs, the length of TMD and the number of TMDs at the N-terminus of a protein. Using GolgiP, we have made genome-scale predictions of Golgi-resident proteins in 18 plant genomes, and have made the preliminary analysis of the predicted data.'),
(75674, 2010, 'bio', 'Annotare--a tool for annotating high-throughput biomedical investigations and resulting data', 'Shankar, Ravi|Parkinson, Helen|Burdett, Tony|Hastings, Emma|Liu, Junmin|Miller, Michael|Srinivasa, Rashmi|White, Joseph|Brazma, Alvis|Sherlock, Gavin|Stoeckert, Christian J|Ball, Catherine A', 'Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu|Department of Biochemistry, Stanford University School of Medicine, Stanford, CA 94305-5307, USA. rshankar@stanford.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Computational Biology|Databases, Factual|Gene Expression Profiling|Molecular Sequence Annotation|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq462', '20733062', 'Computational methods in molecular biology will increasingly depend on standards-based annotations that describe biological experiments in an unambiguous manner. Annotare is a software tool that enables biologists to easily annotate their high-throughput experiments, biomaterials and data in a standards-compliant way that facilitates meaningful search and analysis.'),
(75675, 2010, 'bio', 'OpenStructure: a flexible software framework for computational structural biology', 'Biasini, Marco|Mariani, Valerio|Haas, Jürgen|Scheuber, Stefan|Schenk, Andreas D|Schwede, Torsten|Philippsen, Ansgar', 'Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.|Biozentrum, Universität Basel, Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Computational Biology|Databases, Factual|Software', 'Journal Article', '10.1093/bioinformatics/btq481', '20733063', 'Developers of new methods in computational structural biology are often hampered in their research by incompatible software tools and non-standardized data formats. To address this problem, we have developed OpenStructure as a modular open source platform to provide a powerful, yet flexible general working environment for structural bioinformatics. OpenStructure consists primarily of a set of libraries written in C++ with a cleanly designed application programmer interface. All functionality can be accessed directly in C++ or in a Python layer, meeting both the requirements for high efficiency and ease of use. Powerful selection queries and the notion of entity views to represent these selections greatly facilitate the development and implementation of algorithms on structural data. The modular integration of computational core methods with powerful visualization tools makes OpenStructure an ideal working and development environment. Several applications, such as the latest versions of IPLT and QMean, have been implemented based on OpenStructure-demonstrating its value for the development of next-generation structural biology algorithms.'),
(75676, 2010, 'bio', 'Improving performances of suboptimal greedy iterative biclustering heuristics via localization', 'Erten, Cesim|Sözdinler, Melih', 'Department of Computer Engineering, Kadir Has University, Cibali, Istanbul 34083, Turkey. cesim@khas.edu.tr|Department of Computer Engineering, Kadir Has University, Cibali, Istanbul 34083, Turkey. cesim@khas.edu.tr', 'Turkey|Turkey', 7, 'Algorithms|Cluster Analysis|Computational Biology|Databases, Factual|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btq473', '20733064', 'Biclustering gene expression data is the problem of extracting submatrices of genes and conditions exhibiting significant correlation across both the rows and the columns of a data matrix of expression values. Even the simplest versions of the problem are computationally hard. Most of the proposed solutions therefore employ greedy iterative heuristics that locally optimize a suitably assigned scoring function.'),
(75677, 2010, 'bio', 'DRIMM-Synteny: decomposing genomes into evolutionary conserved segments', 'Pham, Son K|Pevzner, Pavel A', 'Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA. kspham@cs.ucsd.edu|Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA. kspham@cs.ucsd.edu', 'United States|United States', 46, 'Algorithms|Animals|Conserved Sequence|Databases, Genetic|Evolution, Molecular|Genome|Genomics|Humans|Mammals|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/btq465', '20736338', 'The rapidly increasing set of sequenced genomes highlights the importance of identifying the synteny blocks in multiple and/or highly duplicated genomes. Most synteny block reconstruction algorithms use genes shared over all genomes to construct the synteny blocks for multiple genomes. However, the number of genes shared among all genomes quickly decreases with the increase in the number of genomes.'),
(75678, 2010, 'bio', 'Circoletto: visualizing sequence similarity with Circos', 'Darzentas, Nikos', 'Institute of Agrobiotechnology, Centre for Research and Technology Hellas, Thessaloniki 57001, Greece. ndarz@certh.gr', 'Greece', 133, 'Computational Biology|Computer Graphics|Internet|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/btq484', '20736339', 'We present Circoletto, an online visualization tool based on Circos, which provides a fast, aesthetically pleasing and informative overview of sequence similarity search results.'),
(75679, 2010, 'bio', 'Deep and wide digging for binding motifs in ChIP-Seq data', 'Kulakovskiy, I V|Boeva, V A|Favorov, A V|Makeev, V J', 'Research Institute for Genetics and Selection of Industrial Microorganisms, Moscow 117545, Russia. ivan.kulakovskiy@gmail.com|Research Institute for Genetics and Selection of Industrial Microorganisms, Moscow 117545, Russia. ivan.kulakovskiy@gmail.com|Research Institute for Genetics and Selection of Industrial Microorganisms, Moscow 117545, Russia. ivan.kulakovskiy@gmail.com|Research Institute for Genetics and Selection of Industrial Microorganisms, Moscow 117545, Russia. ivan.kulakovskiy@gmail.com', '-|-|-|-', 0, 'Base Sequence|Binding Sites|Chromatin Immunoprecipitation|DNA|Databases, Factual|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq488', '20736340', 'ChIP-Seq data are a new challenge for motif discovery. Such a data typically consists of thousands of DNA segments with base-specific coverage values. We present a new version of our DNA motif discovery software ChIPMunk adapted for ChIP-Seq data. ChIPMunk is an iterative algorithm that combines greedy optimization with bootstrapping and uses coverage profiles as motif positional preferences. ChIPMunk does not require truncation of long DNA segments and it is practical for processing up to tens of thousands of data sequences. Comparison with traditional (MEME) or ChIP-Seq-oriented (HMS) motif discovery tools shows that ChIPMunk identifies the correct motifs with the same or better quality but works dramatically faster.'),
(75680, 2010, 'bio', 'Obtaining better quality final clustering by merging a collection of clusterings', 'Mimaroglu, Selim|Erdil, Ertunc', 'Department of Computer Engineering, Bahcesehir University, Ciragan Caddesi 34353 Besiktas, Istanbul, Turkey. selim.mimaroglu@bahcesehir.edu.tr|Department of Computer Engineering, Bahcesehir University, Ciragan Caddesi 34353 Besiktas, Istanbul, Turkey. selim.mimaroglu@bahcesehir.edu.tr', 'Turkey|Turkey', 10, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Proteins', 'Journal Article', '10.1093/bioinformatics/btq489', '20736341', 'Clustering methods including k-means, SOM, UPGMA, DAA, CLICK, GENECLUSTER, CAST, DHC, PMETIS and KMETIS have been widely used in biological studies for gene expression, protein localization, sequence recognition and more. All these clustering methods have some benefits and drawbacks. We propose a novel graph-based clustering software called COMUSA for combining the benefits of a collection of clusterings into a final clustering having better overall quality.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75681, 2010, 'bio', 'ICPS: an integrative cancer profiler system', 'Zhang, Xin-yu|Shi, Lin|Liu, Yan|Tian, Feng|Zhao, Hai-tao|Miao, Xiao-ping|Huang, Ming-lie|Zhu, Xiao-yan', 'State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn|State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China. zhxy@mail.tsinghua.edu.cn', 'China|China|China|China|China|China|China|China', 2, 'Biomarkers|Databases, Genetic|Gene Expression Profiling|Humans|Internet|Meta-Analysis as Topic|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btq487', '20736342', 'Founded upon the database of 570 public signatures, ICPS is a web-based application to obtain biomarker profiles among 11 common cancers by integrating genomic alterations with transcription signatures on the basis of a previously developed integrative pipeline. ICPS supports both public data and users in-house data, and performs meta-analysis at a cancer subtype level by combining heterogeneous datasets. Finally, ICPS returns the robust gene signature containing potential cancer biomarkers that may be useful to carcinogenesis study and clinical cancer diagnosis.'),
(75682, 2010, 'bio', 'Detecting two-locus associations allowing for interactions in genome-wide association studies', 'Wan, Xiang|Yang, Can|Yang, Qiang|Xue, Hong|Tang, Nelson L S|Yu, Weichuan', 'Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.|Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong, China.', 'China|China|China|China|China|China', 0, 'Computational Biology|Databases, Genetic|Genetic Loci|Genetic Predisposition to Disease|Genome, Human|Genome-Wide Association Study|Humans|Macular Degeneration|Parkinson Disease|Phylogeny|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/btq486', '20736343', 'Genome-wide association studies (GWASs) aim to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single nucleotide polymorphisms (SNPs). Although traditional single-locus statistical tests have identified many genetic determinants of susceptibility, those findings cannot completely explain genetic contributions to complex diseases. Marchini and coauthors demonstrated the importance of testing two-locus associations allowing for interactions through a wide range of simulation studies. However, such a test is computationally demanding as we need to test hundreds of billions of SNP pairs in GWAS. Here, we provide a method to address this computational burden for dichotomous phenotypes.'),
(75683, 2010, 'bio', 'BioRuby: bioinformatics software for the Ruby programming language', 'Goto, Naohisa|Prins, Pjotr|Nakao, Mitsuteru|Bonnal, Raoul|Aerts, Jan|Katayama, Toshiaki', 'Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.|Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.|Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.|Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.|Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.|Department of Genome Informatics, Genome Information Research Center, Research Institute for Microbial Diseases, Osaka University, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Computational Biology|Databases, Factual|MEDLINE|Phylogeny|Programming Languages|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq475', '20739307', 'The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis, it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser.'),
(75684, 2010, 'bio', '2Struc: the secondary structure server', 'Klose, D P|Wallace, B A|Janes, Robert W', 'School of Biological and Chemical Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK.|School of Biological and Chemical Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK.|School of Biological and Chemical Sciences, Queen Mary, University of London, Mile End Road, London E1 4NS, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Crystallography, X-Ray|Hydrogen Bonding|Nuclear Magnetic Resonance, Biomolecular|Protein Folding|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq480', '20739308', 'The defined secondary structure of proteins method is often considered the gold standard for assignment of secondary structure from three-dimensional coordinates. However, there are alternative methods. 2Struc: The Secondary Structure Server has been created as a single point of access for eight different secondary structure assignment methods. It has been designed to enable comparisons between methods for analyzing the secondary structure content for a single protein. It also includes a second functionality, Compare-the-Protein to enable comparisons of the secondary structure features from any one method to be made within a collection of nuclear magnetic resonance models, or between the crystal structures of two different proteins.'),
(75685, 2010, 'bio', 'Structural genomics of histone tail recognition', 'Wang, Minghua|Mok, Man Wai|Harper, Hong|Lee, Wen Hwa|Min, Jinrong|Knapp, Stefan|Oppermann, Udo|Marsden, Brian|Schapira, Matthieu', 'Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.|Structural Genomics Consortium, University of Oxford, Headington, Oxford OX37DQ, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Binding Sites|Databases, Protein|Genomics|Histones|Protein Conformation', 'Journal Article', '10.1093/bioinformatics/btq491', '20739309', 'The structural genomics of histone tail recognition web server is an open access resource that presents within mini articles all publicly available experimental structures of histone tails in complex with human proteins. Each article is composed of interactive 3D slides that dissect the structural mechanism underlying the recognition of specific sequences and histone marks. A concise text html-linked to interactive graphics guides the reader through the main features of the interaction. This resource can be used to analyze and compare binding modes across multiple histone recognition modules, to evaluate the chemical tractability of binding sites involved in epigenetic signaling and design small molecule inhibitors.'),
(75686, 2010, 'bio', 'GASSST: global alignment short sequence search tool', 'Rizk, Guillaume|Lavenier, Dominique', 'Univ-Rennes 1/IRISA, IRISA - Symbiose Campus universitaire de Beaulieu, 35042 Rennes Cedex, France. guillaume.rizk@irisa.fr|Univ-Rennes 1/IRISA, IRISA - Symbiose Campus universitaire de Beaulieu, 35042 Rennes Cedex, France. guillaume.rizk@irisa.fr', 'France|France', 65, 'Algorithms|Base Sequence|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq485', '20739310', 'The rapid development of next-generation sequencing technologies able to produce huge amounts of sequence data is leading to a wide range of new applications. This triggers the need for fast and accurate alignment software. Common techniques often restrict indels in the alignment to improve speed, whereas more flexible aligners are too slow for large-scale applications. Moreover, many current aligners are becoming inefficient as generated reads grow ever larger. Our goal with our new aligner GASSST (Global Alignment Short Sequence Search Tool) is thus 2-fold-achieving high performance with no restrictions on the number of indels with a design that is still effective on long reads.'),
(75687, 2010, 'bio', 'TFInfer: a tool for probabilistic inference of transcription factor activities', 'Asif, H M Shahzad|Rolfe, Matthew D|Green, Jeff|Lawrence, Neil D|Rattray, Magnus|Sanguinetti, Guido', 'School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.|School of Informatics, University of Edinburgh, 10 Crichton Street, Edinburgh EH8 9AB, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computational Biology|Databases, Factual|Escherichia coli|Gene Expression|Models, Statistical|Software|Transcription Factors|Yeasts', 'Journal Article', '10.1093/bioinformatics/btq469', '20739311', 'TFInfer is a novel open access, standalone tool for genome-wide inference of transcription factor activities from gene expression data. Based on an earlier MATLAB version, the software has now been extended in a number of ways. It has been significantly optimised in terms of performance, and it was given novel functionality, by allowing the user to model both time series and data from multiple independent conditions. With a full documentation and intuitive graphical user interface, together with an in-built data base of yeast and Escherichia coli transcription factors, the software does not require any mathematical or computational expertise to be used effectively.'),
(75688, 2010, 'bio', 'METAREP: JCVI metagenomics reports--an open source tool for high-performance comparative metagenomics', 'Goll, Johannes|Rusch, Douglas B|Tanenbaum, David M|Thiagarajan, Mathangi|Li, Kelvin|Methé, Barbara A|Yooseph, Shibu', 'The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.|The J. Craig Venter Institute, Rockville, MD 20850, USA.', 'United States|United States|United States|United States|United States|United States|United States', 71, 'Databases, Factual|Information Storage and Retrieval|Internet|Metagenomics|Software', 'Comparative Study', '10.1093/bioinformatics/btq455', '20798169', 'JCVI Metagenomics Reports (METAREP) is a Web 2.0 application designed to help scientists analyze and compare annotated metagenomics datasets. It utilizes Solr/Lucene, a high-performance scalable search engine, to quickly query large data collections. Furthermore, users can use its SQL-like query syntax to filter and refine datasets. METAREP provides graphical summaries for top taxonomic and functional classifications as well as a GO, NCBI Taxonomy and KEGG Pathway Browser. Users can compare absolute and relative counts of multiple datasets at various functional and taxonomic levels. Advanced comparative features comprise statistical tests as well as multidimensional scaling, heatmap and hierarchical clustering plots. Summaries can be exported as tab-delimited files, publication quality plots in PDF format. A data management layer allows collaborative data analysis and result sharing.'),
(75689, 2010, 'bio', 'RDP3: a flexible and fast computer program for analyzing recombination', 'Martin, Darren P|Lemey, Philippe|Lott, Martin|Moulton, Vincent|Posada, David|Lefeuvre, Pierre', 'Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com|Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com|Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com|Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com|Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com|Computational Biology Group, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Centre for High Performance Computing, Rosebank, Cape Town, South Africa. darrenpatrickmartin@gmail.com', 'South Africa|South Africa|South Africa|South Africa|South Africa|South Africa', 1361, 'Algorithms|Databases, Genetic|Phylogeny|Recombination, Genetic|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq467', '20798170', 'RDP3 is a new version of the RDP program for characterizing recombination events in DNA-sequence alignments. Among other novelties, this version includes four new recombination analysis methods (3SEQ, VISRD, PHYLRO and LDHAT), new tests for recombination hot-spots, a range of matrix methods for visualizing over-all patterns of recombination within datasets and recombination-aware ancestral sequence reconstruction. Complementary to a high degree of analysis flow automation, RDP3 also has a highly interactive and detailed graphical user interface that enables more focused hands-on cross-checking of results with a wide variety of newly implemented phylogenetic tree construction and matrix-based recombination signal visualization methods. The new RDP3 can accommodate large datasets and is capable of analyzing alignments ranging in size from 1000 × 10 kilobase sequences to 20 × 2 megabase sequences within 48 h on a desktop PC.'),
(75690, 2010, 'bio', 'Measuring the physical cohesiveness of proteins using physical interaction enrichment', 'Sama, Iziah Edwin|Huynen, Martijn A', 'Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. i.sama@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands. i.sama@cmbi.ru.nl', 'Netherlands|Netherlands', 14, 'Genomics|Humans|Metapneumovirus|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btq474', '20798171', 'Protein-protein interaction (PPI) networks are a valuable resource for the interpretation of genomics data. However, such networks have interaction enrichment biases for proteins that are often studied. These biases skew quantitative results from comparing PPI networks with genomics data. Here, we introduce an approach named physical interaction enrichment (PIE) to eliminate these biases.'),
(75691, 2010, 'bio', 'A study of the efficiency of pooling in haplotype estimation', 'Kuk, Anthony Y C|Xu, Jinfeng|Yang, Yaning', 'Department of Statistics and Applied Probability, National University of Singapore,117546 Singapore. stakuka@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore,117546 Singapore. stakuka@nus.edu.sg|Department of Statistics and Applied Probability, National University of Singapore,117546 Singapore. stakuka@nus.edu.sg', 'Singapore|Singapore|Singapore', 5, 'Algorithms|Gene Frequency|Genotype|Haplotypes|Likelihood Functions|Linkage Disequilibrium|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btq492', '20801910', 'It has been claimed in the literature that pooling DNA samples is efficient in estimating haplotype frequencies. There is, however, no theoretical justification based on calculation of statistical efficiency. In fact, the limited evidence given so far is based on simulation studies with small numbers of loci. With rapid advance in technology, it is of interest to see if pooling is still efficient when the number of loci increases.'),
(75692, 2010, 'bio', 'miRNAkey: a software for microRNA deep sequencing analysis', 'Ronen, Roy|Gan, Ido|Modai, Shira|Sukacheov, Alona|Dror, Gideon|Halperin, Eran|Shomron, Noam', 'Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.|Department of Cell and Developmental Biology, Sackler Faculty of Medicine, Tel Aviv University, Tel-Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 62, 'Base Sequence|Computational Biology|Databases, Nucleic Acid|Gene Expression Profiling|MicroRNAs|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq493', '20801911', 'MicroRNAs (miRNAs) are short abundant non-coding RNAs critical for many cellular processes. Deep sequencing (next-generation sequencing) technologies are being readily used to receive a more accurate depiction of miRNA expression profiles in living cells. This type of analysis is a key step towards improving our understanding of the complexity and mode of miRNA regulation.'),
(75693, 2010, 'bio', 'Ontology- and graph-based similarity assessment in biological networks', 'Wang, Haiying|Zheng, Huiru|Azuaje, Francisco', 'Computer Science Research Institute, School of Computing and Mathematics, University of Ulster.|Computer Science Research Institute, School of Computing and Mathematics, University of Ulster.|Computer Science Research Institute, School of Computing and Mathematics, University of Ulster.', '-|-|-', 10, 'Algorithms|Biomarkers|Computational Biology|Drug Discovery', 'Journal Article', '10.1093/bioinformatics/btq477', '20801912', 'A standard systems-based approach to biomarker and drug target discovery consists of placing putative biomarkers in the context of a network of biological interactions, followed by different guilt-by-association analyses. The latter is typically done based on network structural features. Here, an alternative analysis approach in which the networks are analyzed on a semantic similarity space is reported. Such information is extracted from ontology-based functional annotations. We present SimTrek, a Cytoscape plugin for ontology-based similarity assessment in biological networks.'),
(75694, 2010, 'bio', 'Simple sequence-based kernels do not predict protein-protein interactions', 'Yu, Jiantao|Guo, Maozu|Needham, Chris J|Huang, Yangchao|Cai, Lu|Westhead, David R', 'School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.|School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China.', 'China|China|China|China|China|China', 72, 'Computational Biology|Databases, Protein|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btq483', '20801913', 'A number of methods have been reported that predict protein-protein interactions (PPIs) with high accuracy using only simple sequence-based features such as amino acid 3mer content. This is surprising, given that many protein interactions have high specificity that depends on detailed atomic recognition between physiochemically complementary surfaces. Are the reported high accuracies realistic?'),
(75695, 2010, 'bio', 'DCGL: an R package for identifying differentially coexpressed genes and links from gene expression microarray data', 'Liu, Bao-Hong|Yu, Hui|Tu, Kang|Li, Chun|Li, Yi-Xue|Li, Yuan-Yuan', 'School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.|School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.|School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.|School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.|School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.|School of Life Science and Technology, Tongji University, Shanghai 200092, P R China.', 'China|China|China|China|China|China', 75, 'Algorithms|Databases, Genetic|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software', 'Journal Article', '10.1093/bioinformatics/btq471', '20801914', 'Gene coexpression analysis was developed to explore gene interconnection at the expression level from a systems perspective, and differential coexpression analysis (DCEA), which examines the change in gene expression correlation between two conditions, was accordingly designed as a complementary technique to traditional differential expression analysis (DEA). Since there is a shortage of DCEA tools, we implemented in an R package DCGL five DCEA methods for identification of differentially coexpressed genes and differentially coexpressed links, including three currently popular methods and two novel algorithms described in a companion paper. DCGL can serve as an easy-to-use tool to facilitate differential coexpression analyses.'),
(75696, 2010, 'bio', 'Preferential use of protein domain pairs as interaction mediators: order and transitivity', 'Itzhaki, Zohar|Akiva, Eyal|Margalit, Hanah', 'Department of Microbiology and Molecular Genetics, The Institute for Medical Research - Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.|Department of Microbiology and Molecular Genetics, The Institute for Medical Research - Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.|Department of Microbiology and Molecular Genetics, The Institute for Medical Research - Israel-Canada, Faculty of Medicine, The Hebrew University of Jerusalem, Jerusalem 91120, Israel.', 'Canada|Canada|Canada', 8, 'Binding Sites|Computational Biology|Databases, Protein|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/btq495', '20802208', 'Many protein-protein interactions (PPIs) are mediated by protein domains. The structural data of multi-domain PPIs reveal the domain pair (or pairs) that mediate a PPI, and implicitly also the domain pairs that are not involved in the interaction. By analyzing such data, preference relations between domain pairs as interaction mediators may be revealed.'),
(75697, 2010, 'bio', 'XMSF: Structure-preserving noise reduction and pre-segmentation in microscope tomography', 'Bilbao-Castro, J R|Sorzano, C O S|García, I|Fernández, J J', 'Department of Computer Architecture and Electronics, University de Almería, Almería, Spain. jrbcast@ace.ual.es|Department of Computer Architecture and Electronics, University de Almería, Almería, Spain. jrbcast@ace.ual.es|Department of Computer Architecture and Electronics, University de Almería, Almería, Spain. jrbcast@ace.ual.es|Department of Computer Architecture and Electronics, University de Almería, Almería, Spain. jrbcast@ace.ual.es', 'Spain|Spain|Spain|Spain', 4, 'Algorithms|Electron Microscope Tomography|Image Processing, Computer-Assisted|Imaging, Three-Dimensional|Sensitivity and Specificity|Software', 'Journal Article', '10.1093/bioinformatics/btq496', '20802209', 'Interpretation of electron tomograms is difficult due to the high noise levels. Thus, denoising techniques are needed to improve the signal-to-noise ratio. XMSF (Microscopy Mean Shift Filtering) is a fast, user-friendly application that succeeds in filtering noise while preserving the structures of interest. It is based on the extension to 3D of a method widely applied in other image processing fields under very different scenarios. XMSF has been tested for a variety of tomograms, showing a great potential to become a state-of-the-art filtering program in electron tomography. Applied iteratively, the algorithm yields pre-segmented volumes facilitating posterior segmentation tasks. Moreover, execution times remain low thanks to parallel computing techniques to exploit current multicore computers.'),
(75698, 2010, 'bio', 'Model-based clustering of microarray expression data via latent Gaussian mixture models', 'McNicholas, Paul D|Murphy, Thomas Brendan', 'Department of Mathematics & Statistics, University of Guelph, Guelph, Ontario, Canada. pmcnicho@uoguelph.ca|Department of Mathematics & Statistics, University of Guelph, Guelph, Ontario, Canada. pmcnicho@uoguelph.ca', 'Canada|Canada', 91, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Normal Distribution|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btq498', '20802251', 'In recent years, work has been carried out on clustering gene expression microarray data. Some approaches are developed from an algorithmic viewpoint whereas others are developed via the application of mixture models. In this article, a family of eight mixture models which utilizes the factor analysis covariance structure is extended to 12 models and applied to gene expression microarray data. This modelling approach builds on previous work by introducing a modified factor analysis covariance structure, leading to a family of 12 mixture models, including parsimonious models. This family of models allows for the modelling of the correlation between gene expression levels even when the number of samples is small. Parameter estimation is carried out using a variant of the expectation-maximization algorithm and model selection is achieved using the Bayesian information criterion. This expanded family of Gaussian mixture models, known as the expanded parsimonious Gaussian mixture model (EPGMM) family, is then applied to two well-known gene expression data sets.'),
(75699, 2010, 'bio', 'A sample storage management system for biobanks', 'Voegele, C|Alteyrac, L|Caboux, E|Smans, M|Lesueur, F|Le Calvez-Kelm, F|Hainaut, P', 'Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr|Genetic Cancer Susceptibility Group, International Agency for Research on Cancer (IARC), Lyon, France. voegele@iarc.fr', 'France|France|France|France|France|France|France', 9, 'Biological Specimen Banks|Computational Biology|Databases, Factual|Humans|Information Storage and Retrieval', 'Journal Article', '10.1093/bioinformatics/btq502', '20807837', 'Establishment of large-scale biobanks of human specimens is essential to conduct molecular pathological or epidemiological studies. This requires automation of procedures for specimen cataloguing and tracking through complex analytical processes. The International Agency for Research on Cancer (IARC) develops a large portfolio of studies broadly aimed at cancer prevention and including cohort, case-control and case-only studies in various parts of the world. This diversity of study designs, structure, annotations and specimen collections is extremely difficult to accommodate into a single sample management system (SMS). Current commercial or academic SMS are often restricted to a few sample types and tailored to a limited number of analytic workflows [Voegele et al. (2007) A laboratory information management system (LIMS) for a high throughput genetic platform aimed at candidate gene mutation screening. Bioinformatics, 23, 2504-2506]. Thus, we developed a system based on a three-tier architecture and relying on an Oracle database and an Oracle Forms web application. Data are imported through forms or csv files, and information retrieval is enabled via multi-criteria queries that can generate different types of reports including tables, Excel files, trees, pictures and graphs. The system is easy to install, flexible, expandable and implemented with a high degree of data security and confidentiality. Both the database and the interface have been modeled to be compatible with and adaptable to almost all types of biobanks.'),
(75700, 2010, 'bio', 'Novel sequence-based method for identifying transcription factor binding sites in prokaryotic genomes', 'Sahota, Gurmukh|Stormo, Gary D', 'Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63108, USA.|Department of Genetics, Washington University School of Medicine, Saint Louis, MO 63108, USA.', 'United States|United States', 0, 'Binding Sites|Computational Biology|Genome|Promoter Regions, Genetic|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq501', '20807838', 'Computational techniques for microbial genomic sequence analysis are becoming increasingly important. With next-generation sequencing technology and the human microbiome project underway, current sequencing capacity is significantly greater than the speed at which organisms of interest can be studied experimentally. Most related computational work has been focused on sequence assembly, gene annotation and metabolic network reconstruction. We have developed a method that will primarily use available sequence data in order to determine prokaryotic transcription factor (TF) binding specificities.'),
(75701, 2010, 'bio', 'CoGAPS: an R/C++ package to identify patterns and biological process activity in transcriptomic data', 'Fertig, Elana J|Ding, Jie|Favorov, Alexander V|Parmigiani, Giovanni|Ochs, Michael F', 'Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu|Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu|Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu|Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu|Department of Oncology and Division of Oncology, Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, School of Medicine, Johns Hopkins University, Baltimore, MD 21205, USA. ejfertig@jhmi.edu', 'United States|United States|United States|United States|United States', 32, 'Computational Biology|Gene Expression|Gene Expression Profiling|Genomics|Markov Chains|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btq503', '20810601', 'Coordinated Gene Activity in Pattern Sets (CoGAPS) provides an integrated package for isolating gene expression driven by a biological process, enhancing inference of biological processes from transcriptomic data. CoGAPS improves on other enrichment measurement methods by combining a Markov chain Monte Carlo (MCMC) matrix factorization algorithm (GAPS) with a threshold-independent statistic inferring activity on gene sets. The software is provided as open source C++ code built on top of JAGS software with an R interface.'),
(75702, 2010, 'bio', 'Click-words: learning to predict document keywords from a user perspective', 'Islamaj Doxc4x9fan, Rezarta|Lu, Zhiyong', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States', 11, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|MEDLINE|PubMed|Semantics', 'Journal Article', '10.1093/bioinformatics/btq459', '20810602', 'Recognizing words that are key to a document is important for ranking relevant scientific documents. Traditionally, important words in a document are either nominated subjectively by authors and indexers or selected objectively by some statistical measures. As an alternative, we propose to use documents words popularity in user queries to identify click-words, a set of prominent words from the users perspective. Although they often overlap, click-words differ significantly from other document keywords.'),
(75703, 2010, 'bio', 'Global modeling of transcriptional responses in interaction networks', 'Lahti, Leo|Knuuttila, Juha E A|Kaski, Samuel', 'Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University School of Science and Technology, Aalto, Finland. leo.lahti@iki.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University School of Science and Technology, Aalto, Finland. leo.lahti@iki.fi|Helsinki Institute for Information Technology HIIT, Department of Information and Computer Science, Aalto University School of Science and Technology, Aalto, Finland. leo.lahti@iki.fi', 'Finland|Finland|Finland', 7, 'Databases, Genetic|Gene Regulatory Networks|Genomics|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq500', '20813878', 'Cell-biological processes are regulated through a complex network of interactions between genes and their products. The processes, their activating conditions and the associated transcriptional responses are often unknown. Organism-wide modeling of network activation can reveal unique and shared mechanisms between tissues, and potentially as yet unknown processes. The same method can also be applied to cell-biological conditions in one or more tissues.'),
(75704, 2010, 'bio', 'Using coalitional games on biological networks to measure centrality and power of genes', 'Moretti, Stefano|Fragnelli, Vito|Patrone, Fioravante|Bonassi, Stefano', 'Université Paris-Dauphine, Lamsade, Paris, France. stefano.moretti@dauphine.fr|Université Paris-Dauphine, Lamsade, Paris, France. stefano.moretti@dauphine.fr|Université Paris-Dauphine, Lamsade, Paris, France. stefano.moretti@dauphine.fr|Université Paris-Dauphine, Lamsade, Paris, France. stefano.moretti@dauphine.fr', 'France|France|France|France', 0, 'Algorithms|Gene Expression|Gene Expression Profiling', 'Journal Article', '10.1093/bioinformatics/btq508', '20817743', 'The interpretation of gene interaction in biological networks generates the need for a meaningful ranking of network elements. Classical centrality analysis ranks network elements according to their importance but may fail to reflect the power of each gene in interaction with the others.'),
(75705, 2010, 'bio', 'Using manifold embedding for assessing and predicting protein interactions from high-throughput experimental data', 'You, Zhu-Hong|Lei, Ying-Ke|Gui, Jie|Huang, De-Shuang|Zhou, Xiaobo', 'Intelligent Computing Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China.|Intelligent Computing Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China.|Intelligent Computing Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China.|Intelligent Computing Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China.|Intelligent Computing Laboratory, Institute of Intelligent Machines, Chinese Academy of Sciences, Hefei, Anhui, China.', 'China|China|China|China|China', 142, 'Algorithms|Databases, Protein|Protein Interaction Mapping|Proteins', 'Journal Article', '10.1093/bioinformatics/btq510', '20817744', 'High-throughput protein interaction data, with ever-increasing volume, are becoming the foundation of many biological discoveries, and thus high-quality protein-protein interaction (PPI) maps are critical for a deeper understanding of cellular processes. However, the unreliability and paucity of current available PPI data are key obstacles to the subsequent quantitative studies. It is therefore highly desirable to develop an approach to deal with these issues from the computational perspective. Most previous works for assessing and predicting protein interactions either need supporting evidences from multiple information resources or are severely impacted by the sparseness of PPI networks.'),
(75706, 2010, 'bio', 'Temporal waves of coherent gene expression during Drosophila embryogenesis', 'Papatsenko, Ilya|Levine, Mike|Papatsenko, Dmitri', 'Department of Molecular and Cell Biology, University of California-Berkeley, CA, USA.|Department of Molecular and Cell Biology, University of California-Berkeley, CA, USA.|Department of Molecular and Cell Biology, University of California-Berkeley, CA, USA.', 'United States|United States|United States', 0, 'Animals|Cell Differentiation|Drosophila|Embryonic Development|Gene Expression Regulation, Developmental|Morphogenesis', 'Journal Article', '10.1093/bioinformatics/btq513', '20819957', 'Animal development depends on localized patterns of gene expression. Whole-genome methods permit the global identification of differential expression patterns. However, most gene-expression-clustering methods focus on the analysis of entire expression profiles, rather than temporal segments or time windows.'),
(75707, 2010, 'bio', 'The mRNA landscape at yeast translation initiation sites', 'Robbins-Pianka, A|Rice, M D|Weir, M P', 'Department of Biology and Department of Mathematics and Computer Science, Wesleyan University, Middletown, CT 06459, USA.|Department of Biology and Department of Mathematics and Computer Science, Wesleyan University, Middletown, CT 06459, USA.|Department of Biology and Department of Mathematics and Computer Science, Wesleyan University, Middletown, CT 06459, USA.', 'United States|United States|United States', 0, 'Algorithms|Computational Biology|Genes, Fungal|Nucleic Acid Conformation|Protein Biosynthesis|RNA, Messenger|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btq509', '20819958', 'Although translation initiation has been well studied, many questions remain in elucidating its mechanisms. An ongoing challenge is to understand how ribosomes choose a translation initiation site (TIS). To gain new insights, we analyzed large sets of TISs with the aim of identifying common characteristics that are potentially of functional importance. Nucleotide sequence context has previously been demonstrated to play an important role in the ribosomes selection of a TIS, and mRNA secondary structure is also emerging as a contributing factor. Here, we analyze mRNA secondary structure using the folding predictions of the RNAfold algorithm. We present a method for analyzing these results using a rank-ordering approach to assess the overall degree of predicted secondary structure in a given region of mRNA. In addition, we used a modified version of the algorithm that makes use of only a subset of the standard versions output to incorporate base-pairing polarity constraints suggested by the ribosome scanning process. These methods were employed to study the TISs of 1735 genes in Saccharomyces cerevisiae. Trends in base composition and base-pairing probabilities suggest that efficient translation initiation and high protein expression are aided by reduced secondary structure upstream and downstream of the TIS. However, the downstream reduction is not observed for sets of TISs with nucleotide sequence contexts unfavorable for translation initiation, consistent with previous suggestions that secondary structure downstream of the ribosome can facilitate TIS recognition.'),
(75708, 2010, 'bio', 'Identification of protein binding surfaces using surface triplet propensities', 'Mehio, Wissam|Kemp, Graham J L|Taylor, Paul|Walkinshaw, Malcolm D', 'Institute of Structural and Molecular Biology, School of Biological Sciences, The University of Edinburgh, Kings Buildings, Mayfield Road, Edinburgh EH9 3JR, UK.|Institute of Structural and Molecular Biology, School of Biological Sciences, The University of Edinburgh, Kings Buildings, Mayfield Road, Edinburgh EH9 3JR, UK.|Institute of Structural and Molecular Biology, School of Biological Sciences, The University of Edinburgh, Kings Buildings, Mayfield Road, Edinburgh EH9 3JR, UK.|Institute of Structural and Molecular Biology, School of Biological Sciences, The University of Edinburgh, Kings Buildings, Mayfield Road, Edinburgh EH9 3JR, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Binding Sites|Crystallography, X-Ray|Databases, Protein|Ligands|Protein Interaction Mapping|Proteins|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btq490', '20819959', 'The ability to reliably predict protein-protein and protein-ligand interactions is important for identifying druggable binding sites and for understanding how proteins communicate. Most currently available algorithms identify cavities on the protein surface as potential ligand recognition sites. The method described here does not explicitly look for cavities but uses small surface patches consisting of triplets of adjacent surface atomic groups that can be touched simultaneously by a probe sphere representing a solvent molecule. A total of 455 different types of triplets can be identified. A training set of 309 protein-ligand protein X-ray structures has been used to generate interface propensities for the triplets, which can be used to predict their involvement in ligand-binding interactions.'),
(75709, 2010, 'bio', 'Automated construction and analysis of the design space for biochemical systems', 'Fasani, Rick A|Savageau, Michael A', 'Department of Biomedical Engineering, University of California, Davis, CA 95616, USA.|Department of Biomedical Engineering, University of California, Davis, CA 95616, USA.', 'United States|United States', 18, 'Automation|Biochemical Phenomena|Computational Biology|Models, Biological|Phenotype|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq479', '20823298', 'Our recent work introduced a generic method to construct the design space of biochemical systems: a representation of the relationships between system parameters, environmental variables and phenotypic behavior. In design space, the qualitatively distinct phenotypes of a biochemical system can be identified, counted, analyzed and compared. Boundaries in design space indicate a transition between phenotypic behaviors and can be used to measure a systems tolerance to large changes in parameters. Moreover, the relative size and arrangement of such phenotypic regions can suggest or confirm global properties of the system.'),
(75710, 2010, 'bio', 'Yves Moreau and Jaap Heringa, on behalf of the ECCB10 organizing and steering committees', 'Moreau, Yves|Heringa, Jaap', 'Department of Biomedical Engineering, University of California, Davis, CA 95616, USA.|Department of Biomedical Engineering, University of California, Davis, CA 95616, USA.', 'United States|United States', 0, 'Computational Biology|Congresses as Topic', 'Editorial', '10.1093/bioinformatics/btq482', '20823300', '-');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75711, 2010, 'bio', 'A fast algorithm for exact sequence search in biological sequences using polyphase decomposition', 'Srikantha, Abhilash|Bopardikar, Ajit S|Kaipa, Kalyan Kumar|Venkataraman, Parthasarathy|Lee, Kyusang|Ahn, TaeJin|Narayanan, Rangavittal', 'Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com|Samsung Advanced Institute of Technology, Bangalore, Karnataka, India. s.abhilash@samsung.com', 'India|India|India|India|India|India|India', 1, 'Algorithms|Base Sequence|Chromosomes, Human, Pair 1|Databases, Genetic|Genomics|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq364', '20823301', 'Exact sequence search allows a user to search for a specific DNA subsequence in a larger DNA sequence or database. It serves as a vital block in many areas such as Pharmacogenetics, Phylogenetics and Personal Genomics. As sequencing of genomic data becomes increasingly affordable, the amount of sequence data that must be processed will also increase exponentially. In this context, fast sequence search algorithms will play an important role in exploiting the information contained in the newly sequenced data. Many existing algorithms do not scale up well for large sequences or databases because of their high-computational costs. This article describes an efficient algorithm for performing fast searches on large DNA sequences. It makes use of hash tables of Q-grams that are constructed after downsampling the database, to enable efficient search and memory use. Time complexity for pattern search is reduced using beam pruning techniques. Theoretical complexity calculations and performance figures are presented to indicate the potential of the proposed algorithm.'),
(75712, 2010, 'bio', 'Characteristics of 454 pyrosequencing data--enabling realistic simulation with flowsim', 'Balzer, Susanne|Malde, Ketil|Lanzén, Anders|Sharma, Animesh|Jonassen, Inge', 'Institute of Marine Research, University of Bergen, Bergen, Norway. susanne.balzer@imr.no|Institute of Marine Research, University of Bergen, Bergen, Norway. susanne.balzer@imr.no|Institute of Marine Research, University of Bergen, Bergen, Norway. susanne.balzer@imr.no|Institute of Marine Research, University of Bergen, Bergen, Norway. susanne.balzer@imr.no|Institute of Marine Research, University of Bergen, Bergen, Norway. susanne.balzer@imr.no', 'Norway|Norway|Norway|Norway|Norway', 0, 'Algorithms|Animals|Base Sequence|Bass|Chromosome Mapping|Computer Simulation|DNA, Bacterial|Electronic Data Processing|Escherichia coli|Genomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq365', '20823302', 'The commercial launch of 454 pyrosequencing in 2005 was a milestone in genome sequencing in terms of performance and cost. Throughout the three available releases, average read lengths have increased to approximately 500 base pairs and are thus approaching read lengths obtained from traditional Sanger sequencing. Study design of sequencing projects would benefit from being able to simulate experiments.'),
(75713, 2010, 'bio', 'Classification of ncRNAs using position and size information in deep sequencing data', 'Erhard, Florian|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, München, Germany.|Institut für Informatik, Ludwig-Maximilians-Universität München, München, Germany.', 'Germany|Germany', 0, 'Algorithms|Base Sequence|Humans|RNA, Untranslated|Sequence Alignment', 'Evaluation Studies', '10.1093/bioinformatics/btq363', '20823303', 'Small non-coding RNAs (ncRNAs) play important roles in various cellular functions in all clades of life. With next-generation sequencing techniques, it has become possible to study ncRNAs in a high-throughput manner and by using specialized algorithms ncRNA classes such as miRNAs can be detected in deep sequencing data. Typically, such methods are targeted to a certain class of ncRNA. Many methods rely on RNA secondary structure prediction, which is not always accurate and not all ncRNA classes are characterized by a common secondary structure. Unbiased classification methods for ncRNAs could be important to improve accuracy and to detect new ncRNA classes in sequencing data.'),
(75714, 2010, 'bio', 'Integrating genome assemblies with MAIA', 'Nijkamp, Jurgen|Winterbach, Wynand|van den Broek, Marcel|Daran, Jean-Marc|Reinders, Marcel|de Ridder, Dick', 'Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl|Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl|Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl|Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl|Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl|Department of Mediamatics, Delft University of Technology, Delft, The Netherlands. j.f.nijkamp@tudelft.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Computer Graphics|Contig Mapping|DNA, Fungal|Genome, Fungal|Genomics|Saccharomyces cerevisiae|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btq366', '20823304', 'De novo assembly of a eukaryotic genome with next-generation sequencing data is still a challenging task. Over the past few years several assemblers have been developed, often suitable for one specific type of sequencing data. The number of known genomes is expanding rapidly, therefore it becomes possible to use multiple reference genomes for assembly projects. We introduce an assembly integrator that makes use of all available data, i.e. multiple de novo assemblies and mappings against multiple related genomes, by optimizing a weighted combination of criteria.'),
(75715, 2010, 'bio', 'Maximum likelihood estimation of locus-specific mutation rates in Y-chromosome short tandem repeats', 'Ravid-Amir, Osnat|Rosset, Saharon', 'Department of Statistics and Operation Research, Tel Aviv, Israel.|Department of Statistics and Operation Research, Tel Aviv, Israel.', 'Israel|Israel', 0, 'Chromosomes, Human, Y|Data Interpretation, Statistical|Haplotypes|Humans|Likelihood Functions|Male|Microsatellite Repeats|Mutation', 'Comparative Study', '10.1093/bioinformatics/btq367', '20823305', 'Y-chromosome short tandem repeats (Y-STRs) are widely used for population studies, forensic purposes and, potentially, the study of disease, therefore knowledge of their mutation rate is valuable. Here we show a novel method for estimation of site-specific Y-STR mutation rates from partial phylogenetic information, via the maximum likelihood framework.'),
(75716, 2010, 'bio', 'Parsimony and likelihood reconstruction of human segmental duplications', 'Kahn, Crystal L|Hristov, Borislav H|Raphael, Benjamin J', 'Department of Computer Science, Brown University, Providence, RI 02912, USA. clkahn@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI 02912, USA. clkahn@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI 02912, USA. clkahn@cs.brown.edu', 'United States|United States|United States', 0, 'Algorithms|Evolution, Molecular|Genome, Human|Humans|Models, Genetic|Models, Statistical|Probability|Segmental Duplications, Genomic', 'Journal Article', '10.1093/bioinformatics/btq368', '20823306', 'Segmental duplications > 1 kb in length with >or= 90% sequence identity between copies comprise nearly 5% of the human genome. They are frequently found in large, contiguous regions known as duplication blocks that can contain mosaic patterns of thousands of segmental duplications. Reconstructing the evolutionary history of these complex genomic regions is a non-trivial, but important task.'),
(75717, 2010, 'bio', 'Discriminatory power of RNA family models', 'Höner zu Siederdissen, Christian|Hofacker, Ivo L', 'Institute for Theoretical Chemistry, University of Vienna, Wien, Austria. choener@tbi.univie.ac.at|Institute for Theoretical Chemistry, University of Vienna, Wien, Austria. choener@tbi.univie.ac.at', 'Austria|Austria', 0, 'Algorithms|Base Sequence|Databases, Genetic|Internet|Models, Genetic|RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq370', '20823307', 'RNA family models group nucleotide sequences that share a common biological function. These models can be used to find new sequences belonging to the same family. To succeed in this task, a model needs to exhibit high sensitivity as well as high specificity. As model construction is guided by a manual process, a number of problems can occur, such as the introduction of more than one model for the same family or poorly constructed models. We explore the Rfam database to discover such problems.'),
(75718, 2010, 'bio', 'RactIP: fast and accurate prediction of RNA-RNA interaction using integer programming', 'Kato, Yuki|Sato, Kengo|Hamada, Michiaki|Watanabe, Yoshihide|Asai, Kiyoshi|Akutsu, Tatsuya', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan. ykato@kuicr.kyoto-u.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan', 3, 'Algorithms|Base Pairing|Base Sequence|Binding Sites|Mathematical Computing|Nucleic Acid Conformation|RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq372', '20823308', 'Considerable attention has been focused on predicting RNA-RNA interaction since it is a key to identifying possible targets of non-coding small RNAs that regulate gene expression post-transcriptionally. A number of computational studies have so far been devoted to predicting joint secondary structures or binding sites under a specific class of interactions. In general, there is a trade-off between range of interaction type and efficiency of a prediction algorithm, and thus efficient computational methods for predicting comprehensive type of interaction are still awaited.'),
(75719, 2010, 'bio', 'Solenoid and non-solenoid protein recognition using stationary wavelet packet transform', 'Vo, An|Nguyen, Nha|Huang, Heng', 'The Feinstein Institute for Medical Research, North Shore LIJ Health System, NY, USA. anphuocnhu.vo@mavs.uta.edu|The Feinstein Institute for Medical Research, North Shore LIJ Health System, NY, USA. anphuocnhu.vo@mavs.uta.edu|The Feinstein Institute for Medical Research, North Shore LIJ Health System, NY, USA. anphuocnhu.vo@mavs.uta.edu', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Codon|Electrochemistry|Fourier Analysis|Protein Structure, Secondary|Proteins|ROC Curve|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq371', '20823309', 'Solenoid proteins are emerging as a protein class with properties intermediate between structured and intrinsically unstructured proteins. Containing repeating structural units, solenoid proteins are expected to share sequence similarities. However, in many cases, the sequence similarities are weak and non-detectable. Moreover, solenoids can be degenerated and widely vary in the number of units. So that it is difficult to detect them. Recently, several solenoid repeats detection methods have been proposed, such as self-alignment of the sequence, spectral analysis and discrete Fourier transform of sequence. Although these methods have shown good performance on certain data sets, they often fail to detect repeats with weak similarities. In this article, we propose a new approach to recognize solenoid repeats and non-solenoid proteins using stationary wavelet packet transform (SWPT). Our method associates with three advantages: (i) naturally representing five main factors of protein structure and properties by wavelet analysis technique, (ii) extracting novel wavelet features that can capture hidden components from solenoid sequence similarities and distinguish them from global proteins, (iii) obtaining statistics features that capture repeating motifs of solenoid proteins.'),
(75720, 2010, 'bio', 'Vorescore--fold recognition improved by rescoring of protein structure models', 'Csaba, Gergely|Zimmer, Ralf', 'Department of Informatics, Ludwig-Maximilians-Universität München, München, Germany. csaba@bio.ifi.lmu.de|Department of Informatics, Ludwig-Maximilians-Universität München, München, Germany. csaba@bio.ifi.lmu.de', 'Germany|Germany', 0, 'Models, Molecular|Models, Structural|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btq369', '20823310', 'The identification of good protein structure models and their appropriate ranking is a crucial problem in structure prediction and fold recognition. For many alignment methods, rescoring of alignment-induced models using structural information can improve the separation of useful and less useful models as compared with the alignment score. Vorescore, a template-based protein structure model rescoring system is introduced. The method scores the model structure against the template used for the modeling using Vorolign. The method works on models from different alignment methods and incorporates both knowledge from the prediction method and the rescoring.'),
(75721, 2010, 'bio', 'A predictor for toxin-like proteins exposes cell modulator candidates within viral genomes', 'Naamati, Guy|Askenazi, Manor|Linial, Michal', 'School of Computer Science and Engineering, Hebrew University of Jerusalem, Israel.|School of Computer Science and Engineering, Hebrew University of Jerusalem, Israel.|School of Computer Science and Engineering, Hebrew University of Jerusalem, Israel.', 'Israel|Israel|Israel', 0, 'Algorithms|Amino Acid Sequence|Animals|Artificial Intelligence|Base Sequence|Conotoxins|Metagenomics|Molecular Sequence Data|Protein Folding|Protein Structure, Tertiary|Proteome|Toxins, Biological|Viral Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btq375', '20823311', 'Animal toxins operate by binding to receptors and ion channels. These proteins are short and vary in sequence, structure and function. Sporadic discoveries have also revealed endogenous toxin-like proteins in non-venomous organisms. Viral proteins are the largest group of quickly evolving proteomes. We tested the hypothesis that toxin-like proteins exist in viruses and that they act to modulate functions of their hosts.'),
(75722, 2010, 'bio', 'Improved sequence-based prediction of disordered regions with multilayer fusion of multiple information sources', 'Mizianty, Marcin J|Stach, Wojciech|Chen, Ke|Kedarisetti, Kanaka Durga|Disfani, Fatemeh Miri|Kurgan, Lukasz', 'Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Amino Acid Sequence|Base Sequence|Databases, Protein|Protein Structure, Secondary|Protein Structure, Tertiary|Proteins|Software', 'Comparative Study', '10.1093/bioinformatics/btq373', '20823312', 'Intrinsically disordered proteins play a crucial role in numerous regulatory processes. Their abundance and ubiquity combined with a relatively low quantity of their annotations motivate research toward the development of computational models that predict disordered regions from protein sequences. Although the prediction quality of these methods continues to rise, novel and improved predictors are urgently needed.'),
(75723, 2010, 'bio', 'Prototypes of elementary functional loops unravel evolutionary connections between protein functions', 'Goncearenco, Alexander|Berezovsky, Igor N', 'Bergen Center for Computational Science and Department of Informatics, University of Bergen, Bergen, Norway.|Bergen Center for Computational Science and Department of Informatics, University of Bergen, Bergen, Norway.', 'Norway|Norway', 0, 'Amino Acid Motifs|Amino Acid Sequence|Archaeal Proteins|Base Sequence|Computational Biology|Evolution, Molecular|Genome, Archaeal|Models, Molecular|Molecular Sequence Data|Protein Folding|Proteome', 'Journal Article', '10.1093/bioinformatics/btq374', '20823313', 'Earlier studies of protein structure revealed closed loops with a characteristic size 25-30 residues and ring-like shape as a basic universal structural element of globular proteins. Elementary functional loops (EFLs) have specific signatures and provide functional residues important for binding/activation and principal chemical transformation steps of the enzymatic reaction. The goal of this work is to show how these functional loops evolved from pre-domain peptides and to find a set of prototypes from which the EFLs of contemporary proteins originated.'),
(75724, 2010, 'bio', 'A varying threshold method for ChIP peak-calling using multiple sources of information', 'Chen, Kuan-Bei|Zhang, Yu', 'Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA.|Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA.', 'United States|United States', 0, 'Algorithms|Animals|Binding Sites|Cell Line|Chromatin Immunoprecipitation|Computer Simulation|DNA|GATA1 Transcription Factor|Mathematical Computing|Mice|Protein Binding', 'Evaluation Studies', '10.1093/bioinformatics/btq379', '20823314', 'Gene regulation commonly involves interaction among DNA, proteins and biochemical conditions. Using chromatin immunoprecipitation (ChIP) technologies, protein-DNA interactions are routinely detected in the genome scale. Computational methods that detect weak protein-binding signals and simultaneously maintain a high specificity yet remain to be challenging. An attractive approach is to incorporate biologically relevant data, such as protein co-occupancy, to improve the power of protein-binding detection. We call the additional data related with the target protein binding as supporting tracks.'),
(75725, 2010, 'bio', 'De-correlating expression in gene-set analysis', 'Nam, Dougu', 'School of Nano-Biotechnology and Chemical Engineering, Ulsan National Institute of Science and Technology, Republic of Korea. dougnam@unist.ac.kr', '-', 0, 'Algorithms|Computer Simulation|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|Genes, p53|Humans|Male|Prostate|Prostatic Neoplasms', 'Evaluation Studies', '10.1093/bioinformatics/btq380', '20823315', 'Group-wise pattern analysis of genes, known as gene-set analysis (GSA), addresses the differential expression pattern of biologically pre-defined gene sets. GSA exhibits high statistical power and has revealed many novel biological processes associated with specific phenotypes. In most cases, however, GSA relies on the invalid assumption that the members of each gene set are sampled independently, which increases false predictions.'),
(75726, 2010, 'bio', 'Discovering graphical Granger causality using the truncating lasso penalty', 'Shojaie, Ali|Michailidis, George', 'Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, USA. shojaie@umich.edu|Department of Statistics, University of Michigan, Ann Arbor, Michigan 48109, USA. shojaie@umich.edu', 'United States|United States', 2, 'Algorithms|Animals|Computer Simulation|Escherichia coli|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|HeLa Cells|Humans|Models, Genetic|Models, Statistical|Regression Analysis', 'Evaluation Studies', '10.1093/bioinformatics/btq377', '20823316', 'Components of biological systems interact with each other in order to carry out vital cell functions. Such information can be used to improve estimation and inference, and to obtain better insights into the underlying cellular mechanisms. Discovering regulatory interactions among genes is therefore an important problem in systems biology. Whole-genome expression data over time provides an opportunity to determine how the expression levels of genes are affected by changes in transcription levels of other genes, and can therefore be used to discover regulatory interactions among genes.'),
(75727, 2010, 'bio', 'is-rSNP: a novel technique for in silico regulatory SNP detection', 'Macintyre, Geoff|Bailey, James|Haviv, Izhak|Kowalczyk, Adam', 'Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia. gmaci@csse.unimelb.edu.au|Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia. gmaci@csse.unimelb.edu.au|Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia. gmaci@csse.unimelb.edu.au|Department of Computer Science and Software Engineering, University of Melbourne, Victoria, Australia. gmaci@csse.unimelb.edu.au', 'Australia|Australia|Australia|Australia', 0, 'Algorithms|Alleles|DNA|Databases, Genetic|Disease|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Position-Specific Scoring Matrices|Regulatory Sequences, Nucleic Acid|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btq378', '20823317', 'Determining the functional impact of non-coding disease-associated single nucleotide polymorphisms (SNPs) identified by genome-wide association studies (GWAS) is challenging. Many of these SNPs are likely to be regulatory SNPs (rSNPs): variations which affect the ability of a transcription factor (TF) to bind to DNA. However, experimental procedures for identifying rSNPs are expensive and labour intensive. Therefore, in silico methods are required for rSNP prediction. By scoring two alleles with a TF position weight matrix (PWM), it can be determined which SNPs are likely rSNPs. However, predictions in this manner are noisy and no method exists that determines the statistical significance of a nucleotide variation on a PWM score.'),
(75728, 2010, 'bio', 'Nonlinear dimension reduction and clustering by Minimum Curvilinearity unfold neuropathic pain and tissue embryological classes', 'Cannistraci, Carlo Vittorio|Ravasi, Timothy|Montevecchi, Franco Maria|Ideker, Trey|Alessio, Massimo', 'Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com|Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com|Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com|Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com|Computational Bioscience Research Center, Division of Chemical and Life Sciences and Engineering, King Abdullah University for Science and Technology (KAUST), Jeddah, Kingdom of Saudi Arabia. kalokagathos.agon@gmail.com', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia', 0, 'Algorithms|Artificial Intelligence|Cell Line|Cluster Analysis|Data Interpretation, Statistical|Embryo, Mammalian|Humans|Pain|Peripheral Nervous System Diseases|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btq376', '20823318', 'Nonlinear small datasets, which are characterized by low numbers of samples and very high numbers of measures, occur frequently in computational biology, and pose problems in their investigation. Unsupervised hybrid-two-phase (H2P) procedures-specifically dimension reduction (DR), coupled with clustering-provide valuable assistance, not only for unsupervised data classification, but also for visualization of the patterns hidden in high-dimensional feature space.'),
(75729, 2010, 'bio', 'BioXSD: the common data-exchange format for everyday bioinformatics web services', 'Kalas, Matxc3xbas|Puntervoll, Pxc3xa5l|Joseph, Alexandre|Bartasevicixc5xabte, Edita|Txc3xb6pfer, Armin|Venkataraman, Prabakar|Pettifer, Steve|Bryne, Jan Christian|Ison, Jon|Blanchet, Christophe|Rapacki, Kristoffer|Jonassen, Inge', 'Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no|Bergen Center for Computational Science, Uni Research, Bergen, Norway. matus.kalas@bccs.uib.no', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway|Norway', 0, 'Amino Acid Sequence|Computational Biology|Information Storage and Retrieval|Internet|Molecular Sequence Data|Programming Languages|Semantics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/btq391', '20823319', 'The world-wide community of life scientists has access to a large number of public bioinformatics databases and tools, which are developed and deployed using diverse technologies and designs. More and more of the resources offer programmatic web-service interface. However, efficient use of the resources is hampered by the lack of widely used, standard data-exchange formats for the basic, everyday bioinformatics data types.'),
(75730, 2010, 'bio', 'Discovering drug-drug interactions: a text-mining and reasoning approach based on properties of drug metabolism', 'Tari, Luis|Anwar, Saadat|Liang, Shanshan|Cai, James|Baral, Chitta', 'Disease and Translational Informatics, Hoffmann-La Roche, Nutley, NJ 07110, USA. luis.tari@roche.com|Disease and Translational Informatics, Hoffmann-La Roche, Nutley, NJ 07110, USA. luis.tari@roche.com|Disease and Translational Informatics, Hoffmann-La Roche, Nutley, NJ 07110, USA. luis.tari@roche.com|Disease and Translational Informatics, Hoffmann-La Roche, Nutley, NJ 07110, USA. luis.tari@roche.com|Disease and Translational Informatics, Hoffmann-La Roche, Nutley, NJ 07110, USA. luis.tari@roche.com', 'United States|United States|United States|United States|United States', 0, 'Data Mining|Databases, Factual|Drug Interactions|Enzymes|Feasibility Studies|Humans|Logic|Natural Language Processing|Pharmaceutical Preparations', 'Evaluation Studies', '10.1093/bioinformatics/btq382', '20823320', 'Identifying drug-drug interactions (DDIs) is a critical process in drug administration and drug development. Clinical support tools often provide comprehensive lists of DDIs, but they usually lack the supporting scientific evidences and different tools can return inconsistent results. In this article, we propose a novel approach that integrates text mining and automated reasoning to derive DDIs. Through the extraction of various facts of drug metabolism, not only the DDIs that are explicitly mentioned in text can be extracted but also the potential interactions that can be inferred by reasoning.'),
(75731, 2010, 'bio', 'Discriminative and informative features for biomolecular text mining with ensemble feature selection', 'Van Landeghem, Sofie|Abeel, Thomas|Saeys, Yvan|Van de Peer, Yves', 'Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 1, 'Algorithms|Artificial Intelligence|Data Mining|Gene Expression|Metabolism|Phosphorylation|Protein Binding|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq381', '20823321', 'In the field of biomolecular text mining, black box behavior of machine learning systems currently limits understanding of the true nature of the predictions. However, feature selection (FS) is capable of identifying the most relevant features in any supervised learning setting, providing insight into the specific properties of the classification algorithm. This allows us to build more accurate classifiers while at the same time bridging the gap between the black box behavior and the end-user who has to interpret the results.'),
(75732, 2010, 'bio', 'Improving disease gene prioritization using the semantic similarity of Gene Ontology terms', 'Schlicker, Andreas|Lengauer, Thomas|Albrecht, Mario', 'Max Planck Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Saarbrücken, Germany.|Max Planck Institute for Informatics, Department of Computational Biology and Applied Algorithmics, Saarbrücken, Germany.', 'Germany|Germany|Germany', 6, 'Animals|Benchmarking|Computational Biology|Databases, Genetic|Genes|Genetic Diseases, Inborn|Humans|Mice|Multifactorial Inheritance|Proteins|Semantics|Software', 'Comparative Study', '10.1093/bioinformatics/btq384', '20823322', 'Many hereditary human diseases are polygenic, resulting from sequence alterations in multiple genes. Genomic linkage and association studies are commonly performed for identifying disease-related genes. Such studies often yield lists of up to several hundred candidate genes, which have to be prioritized and validated further. Recent studies discovered that genes involved in phenotypically similar diseases are often functionally related on the molecular level.'),
(75733, 2010, 'bio', 'Utopia documents: linking scholarly literature with research data', 'Attwood, T K|Kell, D B|McDermott, P|Marsh, J|Pettifer, S R|Thorne, D', 'School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk|School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk|School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk|School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk|School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk|School of Computer Science, Faculty of Life Sciences, University of Manchester, Manchester, UK. teresa.k.attwood@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Information Services|Internet|Literature|Periodicals as Topic|Publications|Publishing|Research|Software', 'Journal Article', '10.1093/bioinformatics/btq383', '20823323', 'In recent years, the gulf between the mass of accumulating-research data and the massive literature describing and analyzing those data has widened. The need for intelligent tools to bridge this gap, to rescue the knowledge being systematically isolated in literature and data silos, is now widely acknowledged.'),
(75734, 2010, 'bio', 'A graphical method for reducing and relating models in systems biology', 'Gay, Steven|Soliman, Sylvain|Fages, François', 'EPI Contraintes, Institut National de Recherche en Informatique et Automatique, INRIA Paris-Rocquencourt, France.|EPI Contraintes, Institut National de Recherche en Informatique et Automatique, INRIA Paris-Rocquencourt, France.|EPI Contraintes, Institut National de Recherche en Informatique et Automatique, INRIA Paris-Rocquencourt, France.', 'France|France|France', 2, 'Algorithms|Calcium|Cell Cycle|Circadian Rhythm|Computer Graphics|Internet|MAP Kinase Signaling System|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq388', '20823324', 'In Systems Biology, an increasing collection of models of various biological processes is currently developed and made available in publicly accessible repositories, such as biomodels.net for instance, through common exchange formats such as SBML. To date, however, there is no general method to relate different models to each other by abstraction or reduction relationships, and this task is left to the modeler for re-using and coupling models. In mathematical biology, model reduction techniques have been studied for a long time, mainly in the case where a model exhibits different time scales, or different spatial phases, which can be analyzed separately. These techniques are however far too restrictive to be applied on a large scale in systems biology, and do not take into account abstractions other than time or phase decompositions. Our purpose here is to propose a general computational method for relating models together, by considering primarily the structure of the interactions and abstracting from their dynamics in a first step.'),
(75735, 2010, 'bio', 'A novel approach for determining environment-specific protein costs: the case of Arabidopsis thaliana', 'Sajitz-Hermstein, Max|Nikoloski, Zoran', 'Max-Planck Institute of Molecular Plant Physiology, University of Postdam, Potsdam, Germany.|Max-Planck Institute of Molecular Plant Physiology, University of Postdam, Potsdam, Germany.', 'Germany|Germany', 0, 'Amino Acids|Arabidopsis|Arabidopsis Proteins|Darkness|Energy Metabolism|Environment|Genome, Plant|Light|Metabolomics|Models, Biological|Proteomics', 'Journal Article', '10.1093/bioinformatics/btq390', '20823325', 'Comprehensive understanding of cellular processes requires development of approaches which consider the energetic balances in the cell. The existing approaches that address this problem are based on defining energy-equivalent costs which do not include the effects of a changing environment. By incorporating these effects, one could provide a framework for integrating omics data from various levels of the system in order to provide interpretations with respect to the energy state and to elicit conclusions about putative global energy-related response mechanisms in the cell.'),
(75736, 2010, 'bio', 'Bayesian experts in exploring reaction kinetics of transcription circuits', 'Yoshida, Ryo|Saito, Masaya M|Nagao, Hiromichi|Higuchi, Tomoyuki', 'The Institute of Statistical Mathematics, Research Organization of Information and Systems, Tokyo, Japan. yoshidar@ism.ac.jp|The Institute of Statistical Mathematics, Research Organization of Information and Systems, Tokyo, Japan. yoshidar@ism.ac.jp|The Institute of Statistical Mathematics, Research Organization of Information and Systems, Tokyo, Japan. yoshidar@ism.ac.jp|The Institute of Statistical Mathematics, Research Organization of Information and Systems, Tokyo, Japan. yoshidar@ism.ac.jp', 'Japan|Japan|Japan|Japan', 0, 'Algorithms|Bayes Theorem|Circadian Rhythm|Computer Simulation|Kinetics|Models, Genetic|Stochastic Processes|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btq389', '20823326', 'Biochemical reactions in cells are made of several types of biological circuits. In current systems biology, making differential equation (DE) models simulatable in silico has been an appealing, general approach to uncover a complex world of biochemical reaction dynamics. Despite of a need for simulation-aided studies, our research field has yet provided no clear answers: how to specify kinetic values in models that are difficult to measure from experimental/theoretical analyses on biochemical kinetics.'),
(75737, 2010, 'bio', 'Dynamic deterministic effects propagation networks: learning signalling pathways from longitudinal protein array data', 'Bender, Christian|Henjes, Frauke|Fröhlich, Holger|Wiemann, Stefan|Korf, Ulrike|Beissbarth, Tim', 'Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, Heidelberg, Germany. c.bender@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 2, 'Algorithms|Breast Neoplasms|Cell Line, Tumor|Computer Simulation|Electronic Data Processing|Female|Humans|Likelihood Functions|Models, Biological|Neoplasm Proteins|Phosphorylation|Protein Array Analysis|Proteins|Proteomics|Signal Transduction|Systems Biology', 'Comparative Study', '10.1093/bioinformatics/btq385', '20823327', 'Network modelling in systems biology has become an important tool to study molecular interactions in cancer research, because understanding the interplay of proteins is necessary for developing novel drugs and therapies. De novo reconstruction of signalling pathways from data allows to unravel interactions between proteins and make qualitative statements on possible aberrations of the cellular regulatory program. We present a new method for reconstructing signalling networks from time course experiments after external perturbation and show an application of the method to data measuring abundance of phosphorylated proteins in a human breast cancer cell line, generated on reverse phase protein arrays.'),
(75738, 2010, 'bio', 'Efficient parameter search for qualitative models of regulatory networks using symbolic model checking', 'Batt, Gregory|Page, Michel|Cantone, Irene|Goessler, Gregor|Monteiro, Pedro|de Jong, Hidde', 'INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr|INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr|INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr|INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr|INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr|INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr', 'France|France|France|France|France|France', 2, 'Benchmarking|Computer Simulation|Electronic Data Processing|Gene Expression Regulation, Fungal|Gene Regulatory Networks|Models, Genetic|Software|Symbolism|Systems Biology|Yeasts', 'Journal Article', '10.1093/bioinformatics/btq387', '20823328', 'Investigating the relation between the structure and behavior of complex biological networks often involves posing the question if the hypothesized structure of a regulatory network is consistent with the observed behavior, or if a proposed structure can generate a desired behavior.'),
(75739, 2010, 'bio', 'How threshold behaviour affects the use of subgraphs for network comparison', 'Rito, Tiago|Wang, Zi|Deane, Charlotte M|Reinert, Gesine', 'Department of Statistics, University of Oxford, Oxford, UK. tiago@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, UK. tiago@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, UK. tiago@stats.ox.ac.uk|Department of Statistics, University of Oxford, Oxford, UK. tiago@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Computer Simulation|Data Interpretation, Statistical|Humans|Models, Biological|Protein Interaction Mapping|Saccharomyces cerevisiae|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btq386', '20823329', 'A wealth of protein-protein interaction (PPI) data has recently become available. These data are organized as PPI networks and an efficient and biologically meaningful method to compare such PPI networks is needed. As a first step, we would like to compare observed networks to established network models, under the aspect of small subgraph counts, as these are conjectured to relate to functional modules in the PPI network. We employ the software tool GraphCrunch with the Graphlet Degree Distribution Agreement (GDDA) score to examine the use of such counts for network comparison.'),
(75740, 2010, 'bio', 'Candidate gene prioritization based on spatially mapped gene expression: an application to XLMR', 'Piro, Rosario M|Molineris, Ivan|Ala, Ugo|Provero, Paolo|Di Cunto, Ferdinando', 'Molecular Biotechnology Center, Biology and Biochemistry, University of Torino, Torino, Italy. rosario.piro@unito.it|Molecular Biotechnology Center, Biology and Biochemistry, University of Torino, Torino, Italy. rosario.piro@unito.it|Molecular Biotechnology Center, Biology and Biochemistry, University of Torino, Torino, Italy. rosario.piro@unito.it|Molecular Biotechnology Center, Biology and Biochemistry, University of Torino, Torino, Italy. rosario.piro@unito.it|Molecular Biotechnology Center, Biology and Biochemistry, University of Torino, Torino, Italy. rosario.piro@unito.it', 'Italy|Italy|Italy|Italy|Italy', 1, 'Animals|Brain|Chromosome Mapping|Chromosomes, Human, X|Gene Expression Profiling|Genome-Wide Association Study|Humans|Mental Retardation, X-Linked|Mice|Phenotype', 'Evaluation Studies', '10.1093/bioinformatics/btq396', '20823330', 'The identification of genes involved in specific phenotypes, such as human hereditary diseases, often requires the time-consuming and expensive examination of a large number of positional candidates selected by genome-wide techniques such as linkage analysis and association studies. Even considering the positive impact of next-generation sequencing technologies, the prioritization of these positional candidates may be an important step for disease-gene identification.'),
(75741, 2010, 'bio', 'Inferring cancer subnetwork markers using density-constrained biclustering', 'Dao, Phuong|Colak, Recep|Salari, Raheleh|Moser, Flavia|Davicioni, Elai|Schönhuth, Alexander|Ester, Martin', 'School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.|School of Computing Science, Simon Fraser University, Burnaby, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 2, 'Algorithms|Benchmarking|Biomarkers, Tumor|Breast Neoplasms|Colonic Neoplasms|Computational Biology|Female|Gene Expression Profiling|Gene Regulatory Networks|Genes, p53|Humans|Neoplasms|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq393', '20823331', 'Recent genomic studies have confirmed that cancer is of utmost phenotypical complexity, varying greatly in terms of subtypes and evolutionary stages. When classifying cancer tissue samples, subnetwork marker approaches have proven to be superior over single gene marker approaches, most importantly in cross-platform evaluation schemes. However, prior subnetwork-based approaches do not explicitly address the great phenotypical complexity of cancer.'),
(75742, 2010, 'bio', 'Modeling associations between genetic markers using Bayesian networks', 'Villanueva, Edwin|Maciel, Carlos Dias', 'Electrical Engineering Department, Sao Carlos School of Engineering, University of Sao Paulo, Sao Carlos, Sao Paulo, Brazil.|Electrical Engineering Department, Sao Carlos School of Engineering, University of Sao Paulo, Sao Carlos, Sao Paulo, Brazil.', 'Brazil|Brazil', 0, 'Algorithms|Bayes Theorem|Chromosome Mapping|Genetic Markers|Haplotypes|Humans|Linkage Disequilibrium|Models, Genetic|Polymorphism, Single Nucleotide', 'Evaluation Studies', '10.1093/bioinformatics/btq392', '20823332', 'Understanding the patterns of association between polymorphisms at different loci in a population (linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure. GMs based in coalescent theory have been the most appealing because they link LD to evolutionary factors. Nevertheless, the inference and parameter estimation of such models is still computationally challenging.'),
(75743, 2010, 'bio', 'Prediction of a gene regulatory network linked to prostate cancer from gene expression, microRNA and clinical data', 'Bonnet, Eric|Michoel, Tom|Van de Peer, Yves', 'Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.|Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium.', 'Belgium|Belgium|Belgium', 2, 'Aged|Algorithms|Cell Line, Tumor|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Male|MicroRNAs|Prostatic Neoplasms|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq395', '20823333', 'Cancer is a complex disease, triggered by mutations in multiple genes and pathways. There is a growing interest in the application of systems biology approaches to analyze various types of cancer-related data to understand the overwhelming complexity of changes induced by the disease.'),
(75744, 2010, 'bio', 'Semi-supervised multi-task learning for predicting interactions between HIV-1 and human proteins', 'Qi, Yanjun|Tastan, Oznur|Carbonell, Jaime G|Klein-Seetharaman, Judith|Weston, Jason', 'NEC Labs America, Princeton, NJ 08540, USA. qyj@cs.cmu.edu|NEC Labs America, Princeton, NJ 08540, USA. qyj@cs.cmu.edu|NEC Labs America, Princeton, NJ 08540, USA. qyj@cs.cmu.edu|NEC Labs America, Princeton, NJ 08540, USA. qyj@cs.cmu.edu|NEC Labs America, Princeton, NJ 08540, USA. qyj@cs.cmu.edu', 'United States|United States|United States|United States|United States', 4, 'Algorithms|Artificial Intelligence|Computational Biology|Data Interpretation, Statistical|HIV-1|Human Immunodeficiency Virus Proteins|Humans|Models, Statistical|Protein Interaction Mapping|Proteins', 'Evaluation Studies', '10.1093/bioinformatics/btq394', '20823334', 'Protein-protein interactions (PPIs) are critical for virtually every biological function. Recently, researchers suggested to use supervised learning for the task of classifying pairs of proteins as interacting or not. However, its performance is largely restricted by the availability of truly interacting proteins (labeled). Meanwhile, there exists a considerable amount of protein pairs where an association appears between two partners, but not enough experimental evidence to support it as a direct interaction (partially labeled).');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75745, 2010, 'bio', 'Detecting host factors involved in virus infection by observing the clustering of infected cells in siRNA screening images', 'Suratanee, Apichat|Rebhan, Ilka|Matula, Petr|Kumar, Anil|Kaderali, Lars|Rohr, Karl|Bartenschlager, Ralf|Eils, Roland|König, Rainer', 'Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.|Department of Bioinformatics and Functional Genomics, University of Heidelberg, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 10, 'Antigens, CD|Biological Factors|Casein Kinase II|Cell Line, Tumor|Data Interpretation, Statistical|Dengue Virus|Hepacivirus|Humans|Image Processing, Computer-Assisted|Minor Histocompatibility Antigens|Phosphotransferases (Alcohol Group Acceptor)|Protein Kinases|RNA Interference|RNA, Small Interfering|Receptors, Cell Surface|Signaling Lymphocytic Activation Molecule Family Member 1|Tetraspanin 28|Vascular Endothelial Growth Factor Receptor-3|Virus Replication', 'Journal Article', '10.1093/bioinformatics/btq398', '20823335', 'Detecting human proteins that are involved in virus entry and replication is facilitated by modern high-throughput RNAi screening technology. However, hit lists from different laboratories have shown only little consistency. This may be caused by not only experimental discrepancies, but also not fully explored possibilities of the data analysis. We wanted to improve reliability of such screens by combining a population analysis of infected cells with an established dye intensity readout.'),
(75746, 2010, 'bio', 'Mass spectrometry data processing using zero-crossing lines in multi-scale of Gaussian derivative wavelet', 'Nguyen, Nha|Huang, Heng|Oraintara, Soontorn|Vo, An', 'Department of Computer Science and Engineering, University of Texas, Arlington, TX, USA.|Department of Computer Science and Engineering, University of Texas, Arlington, TX, USA.|Department of Computer Science and Engineering, University of Texas, Arlington, TX, USA.|Department of Computer Science and Engineering, University of Texas, Arlington, TX, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Normal Distribution|ROC Curve|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Evaluation Studies', '10.1093/bioinformatics/btq397', '20823336', 'Peaks are the key information in mass spectrometry (MS) which has been increasingly used to discover diseases-related proteomic patterns. Peak detection is an essential step for MS-based proteomic data analysis. Recently, several peak detection algorithms have been proposed. However, in these algorithms, there are three major deficiencies: (i) because the noise is often removed, the true signal could also be removed, (ii) baseline removal step may get rid of true peaks and create new false peaks, (iii) in peak quantification step, a threshold of signal-to-noise ratio (SNR) is usually used to remove false peaks, however, noise estimations in SNR calculation are often inaccurate in either time or wavelet domain. In this article, we propose new algorithms to solve these problems. First, we use bivariate shrinkage estimator in stationary wavelet domain to avoid removing true peaks in denoising step. Second, without baseline removal, zero-crossing lines in multi-scale of derivative Gaussian wavelets are investigated with mixture of Gaussian to estimate discriminative parameters of peaks. Third, in quantification step, the frequency, SD, height and rank of peaks are used to detect both high and small energy peaks with robustness to noise.'),
(75747, 2010, 'bio', 'A novel method for similarity analysis and protein sub-cellular localization prediction', 'Liao, Bo|Liao, Benyou|Sun, Xingming|Zeng, Qingguang', 'School of computer and communication, Hunan University, Changsha, Hunan, China. dragonbw@163.com|School of computer and communication, Hunan University, Changsha, Hunan, China. dragonbw@163.com|School of computer and communication, Hunan University, Changsha, Hunan, China. dragonbw@163.com|School of computer and communication, Hunan University, Changsha, Hunan, China. dragonbw@163.com', 'China|China|China|China', 51, 'Algorithms|Databases, Protein|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btq521', '20826879', 'Biological sequence was regarded as an important study by many biologists, because the sequence contains a large number of biological information, what is helpful for scientists studies on biological cells, DNA and proteins. Currently, many researchers used the method based on protein sequences in function classification, sub-cellular location, structure and functional site prediction, including some machine-learning methods. The purpose of this article, is to find a new way of sequence analysis, but more simple and effective.'),
(75748, 2010, 'bio', 'Fixed point characterization of biological networks with complex graph topology', 'Radde, N', 'Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, 70550 Stuttgart, Germany. radde@ist.uni-stuttgart.de', 'Germany', 15, 'Algorithms|Computer Graphics|Metabolic Networks and Pathways|Models, Biological|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq517', '20826880', 'Feedback circuits are important motifs in biological networks and part of virtually all regulation processes that are needed for a reliable functioning of the cell. Mathematically, feedback is connected to complex behavior of the systems, which is often related to bifurcations of fixed points. Therefore, several approaches for the investigation of fixed points in biological networks have been developed in recent years. Many of them assume the fixed point coordinates to be known, and an efficient way to calculate the entire set of fixed points for interrelated feedback structures is highly desirable.'),
(75749, 2010, 'bio', 'Robust and accurate data enrichment statistics via distribution function of sum of weights', 'Stojmirovixc4x87, Aleksandar|Yu, Yi-Kuo', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States', 14, 'Algorithms|Computational Biology|Data Interpretation, Statistical|Databases, Factual|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btq511', '20826881', 'Term-enrichment analysis facilitates biological interpretation by assigning to experimentally/computationally obtained data annotation associated with terms from controlled vocabularies. This process usually involves obtaining statistical significance for each vocabulary term and using the most significant terms to describe a given set of biological entities, often associated with weights. Many existing enrichment methods require selections of (arbitrary number of) the most significant entities and/or do not account for weights of entities. Others either mandate extensive simulations to obtain statistics or assume normal weight distribution. In addition, most methods have difficulty assigning correct statistical significance to terms with few entities.'),
(75750, 2010, 'bio', 'ODES: an overlapping dense sub-graph algorithm', 'Long, James|Hartman, Chris', 'International Arctic Research Center and Department of Computer Science, University of Alaska-Fairbanks, AK 99775, USA. jlong@alaska.edu|International Arctic Research Center and Department of Computer Science, University of Alaska-Fairbanks, AK 99775, USA. jlong@alaska.edu', 'United States|United States', 0, 'Algorithms|Computational Biology|Computer Graphics|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/btq514', '20829442', 'Enumeration of the dense sub-graphs of a graph is of interest in community discovery and membership problems, including dense sub-graphs that overlap each other. Described herein is ODES (Overlapping DEnse Sub-graphs), pthreads parallelized software to extract all overlapping maximal sub-graphs whose densities are greater than or equal to a specified cutoff density of at least 1/2.'),
(75751, 2010, 'bio', 'SBML2TikZ: supporting the SBML render extension in LaTeX', 'Shen, Si Yuan|Bergmann, Frank|Sauro, Herbert M', 'Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.|Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.|Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States', 4, 'Computer Graphics|Databases, Factual|Information Storage and Retrieval|Internet|Models, Biological|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btq512', '20829443', 'The SBML Render Extension enables coloring and shape information of biochemical models to be stored in the Systems Biology Markup Language (SBML). Rendering of this stored graphical information in a portable and well supported system such as TeX would be useful for researchers preparing documentation and presentations. In addition, since the Render Extension is not yet supported by many applications, it is helpful for such rendering functionality be extended to the more popular CellDesigner annotation as well.'),
(75752, 2010, 'bio', 'The Chemical Translation Service--a web-based tool to improve standardization of metabolomic reports', 'Wohlgemuth, Gert|Haldiya, Pradeep Kumar|Willighagen, Egon|Kind, Tobias|Fiehn, Oliver', 'University of California Davis, CA, Genome Center, USA.|University of California Davis, CA, Genome Center, USA.|University of California Davis, CA, Genome Center, USA.|University of California Davis, CA, Genome Center, USA.|University of California Davis, CA, Genome Center, USA.', 'United States|United States|United States|United States|United States', 0, 'Databases, Factual|Internet|Metabolomics|Reference Standards|Software', 'Journal Article', '10.1093/bioinformatics/btq476', '20829444', 'Metabolomic publications and databases use different database identifiers or even trivial names which disable queries across databases or between studies. The best way to annotate metabolites is by chemical structures, encoded by the International Chemical Identifier code (InChI) or InChIKey. We have implemented a web-based Chemical Translation Service that performs batch conversions of the most common compound identifiers, including CAS, CHEBI, compound formulas, Human Metabolome Database HMDB, InChI, InChIKey, IUPAC name, KEGG, LipidMaps, PubChem CID+SID, SMILES and chemical synonym names. Batch conversion downloads of 1410 CIDs are performed in 2.5 min. Structures are automatically displayed.'),
(75753, 2010, 'bio', 'PubDNA Finder: a web database linking full-text articles to sequences of nucleic acids', 'García-Remesal, Miguel|Cuevas, Alejandro|Pérez-Rey, David|Martín, Luis|Anguita, Alberto|de la Iglesia, Diana|de la Calle, Guillermo|Crespo, José|Maojo, Víctor', 'Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es|Departamento de Inteligencia Artificial, Facultad de Informática, Universidad Politécnica de Madrid, Campus de Montegacedo S/N, Boadilla del Monte, Madrid, Spain. mgarcia@infomed.dia.fi.upm.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 9, 'Base Sequence|Computational Biology|Databases, Genetic|Internet|Nucleic Acids|PubMed|Software', 'Journal Article', '10.1093/bioinformatics/btq520', '20829445', 'PubDNA Finder is an online repository that we have created to link PubMed Central manuscripts to the sequences of nucleic acids appearing in them. It extends the search capabilities provided by PubMed Central by enabling researchers to perform advanced searches involving sequences of nucleic acids. This includes, among other features (i) searching for papers mentioning one or more specific sequences of nucleic acids and (ii) retrieving the genetic sequences appearing in different articles. These additional query capabilities are provided by a searchable index that we created by using the full text of the 176 672 papers available at PubMed Central at the time of writing and the sequences of nucleic acids appearing in them. To automatically extract the genetic sequences occurring in each paper, we used an original method we have developed. The database is updated monthly by automatically connecting to the PubMed Central FTP site to retrieve and index new manuscripts. Users can query the database via the web interface provided.'),
(75754, 2010, 'bio', 'Reptile: representative tiling for short read error correction', 'Yang, Xiao|Dorman, Karin S|Aluru, Srinivas', 'Department of Electrical and Computer Engineering, Iowa State University, Ames IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames IA 50011, USA.', 'United States|United States|United States', 109, 'Algorithms|Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq468', '20834037', 'Error correction is critical to the success of next-generation sequencing applications, such as resequencing and de novo genome sequencing. It is especially important for high-throughput short-read sequencing, where reads are much shorter and more abundant, and errors more frequent than in traditional Sanger sequencing. Processing massive numbers of short reads with existing error correction methods is both compute and memory intensive, yet the results are far from satisfactory when applied to real datasets.'),
(75755, 2010, 'bio', 'Semi-supervised recursively partitioned mixture models for identifying cancer subtypes', 'Koestler, Devin C|Marsit, Carmen J|Christensen, Brock C|Karagas, Margaret R|Bueno, Raphael|Sugarbaker, David J|Kelsey, Karl T|Houseman, E Andres', 'Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu|Department of Community Health, Section for Biostatistics, Center for Environmental Health and Technology, Brown University, Providence, RI 02912, USA. devin_koestler@brown.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Cluster Analysis|Databases, Factual|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq470', '20834038', 'Patients with identical cancer diagnoses often progress differently. The disparity we see in disease progression and treatment response can be attributed to the idea that two histologically similar cancers may be completely different diseases on the molecular level. Methods for identifying cancer subtypes associated with patient survival have the capacity to be powerful instruments for understanding the biochemical processes that underlie disease progression as well as providing an initial step toward more personalized therapy for cancer patients. We propose a method called semi-supervised recursively partitioned mixture models (SS-RPMM) that utilizes array-based genetic and patient-level clinical data for finding cancer subtypes that are associated with patient survival.'),
(75756, 2010, 'bio', 'A unified index of sequence quality and contig overlap for DNA barcoding', 'Little, Damon P', 'Cullman Program for Molecular Systematics, The New York Botanical Garden, Bronx, NY, USA. dlittle@nybg.org', 'United States', 13, 'Base Sequence|Computational Biology|DNA|Databases, Factual|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btq507', '20837570', 'Barcode quality index (B) is a novel, unified measure of sequence quality and contig overlap tailored to the needs of DNA barcoding. Re-analysis of published data demonstrates the utility of B.'),
(75757, 2010, 'bio', 'SynBioWave--a real-time communication platform for molecular and synthetic biology', 'Staab, Paul R|Walossek, Jörg|Nellessen, David|Grünberg, Raik|Arndt, Katja M|Müller, Kristian M', 'Department of Mathematics, University of Freiburg.|Department of Mathematics, University of Freiburg.|Department of Mathematics, University of Freiburg.|Department of Mathematics, University of Freiburg.|Department of Mathematics, University of Freiburg.|Department of Mathematics, University of Freiburg.', '-|-|-|-|-|-', 0, 'Computational Biology|Databases, Genetic|Genome|Software|Synthetic Biology', 'Journal Article', '10.1093/bioinformatics/btq518', '20841324', 'Synthetic Biology is advanced by many users and relies on the assembly of genetic elements to devices, systems and finally genomes. SynBioWave is a software suite that enables multiple distributed users to analyze and construct genetic parts in real-time collaboration. It builds on Google Wave and provides an extensible robot-robot-user communication framework, a menu driven user interface, biological data handling including DAS and an internal database communication. We demonstrate its use by implementing robots for gene-data retrieval, manipulation and display. The initial development of SynBioWave demonstrates the power of the underlying Google Wave protocol for Synthetic Biology and lays the foundation for continuous and user-friendly extensions. Specialized wave-robots with a manageable set of capabilities will divide and conquer the complex task of creating a genome in silico.'),
(75758, 2010, 'bio', 'Sequencing delivers diminishing returns for homology detection: implications for mapping the protein universe', 'Chubb, Daniel|Jefferys, Benjamin R|Sternberg, Michael J E|Kelley, Lawrence A', 'Department of Life Science, Imperial College London, London, UK. daniel.chubb01@imperial.ac.uk|Department of Life Science, Imperial College London, London, UK. daniel.chubb01@imperial.ac.uk|Department of Life Science, Imperial College London, London, UK. daniel.chubb01@imperial.ac.uk|Department of Life Science, Imperial College London, London, UK. daniel.chubb01@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Databases, Protein|Genome|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btq527', '20843957', 'Databases of sequenced genomes are widely used to characterize the structure, function and evolutionary relationships of proteins. The ability to discern such relationships is widely expected to grow as sequencing projects provide novel information, bridging gaps in our map of the protein universe.'),
(75759, 2010, 'bio', 'PedMerge: merging pedigrees to facilitate family-based genetic statistical analyses', 'Plaetke, Rosemarie|Balbi, Federico', 'Department of Anthropology, and Center for Alaska Native Health Research, University of Alaska, Fairbanks, AK 99775, USA. rplaetke@alaska.edu|Department of Anthropology, and Center for Alaska Native Health Research, University of Alaska, Fairbanks, AK 99775, USA. rplaetke@alaska.edu', 'United States|United States', 0, 'Algorithms|Animals|Dogs|Family|Humans|Models, Statistical|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/btq523', '20843958', 'PedMerge allows users to accurately and efficiently merge separately ascertained pedigrees that belong to the same extended family. In addition to validation checks of pedigree structure, the software provides files in LINKAGE or PEDSYS format that easily allow to be used by a variety of genetic statistical software packages including LINKAGE, SOLAR, SLINK or can be further manipulated with Mega2.'),
(75760, 2010, 'bio', 'Characterizing molecular adaptation: a hierarchical approach to assess the selective influence of amino acid properties', 'Datta, Saheli|Prado, Raquel|Rodrxc3xadguez, Abel|Escalante, Ananxc3xadas A', 'Department of Applied Mathematics and Statistics, University of California Santa Cruz, CA, USA.|Department of Applied Mathematics and Statistics, University of California Santa Cruz, CA, USA.|Department of Applied Mathematics and Statistics, University of California Santa Cruz, CA, USA.|Department of Applied Mathematics and Statistics, University of California Santa Cruz, CA, USA.', 'United States|United States|United States|United States', 0, 'Alleles|Amino Acids|Bayes Theorem|Codon|Computational Biology|Databases, Genetic|Evolution, Molecular|Humans|Major Histocompatibility Complex', 'Journal Article', '10.1093/bioinformatics/btq532', '20847216', 'A number of methods for detecting positive selection in protein coding DNA sequences are based on whether each site/region has a non-synonymous to synonymous substitution rates ratio xcfx89 greater than one. However, a site/region may show a relatively large number of non-synonymous mutations that conserve a particular property. Recent methods have proposed to consider as evidence for molecular adaptations how conserving, or radically different, non-synonymous mutations are with respect to some key amino acid properties. While such methods have been useful in providing a qualitative assessment of molecular adaptation, they rely on independent statistical analyses for each amino acid property and typically do not properly adjust for multiple comparisons when selection needs to be assessed at several sites.'),
(75761, 2010, 'bio', 'Spatial quantification and classification of skin response following perturbation using organotypic skin cultures', 'Pommerencke, Thora|Westphal, Kathi|Ernst, Claudia|Safferling, Kai|Dickhaus, Hartmut|Steinberg, Thorsten|Tomakidi, Pascal|Grabe, Niels', 'Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, Institute for Medical Biometry and Informatics, University Hospital, University Heidelberg, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 3, 'Algorithms|Biomarkers|Cell Differentiation|Cells, Cultured|Computational Biology|Gene Expression|Intracellular Signaling Peptides and Proteins|Protein-Serine-Threonine Kinases|Skin|Sodium Dodecyl Sulfate', 'Journal Article', '10.1093/bioinformatics/btq525', '20847217', 'For a mechanistic understanding of skin and its response to an induced perturbation, systems biology is gaining increasing attention. Unfortunately, quantitative and spatial expression data for skin, like for most other tissues, are almost not available.'),
(75762, 2010, 'bio', 'Ruffus: a lightweight Python library for computational pipelines', 'Goodstadt, Leo', 'Medical Research Council Functional Genomics Unit, Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK. ruffus@llew.org.uk', 'United Kingdom', 0, 'Computational Biology|Databases, Factual|Internet|Software', 'Journal Article', '10.1093/bioinformatics/btq524', '20847218', 'Computational pipelines are common place in scientific research. However, most of the resources for constructing pipelines are heavyweight systems with graphical user interfaces. Ruffus is a library for the creation of computational pipelines. Its lightweight and unobtrusive design recommends it for use even for the most trivial of analyses. At the same time, it is powerful enough to have been used for complex workflows involving more than 50 interdependent stages.'),
(75763, 2010, 'bio', 'Combined prediction of Tat and Sec signal peptides with hidden Markov models', 'Bagos, Pantelis G|Nikolaou, Elisanthi P|Liakopoulos, Theodore D|Tsirigos, Konstantinos D', 'Department of Computer Science and Biomedical Informatics, University of Central Greece, Papasiopoulou 2-4, Lamia 35100, Greece. pbagos@ucg.gr|Department of Computer Science and Biomedical Informatics, University of Central Greece, Papasiopoulou 2-4, Lamia 35100, Greece. pbagos@ucg.gr|Department of Computer Science and Biomedical Informatics, University of Central Greece, Papasiopoulou 2-4, Lamia 35100, Greece. pbagos@ucg.gr|Department of Computer Science and Biomedical Informatics, University of Central Greece, Papasiopoulou 2-4, Lamia 35100, Greece. pbagos@ucg.gr', 'Greece|Greece|Greece|Greece', 140, 'Computational Biology|Databases, Protein|Markov Chains|Membrane Transport Proteins|Protein Folding|Protein Sorting Signals|Secretory Pathway', 'Journal Article', '10.1093/bioinformatics/btq530', '20847219', 'Computational prediction of signal peptides is of great importance in computational biology. In addition to the general secretory pathway (Sec), Bacteria, Archaea and chloroplasts possess another major pathway that utilizes the Twin-Arginine translocase (Tat), which recognizes longer and less hydrophobic signal peptides carrying a distinctive pattern of two consecutive Arginines (RR) in the n-region. A major functional differentiation between the Sec and Tat export pathways lies in the fact that the former translocates secreted proteins unfolded through a protein-conducting channel, whereas the latter translocates completely folded proteins using an unknown mechanism. The purpose of this work is to develop a novel method for predicting and discriminating Sec from Tat signal peptides at better accuracy.'),
(75764, 2010, 'bio', 'Evidence mining and novelty assessment of protein-protein interactions with the ConsensusPathDB plugin for Cytoscape', 'Pentchev, Konstantin|Ono, Keiichiro|Herwig, Ralf|Ideker, Trey|Kamburov, Atanas', 'Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, Germany.|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, Germany.|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, Germany.|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, Germany.|Department of Vertebrate Genomics, Max Planck Institute for Molecular Genetics, Ihnestrasse 63-73, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany', 20, 'Data Mining|Protein Interaction Mapping|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq522', '20847220', 'Protein-protein interaction detection methods are applied on a daily basis by molecular biologists worldwide. After generating a set of potential interactions, biologists face the problem of highlighting the ones that are novel and collecting evidence with respect to literature and annotation. This task can be as tedious as searching for every predicted interaction in several interaction data repositories, or manually screening the scientific literature. To facilitate the task of evidence mining and novelty assessment of protein-protein interactions, we have developed a Cytoscape plugin that automatically mines publication references, database references, interaction detection method descriptions and pathway annotation for a user-supplied network of interactions. The basis for the annotation is ConsensusPathDB-a meta-database that integrates numerous protein-protein, signaling, metabolic and gene regulatory interaction repositories for currently three species: Homo sapiens, Saccharomyces cerevisiae and Mus musculus.'),
(75765, 2010, 'bio', 'The binding site distance test score: a robust method for the assessment of predicted protein binding sites', 'Roche, Daniel B|Tetchner, Stuart J|McGuffin, Liam J', 'School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK.|School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK.|School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Binding Sites|Computational Biology|Databases, Protein|Protein Conformation|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btq543', '20861025', 'We propose a novel method for scoring the accuracy of protein binding site predictions-the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community-wide prediction experiment-CASP8. While being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of non-binding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores while also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.'),
(75766, 2010, 'bio', 'Selenoprofiles: profile-based scanning of eukaryotic genome sequences for selenoprotein genes', 'Mariotti, M|Guigó, R', 'Bioinformatics and genomics group, Center for Genomic Regulation and Universitat Pompeu Fabra, Barcelona, Catalonia, Spain. marco.mariotti@crg.es|Bioinformatics and genomics group, Center for Genomic Regulation and Universitat Pompeu Fabra, Barcelona, Catalonia, Spain. marco.mariotti@crg.es', 'Spain|Spain', 30, 'Codon, Terminator|Databases, Genetic|Genome|Regulatory Sequences, Nucleic Acid|Selenocysteine|Selenoproteins|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btq516', '20861026', 'Selenoproteins are a group of proteins that contain selenocysteine (Sec), a rare amino acid inserted co-translationally into the protein chain. The Sec codon is UGA, which is normally a stop codon. In selenoproteins, UGA is recoded to Sec in presence of specific features on selenoprotein gene transcripts. Due to the dual role of the UGA codon, selenoprotein prediction and annotation are difficult tasks, and even known selenoproteins are often misannotated in genome databases.'),
(75767, 2010, 'bio', 'SeqEM: an adaptive genotype-calling approach for next-generation sequencing studies', 'Martin, E R|Kinnamon, D D|Schmidt, M A|Powell, E H|Zuchner, S|Morris, R W', 'John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu|John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu|John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu|John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu|John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu|John P. Hussman Institute for Human Genomics and the Dr. John T. Macdonald Foundation Department of Human Genetics, Miller School of Medicine, University of Miami, Miami, Florida, USA. emartin1@med.miami.edu', 'United States|United States|United States|United States|United States|United States', 51, 'Algorithms|Databases, Genetic|Genomics|Genotype|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq526', '20861027', 'Next-generation sequencing presents several statistical challenges, with one of the most fundamental being determining an individuals genotype from multiple aligned short read sequences at a position. Some simple approaches for genotype calling apply fixed filters, such as calling a heterozygote if more than a specified percentage of the reads have variant nucleotide calls. Other genotype-calling methods, such as MAQ and SOAPsnp, are implementations of Bayes classifiers in that they classify genotypes using posterior genotype probabilities.'),
(75768, 2010, 'bio', 'BUCKy: gene tree/species tree reconciliation with Bayesian concordance analysis', 'Larget, Bret R|Kotha, Satish K|Dewey, Colin N|Anxc3xa9, Cxc3xa9cile', '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', 246, 'Bayes Theorem|Computational Biology|Genes|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq539', '20861028', 'BUCKy is a C++ program that implements Bayesian concordance analysis. The method uses a non-parametric clustering of genes with compatible trees, and reconstructs the primary concordance tree from clades supported by the largest proportions of genes. A population tree with branch lengths in coalescent units is estimated from quartet concordance factors.'),
(75769, 2010, 'bio', 'FastPval: a fast and memory efficient program to calculate very low P-values from empirical distribution', 'Li, Mulin Jun|Sham, Pak Chung|Wang, Junwen', 'Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Rd, Pokfulam, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Rd, Pokfulam, Hong Kong SAR, China.|Department of Biochemistry, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Rd, Pokfulam, Hong Kong SAR, China.', 'China|China|China', 0, 'Computational Biology|Databases, Factual|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/btq540', '20861029', 'Resampling methods, such as permutation and bootstrap, have been widely used to generate an empirical distribution for assessing the statistical significance of a measurement. However, to obtain a very low P-value, a large size of resampling is required, where computing speed, memory and storage consumption become bottlenecks, and sometimes become impossible, even on a computer cluster.'),
(75770, 2010, 'bio', 'Girafe--an R/Bioconductor package for functional exploration of aligned next-generation sequencing reads', 'Toedling, Joern|Ciaudo, Constance|Voinnet, Olivier|Heard, Edith|Barillot, Emmanuel', 'Institut Curie, 26 rue dUlm, F-75248 Paris, INSERM U900, F-75248 Paris, France. joern.toedling@curie.fr|Institut Curie, 26 rue dUlm, F-75248 Paris, INSERM U900, F-75248 Paris, France. joern.toedling@curie.fr|Institut Curie, 26 rue dUlm, F-75248 Paris, INSERM U900, F-75248 Paris, France. joern.toedling@curie.fr|Institut Curie, 26 rue dUlm, F-75248 Paris, INSERM U900, F-75248 Paris, France. joern.toedling@curie.fr|Institut Curie, 26 rue dUlm, F-75248 Paris, INSERM U900, F-75248 Paris, France. joern.toedling@curie.fr', 'France|France|France|France|France', 0, 'Databases, Genetic|Genome|Genomics|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq531', '20861030', 'The R/Bioconductor package girafe facilitates the functional exploration of alignments of sequence reads from next-generation sequencing data to a genome. It allows users to investigate the genomic intervals together with the aligned reads and to work with, visualise and export these intervals. Moreover, the package operates within and extends the ever-growing Bioconductor framework and thus enables users to leverage a multitude of methods for their data in order to answer specific research questions.'),
(75771, 2010, 'bio', 'MOBI: a web server to define and visualize structural mobility in NMR protein ensembles', 'Martin, Alberto J M|Walsh, Ian|Tosatto, Silvio C E', 'Department of Biology, University of Padova, viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padova, viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padova, viale G. Colombo 3, 35131 Padova, Italy.', 'Italy|Italy|Italy', 0, 'Crystallography, X-Ray|Databases, Protein|Internet|Models, Molecular|Nuclear Magnetic Resonance, Biomolecular|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq537', '20861031', 'MOBI is a web server for the identification of structurally mobile regions in NMR protein ensembles. It provides a binary mobility definition that is analogous to the commonly used definition of intrinsic disorder in X-ray crystallographic structures. At least three different use cases can be envisaged: (i) visualization of NMR mobility for structural analysis, (ii) definition of regions for reliable comparative modelling in protein structure prediction and (iii) definition of mobility in analogy to intrinsic disorder. MOBI uses structural superposition and local conformational differences to derive a robust binary mobility definition that is in excellent agreement with the manually curated definition used in the CASP8 experiment for intrinsic disorder in NMR structure. The output includes mobility-coloured PDB files, mobility plots and a FASTA formatted sequence file summarizing the mobility results.'),
(75772, 2010, 'bio', 'DisGeNET: a Cytoscape plugin to visualize, integrate, search and analyze gene-disease networks', 'Bauer-Mehren, Anna|Rautschka, Michael|Sanz, Ferran|Furlong, Laura I', 'Research Programme on Biomedical Informatics (GRIB) IMIM, DCEXS, Universitat Pompeu Fabra, C/Dr. Aiguader 88, 08003 Barcelona, Spain.|Research Programme on Biomedical Informatics (GRIB) IMIM, DCEXS, Universitat Pompeu Fabra, C/Dr. Aiguader 88, 08003 Barcelona, Spain.|Research Programme on Biomedical Informatics (GRIB) IMIM, DCEXS, Universitat Pompeu Fabra, C/Dr. Aiguader 88, 08003 Barcelona, Spain.|Research Programme on Biomedical Informatics (GRIB) IMIM, DCEXS, Universitat Pompeu Fabra, C/Dr. Aiguader 88, 08003 Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Computational Biology|Databases, Genetic|Disease|Gene Regulatory Networks|Humans|Software', 'Journal Article', '10.1093/bioinformatics/btq538', '20861032', 'DisGeNET is a plugin for Cytoscape to query and analyze human gene-disease networks. DisGeNET allows user-friendly access to a new gene-disease database that we have developed by integrating data from several public sources. DisGeNET permits queries restricted to (i) the original data source, (ii) the association type, (iii) the disease class or (iv) specific gene(s)/disease(s). It represents gene-disease associations in terms of bipartite graphs and provides gene centric and disease centric views of the data. It assists the user in the interpretation and exploration of the genetic basis of human diseases by a variety of built-in functions. Moreover, DisGeNET permits multicolouring of nodes (genes/diseases) according to standard disease classification for expedient visualization.'),
(75773, 2010, 'bio', 'SpotXplore: a Cytoscape plugin for visual exploration of hotspot expression in gene regulatory networks', 'Westenberg, Michel A|Roerdink, Jos B T M|Kuipers, Oscar P|van Hijum, Sacha A F T', 'Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. m.a.westenberg@tue.nl|Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. m.a.westenberg@tue.nl|Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. m.a.westenberg@tue.nl|Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands. m.a.westenberg@tue.nl', 'Netherlands|Netherlands|Netherlands|Netherlands', 7, 'Computational Biology|Databases, Genetic|Gene Regulatory Networks|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq535', '20861033', 'SpotXplore is a plugin for Cytoscape for extraction and visualization of differentially expressed subnetworks (hotspots) from gene networks. The hotspot-based visualization approach enables interactive exploration of regulatory interactions in differentially expressed gene sets, and it allows a researcher to explore gene expression in direct relation to the affected cellular gene network. The hotspots provide a view beyond the commonly used metabolic pathways and gene ontologies.'),
(75774, 2010, 'bio', 'Metric learning for enzyme active-site search', 'Kato, Tsuyoshi|Nagano, Nozomi', 'GSFS, University of Tokyo, 5-1-5 Kashiwahoha, Kashiwa, Chiba, Japan. kato-tsuyoshi@k.u-tokyo.ac.jp|GSFS, University of Tokyo, 5-1-5 Kashiwahoha, Kashiwa, Chiba, Japan. kato-tsuyoshi@k.u-tokyo.ac.jp', 'Japan|Japan', 0, 'Algorithms|Catalytic Domain|Databases, Protein|Enzymes', 'Journal Article', '10.1093/bioinformatics/btq519', '20870642', 'Finding functionally analogous enzymes based on the local structures of active sites is an important problem. Conventional methods use templates of local structures to search for analogous sites, but their performance depends on the selection of atoms for inclusion in the templates.'),
(75775, 2010, 'bio', 'Statistical considerations for digital approaches to non-invasive fetal genotyping', 'Chu, Tianjiao|Bunce, Kimberly|Hogge, W Allen|Peters, David G', 'Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA.|Department of Obstetrics, Gynecology and Reproductive Sciences, University of Pittsburgh, Pittsburgh, PA, USA.', 'United States|United States|United States|United States', 0, 'Aneuploidy|DNA|Fetus|Genetic Diseases, Inborn|Genotype|Humans|Models, Statistical|Polymerase Chain Reaction|Prenatal Diagnosis', 'Journal Article', '10.1093/bioinformatics/btq544', '20870643', 'A growing body of literature has demonstrated the potential for non-invasive diagnosis of a variety of human genetic diseases using cell-free DNA extracted from maternal plasma samples in early gestation. Such methods are of great significance to the obstetrics community because of their potential use as clinical standard of care. Proof of concept for such approaches has been established for aneuploidy and paternally inherited dominant traits. Although significant progress has recently been made, the non-invasive diagnosis of monogenic diseases that segregate in a recessive mendelian fashion is more problematic. Recent developments in microfluidic digital PCR and DNA sequencing have resulted in a number of recent advances in this field. These have largely, although not exclusively, been used for the development of diagnostic methods for aneuploidy. However, given their prevalence, it is likely that such methods will be utilized towards the development of non-invasive methods for diagnosing monogenetic disorders.'),
(75776, 2010, 'bio', 'PAR: a PARallel and distributed job crusher', 'Berenger, Francois|Coti, Camille|Zhang, Kam Y J', 'Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. berenger@riken.jp|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. berenger@riken.jp|Zhang Initiative Research Unit, Advanced Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan. berenger@riken.jp', 'Japan|Japan|Japan', 0, 'Computational Biology|Software', 'Journal Article', '10.1093/bioinformatics/btq542', '20870644', 'Bioinformaticians are tackling increasingly computation-intensive tasks. In the meantime, workstations are shifting towards multi-core architectures and even massively multi-core may be the norm soon. Bag-of-Tasks (BoT) applications are commonly encountered in bioinformatics. They consist of a large number of independent computation-intensive tasks. This note introduces PAR, a scalable, dynamic, parallel and distributed execution engine for Bag-of-Tasks. PAR is aimed at multi-core architectures and small clusters. Accelerations obtained thanks to PAR on two different applications are shown.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(75777, 2010, 'bio', 'Identification of context-dependent motifs by contrasting ChIP binding data', 'Mason, Mike J|Plath, Kathrin|Zhou, Qing', 'Department of Statistics, University of California, Los Angeles, CA 90095, USA.|Department of Statistics, University of California, Los Angeles, CA 90095, USA.|Department of Statistics, University of California, Los Angeles, CA 90095, USA.', 'United States|United States|United States', 33, 'Algorithms|Animals|Binding Sites|Chromatin Immunoprecipitation|Computational Biology|DNA-Binding Proteins|Genome|Mice|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq546', '20870645', 'DNA binding proteins play crucial roles in the regulation of gene expression. Transcription factors (TFs) activate or repress genes directly while other proteins influence chromatin structure for transcription. Binding sites of a TF exhibit a similar sequence pattern called a motif. However, a one-to-one map does not exist between each TF and motif. Many TFs in a protein family may recognize the same motif with subtle nucleotide differences leading to different binding affinities. Additionally, a particular TF may bind different motifs under certain conditions, for example in the presence of different co-regulators. The availability of genome-wide binding data of multiple collaborative TFs makes it possible to detect such context-dependent motifs.'),
(75778, 2010, 'bio', 'SimiCon: a web tool for protein-ligand model comparison through calculation of equivalent atomic contacts', 'Rueda, Manuel|Katritch, Vsevolod|Raush, Eugene|Abagyan, Ruben', 'UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA 92093, USA.|UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA 92093, USA.|UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA 92093, USA.|UCSD Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California-San Diego, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States', 7, 'Computer Graphics|Databases, Protein|Internet|Ligands|Protein Conformation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btq504', '20871105', 'SimiCon is a web server designed for an automated identification of equivalent protein-ligand atomic contacts in different conformational models of a complex. The contacts are computed with internal coordinate mechanics (ICM) software with respect to molecular symmetry and the results are shown in the browser as text, tables and interactive 3D graphics. The web server can be executed remotely without a browser to allow users to automate multiple calculations.'),
(75779, 2010, 'bio', 'A Gibbs sampling strategy applied to the mapping of ambiguous short-sequence tags', 'Wang, Jianrong|Huda, Ahsan|Lunyak, Victoria V|Jordan, I King', 'School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.|School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.|School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.|School of Biology, Georgia Institute of Technology, Atlanta, GA 30332, USA.', 'Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Base Sequence|Chromatin Immunoprecipitation|Computational Biology|DNA Transposable Elements|Genome|Sequence Analysis, DNA|Sequence Tagged Sites', 'Journal Article', '10.1093/bioinformatics/btq460', '20871106', 'Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is widely used in biological research. ChIP-seq experiments yield many ambiguous tags that can be mapped with equal probability to multiple genomic sites. Such ambiguous tags are typically eliminated from consideration resulting in a potential loss of important biological information.'),
(75780, 2010, 'bio', 'RAPID detection of gene-gene interactions in genome-wide association studies', 'Brinza, Dumitru|Schultz, Matthew|Tesler, Glenn|Bafna, Vineet', 'Life Technologies, Foster City, CA, USA.|Life Technologies, Foster City, CA, USA.|Life Technologies, Foster City, CA, USA.|Life Technologies, Foster City, CA, USA.', 'United States|United States|United States|United States', 23, 'Databases, Genetic|Gene Expression|Genome-Wide Association Study|Genomics|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btq529', '20871107', 'In complex disorders, independently evolving locus pairs might interact to confer disease susceptibility, with only a modest effect at each locus. With genome-wide association studies on large cohorts, testing all pairs for interaction confers a heavy computational burden, and a loss of power due to large Bonferroni-like corrections. Correspondingly, limiting the tests to pairs that show marginal effect at either locus, also has reduced power. Here, we describe an algorithm that discovers interacting locus pairs without explicitly testing all pairs, or requiring a marginal effect at each locus. The central idea is a mathematical transformation that maps statistical correlation between locus pairs to distance between two points in a Euclidean space. This enables the use of geometric properties to identify proximal points (correlated locus pairs), without testing each pair explicitly. For large datasets (xe2x88xbc 10(6) SNPs), this reduces the number of tests from 10(12) to 10(6), significantly reducing the computational burden, without loss of power. The speed of the test allows for correction using permutation-based tests. The algorithm is encoded in a tool called RAPID (RApid Pair IDentification) for identifying paired interactions in case-control GWAS.'),
(75781, 2010, 'bio', 'SylArray: a web server for automated detection of miRNA effects from expression data', 'Bartonicek, Nenad|Enright, Anton J', 'EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom', 31, '3 Untranslated Regions|Computational Biology|Databases, Genetic|Genome|Genomics|MicroRNAs|RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq545', '20871108', 'A useful step for understanding the function of microRNAs (miRNA) or siRNAs is the detection of their effects on genome-wide expression profiles. Typically, approaches look for enrichment of words in the 3()UTR sequences of the most deregulated genes. A number of tools are available for this purpose, but they require either in-depth computational knowledge, filtered 3()UTR sequences for the genome of interest, or a set of genes acquired through an arbitrary expression cutoff. To this end, we have developed SylArray, a web-based resource designed for the analysis of large-scale expression datasets. It simply requires the user to submit a sorted list of genes from an expression experiment. SylArray utilizes curated sets of 3()UTRs to attach sequences to these genes and then applies the Sylamer algorithm for detection of miRNA or siRNA signatures in those sequences. An intuitive system for visualization and interpretation of the small RNA signatures is included.'),
(75782, 2010, 'bio', 'HybridNET: a tool for constructing hybridization networks', 'Chen, Zhi-Zhong|Wang, Lusheng', 'Department of Mathematical Sciences, Tokyo Denki University, Ishizaka, Hatoyama, Hiki, Saitama 359-0394, Japan. zzchen@mail.dendai.ac.jp|Department of Mathematical Sciences, Tokyo Denki University, Ishizaka, Hatoyama, Hiki, Saitama 359-0394, Japan. zzchen@mail.dendai.ac.jp', 'Japan|Japan', 0, 'Computational Biology|Evolution, Molecular|Genome|Hybridization, Genetic|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq548', '20871109', 'When reticulation events occur, the evolutionary history of a set of existing species can be represented by a hybridization network instead of an evolutionary tree. When studying the evolutionary history of a set of existing species, one can obtain a phylogenetic tree of the set of species with high confidence by looking at a segment of sequences or a set of genes. When looking at another segment of sequences, a different phylogenetic tree can be obtained with high confidence too. This indicates that reticulation events may occur. Thus, we have the following problem: given two rooted phylogenetic trees on a set of species that correctly represent the tree-like evolution of different parts of their genomes, what is the hybridization network with the smallest number of reticulation events to explain the evolution of the set of species under consideration?'),
(75783, 2010, 'bio', 'GLOOME: gain loss mapping engine', 'Cohen, Ofir|Ashkenazy, Haim|Belinky, Frida|Huchon, Dorothée|Pupko, Tal', 'Department of Cell Research and Immunology, Tel-Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, Tel-Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, Tel-Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, Tel-Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, Tel-Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel', 47, 'Computational Biology|Evolution, Molecular|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btq549', '20876605', 'The evolutionary analysis of presence and absence profiles (phyletic patterns) is widely used in biology. It is assumed that the observed phyletic pattern is the result of gain and loss dynamics along a phylogenetic tree. Examples of characters that are represented by phyletic patterns include restriction sites, gene families, introns and indels, to name a few. Here, we present a user-friendly web server that accurately infers branch-specific and site-specific gain and loss events. The novel inference methodology is based on a stochastic mapping approach utilizing models that reliably capture the underlying evolutionary processes. A variety of features are available including the ability to analyze the data with various evolutionary models, to infer gain and loss events using either stochastic mapping or maximum parsimony, and to estimate gain and loss rates for each character analyzed.'),
(75784, 2010, 'bio', 'SLOPE: a quick and accurate method for locating non-SNP structural variation from targeted next-generation sequence data', 'Abel, Haley J|Duncavage, Eric J|Becker, Nils|Armstrong, Jon R|Magrini, Vincent J|Pfeifer, John D', 'Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu|Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu|Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu|Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu|Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu|Department of Internal Medicine, Division of Genetic Epidemiology, Department of Pathology, University of Utah, Salt Lake City, UT, USA. haley@genepi.med.utah.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Genome|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software|Translocation, Genetic', 'Journal Article', '10.1093/bioinformatics/btq528', '20876606', 'Targeted deep sequencing of specific genes or regions is of great interest in clinical cancer diagnostics where some sequence variants, particularly translocations and indels, have known prognostic or diagnostic significance. In this setting, it is unnecessary to sequence an entire genome, and target capture methods can be applied to limit sequencing to important regions, thereby reducing costs and the time required to complete testing. Existing next-gen sequencing analysis packages are optimized for efficiency in whole-genome studies and are unable to benefit from the particular structure of targeted sequence data.'),
(75785, 2010, 'bio', 'Spial: analysis of subtype-specific features in multiple sequence alignments of proteins', 'Wuster, Arthur|Venkatakrishnan, A J|Schertler, Gebhard F X|Babu, M Madan', 'Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge CB2 1TP, UK.|Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge CB2 1TP, UK.|Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge CB2 1TP, UK.|Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge CB2 1TP, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Evolution, Molecular|Genomics|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq552', '20880955', 'Spial (Specificity in alignments) is a tool for the comparative analysis of two alignments of evolutionarily related sequences that differ in their function, such as two receptor subtypes. It highlights functionally important residues that are either specific to one of the two alignments or conserved across both alignments. It permits visualization of this information in three complementary ways: by colour-coding alignment positions, by sequence logos and optionally by colour-coding the residues of a protein structure provided by the user. This can aid in the detection of residues that are involved in the subtype-specific interaction with a ligand, other proteins or nucleic acids. Spial may also be used to detect residues that may be post-translationally modified in one of the two sets of sequences.'),
(75786, 2010, 'bio', 'A statistical framework for Illumina DNA methylation arrays', 'Kuan, Pei Fen|Wang, Sijian|Zhou, Xin|Chu, Haitao', 'Department of Biostatistics, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA. pfkuan@bios.unc.edu|Department of Biostatistics, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA. pfkuan@bios.unc.edu|Department of Biostatistics, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA. pfkuan@bios.unc.edu|Department of Biostatistics, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA. pfkuan@bios.unc.edu', 'United States|United States|United States|United States', 68, 'DNA Methylation|Data Interpretation, Statistical|Databases, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btq553', '20880956', 'The Illumina BeadArray is a popular platform for profiling DNA methylation, an important epigenetic event associated with gene silencing and chromosomal instability. However, current approaches rely on an arbitrary detection P-value cutoff for excluding probes and samples from subsequent analysis as a quality control step, which results in missing observations and information loss. It is desirable to have an approach that incorporates the whole data, but accounts for the different quality of individual observations.'),
(75787, 2010, 'bio', 'A simple and fast method to determine the parameters for fuzzy c-means cluster analysis', 'Schwämmle, Veit|Jensen, Ole Nørregaard', 'Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark. veits@bmb.sdu.dk|Department of Biochemistry and Molecular Biology, University of Southern Denmark, Campusvej 55, DK-5230 Odense M, Denmark. veits@bmb.sdu.dk', 'Denmark|Denmark', 0, 'Cluster Analysis|Fuzzy Logic|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteomics', 'Journal Article', '10.1093/bioinformatics/btq534', '20880957', 'Fuzzy c-means clustering is widely used to identify cluster structures in high-dimensional datasets, such as those obtained in DNA microarray and quantitative proteomics experiments. One of its main limitations is the lack of a computationally fast method to set optimal values of algorithm parameters. Wrong parameter values may either lead to the inclusion of purely random fluctuations in the results or ignore potentially important data. The optimal solution has parameter values for which the clustering does not yield any results for a purely random dataset but which detects cluster formation with maximum resolution on the edge of randomness.'),
(75788, 2010, 'bio', 'Interrogating local population structure for fine mapping in genome-wide association studies', 'Qin, Huaizhen|Morris, Nathan|Kang, Sun J|Li, Mingyao|Tayo, Bamidele|Lyon, Helen|Hirschhorn, Joel|Cooper, Richard S|Zhu, Xiaofeng', 'Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.|Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Chromosome Mapping|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Population Groups|Principal Component Analysis|Selection, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btq560', '20889494', 'Adjustment for population structure is necessary to avoid bias in genetic association studies of susceptibility variants for complex diseases. Population structure may differ from one genomic region to another due to the variability of individual ancestry associated with migration, random genetic drift or natural selection. Current association methods for correcting population stratification usually involve adjustment of global ancestry between study subjects.'),
(75789, 2010, 'bio', 'Network-based comparison of temporal gene expression patterns', 'Huang, Wei|Cao, Xiaoyi|Zhong, Sheng', 'Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.|Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, IL, USA.', 'United States|United States|United States', 7, 'Cell Differentiation|Cluster Analysis|Computational Biology|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|RNA Interference|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btq561', '20889495', 'In the pursuits of mechanistic understanding of cell differentiation, it is often necessary to compare multiple differentiation processes triggered by different external stimuli and internal perturbations. Available methods for comparing temporal gene expression patterns are limited to a gene-by-gene approach, which ignores co-expression information and thus is sensitive to measurement noise.'),
(75790, 2010, 'bio', 'Chembench: a cheminformatics workbench', 'Walker, Theo|Grulke, Christopher M|Pozefsky, Diane|Tropsha, Alexander', 'Division of Medicinal Chemistry and Natural Products, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Division of Medicinal Chemistry and Natural Products, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Division of Medicinal Chemistry and Natural Products, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Division of Medicinal Chemistry and Natural Products, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.', 'United States|United States|United States|United States', 0, 'Computational Biology|Drug Discovery|Quantitative Structure-Activity Relationship|Small Molecule Libraries|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btq556', '20889496', 'Advances in the field of cheminformatics have been hindered by a lack of freely available tools. We have created Chembench, a publicly available cheminformatics portal for analyzing experimental chemical structure-activity data. Chembench provides a broad range of tools for data visualization and embeds a rigorous workflow for creating and validating predictive Quantitative Structure-Activity Relationship models and using them for virtual screening of chemical libraries to prioritize the compound selection for drug discovery and/or chemical safety assessment.'),
(75791, 2010, 'bio', 'CopyMap: localization and calling of copy number variation by joint analysis of hybridization data from multiple individuals', 'Zöllner, Sebastian', 'Department of Biostatistics, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109, USA. szoellne@umich.edu', 'United States', 0, 'Comparative Genomic Hybridization|Databases, Genetic|Gene Dosage|Genetic Variation|Genome, Human|Humans|Markov Chains|Nucleic Acid Hybridization|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq515', '20926418', 'The program package CopyMap identifies copy number variation from oligo-hybridization and CGH data. Using a time-dependent hidden Markov model to combine evidence of copy number variants (CNVs) across multiple carriers, CopyMap is substantially more accurate than standard hidden Markov methods in identifying CNVs and calling CNV-carriers. Moreover, CopyMap provides more precise estimates of CNV-boundaries.'),
(75792, 2010, 'bio', 'GeneMANIA Cytoscape plugin: fast gene function predictions on the desktop', 'Montojo, J|Zuberi, K|Rodriguez, H|Kazi, F|Wright, G|Donaldson, S L|Morris, Q|Bader, G D', 'Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.|Banting and Best Department of Medical Research, The Donnelly Centre, University of Toronto, 160 College Street, Toronto, ON, M5S 3E1, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 312, 'Algorithms|Computational Biology|Databases, Factual|Gene Regulatory Networks|Genes|Software', 'Journal Article', '10.1093/bioinformatics/btq562', '20926419', 'The GeneMANIA Cytoscape plugin brings fast gene function prediction capabilities to the desktop. GeneMANIA identifies the most related genes to a query gene set using a guilt-by-association approach. The plugin uses over 800 networks from six organisms and each related gene is traceable to the source network used to make the prediction. Users may add their own interaction networks and expression profile data to complement or override the default data.'),
(75793, 2010, 'bio', 'ALCHEMY: a reliable method for automated SNP genotype calling for small batch sizes and highly homozygous populations', 'Wright, Mark H|Tung, Chih-Wei|Zhao, Keyan|Reynolds, Andy|McCouch, Susan R|Bustamante, Carlos D', 'Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu|Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu|Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu|Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu|Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu|Department of Biological Statistics and Computational Biology, 102 Weill Hall, Cornell University, Ithaca, NY 14853, USA. mhw6@cornell.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Genotype|Homozygote|Models, Statistical|Oligonucleotide Array Sequence Analysis|Oryza|Polymorphism, Single Nucleotide|Software', 'Evaluation Studies', '10.1093/bioinformatics/btq533', '20926420', 'The development of new high-throughput genotyping products requires a significant investment in testing and training samples to evaluate and optimize the product before it can be used reliably on new samples. One reason for this is current methods for automated calling of genotypes are based on clustering approaches which require a large number of samples to be analyzed simultaneously, or an extensive training dataset to seed clusters. In systems where inbred samples are of primary interest, current clustering approaches perform poorly due to the inability to clearly identify a heterozygote cluster.'),
(75794, 2010, 'bio', 'MEDELLER: homology-based coordinate generation for membrane proteins', 'Kelm, Sebastian|Shi, Jiye|Deane, Charlotte M', 'Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. kelm@stats.ox.ac.uk|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. kelm@stats.ox.ac.uk|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. kelm@stats.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 69, 'Databases, Protein|Membrane Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq554', '20926421', 'Membrane proteins (MPs) are important drug targets but knowledge of their exact structure is limited to relatively few examples. Existing homology-based structure prediction methods are designed for globular, water-soluble proteins. However, we are now beginning to have enough MP structures to justify the development of a homology-based approach specifically for them.'),
(75795, 2010, 'bio', 'TURNIP: tracking unresolved nucleotide polymorphisms in large hard-to-assemble regions of repetitive DNA sequence', 'Davey, Robert P|James, Stephen A|Dicks, Jo|Roberts, Ian N', 'National Collection of Yeast Cultures, Institute of Food Research and Department of Computational and Systems Biology, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UA, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research and Department of Computational and Systems Biology, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UA, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research and Department of Computational and Systems Biology, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UA, UK. robert.davey@bbsrc.ac.uk|National Collection of Yeast Cultures, Institute of Food Research and Department of Computational and Systems Biology, John Innes Centre, Norwich Research Park, Colney, Norwich, NR4 7UA, UK. robert.davey@bbsrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Base Sequence|DNA|Genome|Genomic Instability|Genomics|Molecular Sequence Data|Polymorphism, Genetic|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq557', '20926422', 'TURNIP comprises a suite of Perl scripts and modules that facilitates the resolution of microheterogeneity within hard-to-assemble repetitive DNA sequences. TURNIP was originally developed for the Saccharomyces Genome Resequencing Project (SGRP) within which the ribosomal DNA (rDNA) of 36 strains of S.cerevisiae were analysed to investigate the occurrence of potential polymorphisms. Here, partially resolved SNPs, or pSNPs, as well as indels, were found to be far more prevalent than previously suspected. More generally, the TURNIP software ascertains degrees of variation between large tandem repeats within a single locus, offering insights into mechanisms of genome stability and gene conversion in any organism for which genome sequence data are available.'),
(75796, 2010, 'bio', 'GPCRRD: G protein-coupled receptor spatial restraint database for 3D structure modeling and function annotation', 'Zhang, Jian|Zhang, Yang', 'Center for Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave, Ann Arbor, MI 48109, USA.|Center for Computational Medicine and Bioinformatics, University of Michigan, 100 Washtenaw Ave, Ann Arbor, MI 48109, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Databases, Protein|Models, Molecular|Molecular Sequence Annotation|Receptors, G-Protein-Coupled', 'Journal Article', '10.1093/bioinformatics/btq563', '20926423', 'G protein-coupled receptors (GPCRs) comprise the largest family of integral membrane proteins. They are the most important class of drug targets. While there exist crystal structures for only a very few GPCR sequences, numerous experiments have been performed on GPCRs to identify the critical residues and motifs. GPCRRD database is designed to systematically collect all experimental restraints (including residue orientation, contact and distance maps) available from the literature and primary GPCR resources using an automated text mining algorithm combined with manual validation, with the purpose of assisting GPCR 3D structure modeling and function annotation. The current dataset contains thousands of spatial restraints from mutagenesis, disulfide mapping distances, electron cryo-microscopy and Fourier-transform infrared spectroscopy experiments.'),
(75797, 2010, 'bio', 'Robust relationship inference in genome-wide association studies', 'Manichaikul, Ani|Mychaleckyj, Josyf C|Rich, Stephen S|Daly, Kathy|Sale, Michxc3xa8le|Chen, Wei-Min', 'Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.|Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.|Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.|Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.|Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.|Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA.', 'United States|United States|United States|United States|United States|United States', 618, 'Algorithms|Genome, Human|Genome-Wide Association Study|Genotype|Humans|Phenotype|Polymorphism, Single Nucleotide|Population Groups', 'Journal Article', '10.1093/bioinformatics/btq559', '20926424', 'Genome-wide association studies (GWASs) have been widely used to map loci contributing to variation in complex traits and risk of diseases in humans. Accurate specification of familial relationships is crucial for family-based GWAS, as well as in population-based GWAS with unknown (or unrecognized) family structure. The family structure in a GWAS should be routinely investigated using the SNP data prior to the analysis of population structure or phenotype. Existing algorithms for relationship inference have a major weakness of estimating allele frequencies at each SNP from the entire sample, under a strong assumption of homogeneous population structure. This assumption is often untenable.'),
(75798, 2010, 'bio', 'PyETV: a PyMOL evolutionary trace viewer to analyze functional site predictions in protein complexes', 'Lua, Rhonald C|Lichtarge, Olivier', 'Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.', 'United States|United States', 24, 'Binding Sites|Cluster Analysis|Evolution, Molecular|Multiprotein Complexes|Protein Interaction Mapping|Protein Structure, Quaternary|Software', 'Journal Article', '10.1093/bioinformatics/btq566', '20929911', 'PyETV is a PyMOL plugin for viewing, analyzing and manipulating predictions of evolutionarily important residues and sites in protein structures and their complexes. It seamlessly captures the output of the Evolutionary Trace server, namely ranked importance of residues, for multiple chains of a complex. It then yields a high resolution graphical interface showing their distribution and clustering throughout a quaternary structure, including at interfaces. Together with other tools in the popular PyMOL viewer, PyETV thus provides a novel tool to integrate evolutionary forces into the design of experiments targeting the most functionally relevant sites of a protein.'),
(75799, 2010, 'bio', 'Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity', 'Aggio, Raphael B M|Ruggiero, Katya|Villas-Bôas, Silas Granato', 'School of Biological Sciences, The University of Auckland, 3A Symonds Street, Private Bag 92019, Auckland 1142, New Zealand.|School of Biological Sciences, The University of Auckland, 3A Symonds Street, Private Bag 92019, Auckland 1142, New Zealand.|School of Biological Sciences, The University of Auckland, 3A Symonds Street, Private Bag 92019, Auckland 1142, New Zealand.', 'New Zealand|New Zealand|New Zealand', 0, 'Algorithms|Metabolic Networks and Pathways|Metabolomics|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btq567', '20929912', 'Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes.'),
(75800, 2010, 'bio', 'R3D Align: global pairwise alignment of RNA 3D structures using local superpositions', 'Rahrig, Ryan R|Leontis, Neocles B|Zirbel, Craig L', 'Department of Mathematics and Statistics at Ohio Northern University, Ada, OH 45810, USA. r-rahrig@onu.edu|Department of Mathematics and Statistics at Ohio Northern University, Ada, OH 45810, USA. r-rahrig@onu.edu|Department of Mathematics and Statistics at Ohio Northern University, Ada, OH 45810, USA. r-rahrig@onu.edu', 'United States|United States|United States', 0, 'Algorithms|Nucleic Acid Conformation|RNA|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq506', '20929913', 'Comparing 3D structures of homologous RNA molecules yields information about sequence and structural variability. To compare large RNA 3D structures, accurate automatic comparison tools are needed. In this article, we introduce a new algorithm and web server to align large homologous RNA structures nucleotide by nucleotide using local superpositions that accommodate the flexibility of RNA molecules. Local alignments are merged to form a global alignment by employing a maximum clique algorithm on a specially defined graph that we call the local alignment graph.'),
(75801, 2010, 'bio', 'High-throughput prediction of protein antigenicity using protein microarray data', 'Magnan, Christophe N|Zeller, Michael|Kayala, Matthew A|Vigil, Adam|Randall, Arlo|Felgner, Philip L|Baldi, Pierre', 'Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|Institute for Genomics and Bioinformatics, School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Antigens|Antigens, Bacterial|Humans|Protein Array Analysis|Proteins|Proteomics|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btq551', '20934990', 'Discovery of novel protective antigens is fundamental to the development of vaccines for existing and emerging pathogens. Most computational methods for predicting protein antigenicity rely directly on homology with previously characterized protective antigens, however, homology-based methods will fail to discover truly novel protective antigens. Thus, there is a significant need for homology-free methods capable of screening entire proteomes for the antigens most likely to generate a protective humoral immune response.'),
(75802, 2010, 'bio', 'Graph-based word sense disambiguation of biomedical documents', 'Agirre, Eneko|Soroa, Aitor|Stevenson, Mark', 'IXA NLP Group, University of the Basque Country, Donostia, Basque Country, Spain.|IXA NLP Group, University of the Basque Country, Donostia, Basque Country, Spain.|IXA NLP Group, University of the Basque Country, Donostia, Basque Country, Spain.', 'Spain|Spain|Spain', 0, 'Algorithms|Computational Biology|Databases, Factual|Pattern Recognition, Automated|Unified Medical Language System|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btq555', '20934991', 'Word Sense Disambiguation (WSD), automatically identifying the meaning of ambiguous words in context, is an important stage of text processing. This article presents a graph-based approach to WSD in the biomedical domain. The method is unsupervised and does not require any labeled training data. It makes use of knowledge from the Unified Medical Language System (UMLS) Metathesaurus which is represented as a graph. A state-of-the-art algorithm, Personalized PageRank, is used to perform WSD.'),
(75803, 2010, 'bio', 'Target-align: a tool for plant microRNA target identification', 'Xie, Fuliang|Zhang, Baohong', 'Department of Biology, East Carolina University, Greenville, NC 27858, USA.|Department of Biology, East Carolina University, Greenville, NC 27858, USA.', 'United States|United States', 60, 'Base Pair Mismatch|Computational Biology|Gene Expression Regulation, Plant|MicroRNAs|RNA, Plant|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btq568', '20934992', 'MicroRNAs (miRNAs) are important regulatory molecules. A critical step in elucidating miRNA function is identifying potential miRNA targets. However, few reliable tools have been developed for identifying miRNA targets in plants.'),
(75804, 2010, 'bio', 'Pre-calculated protein structure alignments at the RCSB PDB website', 'Prlic, Andreas|Bliven, Spencer|Rose, Peter W|Bluhm, Wolfgang F|Bizon, Chris|Godzik, Adam|Bourne, Philip E', 'San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu|San Diego Supercomputer Center, University of California San Diego, 9500 Gilman Drive, Mailcode 0505 La Jolla, CA 92093-0505, USA. andreas@sdsc.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Internet|Proteins|Software|Structural Homology, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq572', '20937596', 'With the continuous growth of the RCSB Protein Data Bank (PDB), providing an up-to-date systematic structure comparison of all protein structures poses an ever growing challenge. Here, we present a comparison tool for calculating both 1D protein sequence and 3D protein structure alignments. This tool supports various applications at the RCSB PDB website. First, a structure alignment web service calculates pairwise alignments. Second, a stand-alone application runs alignments locally and visualizes the results. Third, pre-calculated 3D structure comparisons for the whole PDB are provided and updated on a weekly basis. These three applications allow users to discover novel relationships between proteins available either at the RCSB PDB or provided by the user.'),
(75805, 2010, 'bio', 'A classification model for G-to-A hypermutation in hepatitis B virus ultra-deep pyrosequencing reads', 'Reuman, Elizabeth C|Margeridon-Thermet, Severine|Caudill, Harrison B|Liu, Tommy|Borroto-Esoda, Katyna|Svarovskaia, Evguenia S|Holmes, Susan P|Shafer, Robert W', 'Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org|Department of Medicine, Division of Infectious Diseases, Stanford University, Stanford, CA 94305, USA. ereuman@stanfordalumni.org', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Adenine|Algorithms|Classification|DNA Mutational Analysis|Drug Resistance, Viral|Guanine|Hepatitis B|Hepatitis B virus|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Mutation', 'Journal Article', '10.1093/bioinformatics/btq570', '20937597', 'G xe2x86x92 A hypermutation is an innate antiviral defense mechanism, mediated by host enzymes, which leads to the mutational impairment of viruses. Sensitive and specific identification of host-mediated G xe2x86x92 A hypermutation is a novel sequence analysis challenge, particularly for viral deep sequencing studies. For example, two of the most common hepatitis B virus (HBV) reverse transcriptase (RT) drug-resistance mutations, A181T and M204I, arise from G xe2x86x92 A changes and are routinely detected as low-abundance variants in nearly all HBV deep sequencing samples.'),
(75806, 2010, 'bio', 'PICMI: mapping point mutations on genomes', 'Le Pera, Loredana|Marcatili, Paolo|Tramontano, Anna', 'Department of Biochemical Sciences, Sapienza University of Rome, P.le A. Moro, 5-00185 Rome, Italy.|Department of Biochemical Sciences, Sapienza University of Rome, P.le A. Moro, 5-00185 Rome, Italy.|Department of Biochemical Sciences, Sapienza University of Rome, P.le A. Moro, 5-00185 Rome, Italy.', 'Italy|Italy|Italy', 3, 'Databases, Genetic|Genome|Genomics|Point Mutation|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btq547', '20940168', 'Several international collaborations and local projects are producing extensive catalogues of genomic variations that are supplementing existing collections such as the OMIM catalogue. The flood of this type of data will keep increasing and, especially, it will be relevant to a wider user base, including not only molecular biologists, geneticists and bioinformaticians, but also clinical researchers. Mapping the observed variations, sometimes only described at the amino acid level, on a genome, identifying whether they affect a gene and-if so-whether they also affect different isoforms of the same gene, is a time consuming and often frustrating task.'),
(75807, 2010, 'bio', 'The SMARTCyp cytochrome P450 metabolism prediction server', 'Rydberg, Patrik|Gloriam, David E|Olsen, Lars', 'Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark.|Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark.|Department of Medicinal Chemistry, Faculty of Pharmaceutical Sciences, University of Copenhagen, Universitetsparken 2, DK-2100 Copenhagen, Denmark.', 'Denmark|Denmark|Denmark', 0, 'Computational Biology|Cytochrome P-450 Enzyme System|Inactivation, Metabolic|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btq584', '20947523', 'The SMARTCyp server is the first web application for site of metabolism prediction of cytochrome P450-mediated drug metabolism.'),
(75808, 2010, 'bio', 'OmicsAnalyzer: a Cytoscape plug-in suite for modeling omics data', 'Xia, Tian|Hemert, John V|Dickerson, Julie A', 'Program of Bioinformatics and Computational Biology and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Program of Bioinformatics and Computational Biology and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Program of Bioinformatics and Computational Biology and Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States', 15, 'Data Interpretation, Statistical|Gene Expression Profiling|Gene Regulatory Networks|Models, Biological|Models, Genetic|Software', 'Journal Article', '10.1093/bioinformatics/btq583', '20947524', 'OmicsAnalyzer is a Cytoscape plug-in for visual omics-based network analysis that (i) integrates hetero-omics data for one or more species, (ii) performs statistical tests on the integrated datasets, and (iii) visualizes results in a network context.'),
(75809, 2010, 'bio', 'Model quality assessment for membrane proteins', 'Ray, Arjun|Lindahl, Erik|Wallner, Björn', 'Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.|Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.|Department of Biochemistry & Biophysics, Stockholm University, Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 0, 'Artificial Intelligence|Binding Sites|Membrane Proteins|Models, Molecular|Protein Conformation', 'Evaluation Studies', '10.1093/bioinformatics/btq581', '20947525', 'Learning-based model quality assessment programs have been quite successful at discriminating between high- and low-quality protein structures. Here, we show that it is possible to improve this performance significantly by restricting the learning space to a specific context, in this case membrane proteins. Since these are among the most important structures from a pharmaceutical point-of-view, it is particularly interesting to resolve local model quality for regions corresponding, e.g. to binding sites.');
