INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77156, 2012, 'bio', 'HighSSR: high-throughput SSR characterization and locus development from next-gen sequencing data', 'Churbanov, Alexander|Ryan, Rachael|Hasan, Nabeeh|Bailey, Donovan|Chen, Haofeng|Milligan, Brook|Houde, Peter', 'New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn|New Mexico State University, Biology Deptartment, MSC 3AF, PO Box 30001, Las Cruces, NM 88003, USA. alexander@big.ac.cn', 'Mexico|Mexico|Mexico|Mexico|Mexico|Mexico|Mexico', 0, 'Algorithms|Animals|Butterflies|Fungi|Gene Library|Genetic Markers|Genome|High-Throughput Nucleotide Sequencing|Microsatellite Repeats|Multigene Family|Plants|Polymorphism, Genetic|Species Specificity', 'Evaluation Studies', '10.1093/bioinformatics/bts524', '22954626', 'Microsatellites are among the most useful genetic markers in population biology. High-throughput sequencing of microsatellite-enriched libraries dramatically expedites the traditional process of screening recombinant libraries for microsatellite markers. However, sorting through millions of reads to distill high-quality polymorphic markers requires special algorithms tailored to tolerate sequencing errors in locus reconstruction, distinguish paralogous loci, rarify raw reads originating from the same amplicon and sort out various artificial fragments resulting from recombination or concatenation of auxiliary adapters. Existing programs warrant improvement.'),
(77157, 2012, 'bio', 'Genome-wide in silico prediction of gene expression', 'McLeay, Robert C|Lesluyes, Tom|Cuellar Partida, Gabriel|Bailey, Timothy L', 'Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia|Australia|Australia', 32, 'Animals|Base Sequence|Binding Sites|Chromatin|Chromatin Immunoprecipitation|Computer Simulation|Embryonic Stem Cells|Gene Expression|Genome-Wide Association Study|Histones|Linear Models|Mice|Models, Molecular|Protein Binding|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts529', '22954627', 'Modelling the regulation of gene expression can provide insight into the regulatory roles of individual transcription factors (TFs) and histone modifications. Recently, Ouyang et al. in 2009 modelled gene expression levels in mouse embryonic stem (mES) cells using in vivo ChIP-seq measurements of TF binding. ChIP-seq TF binding data, however, are tissue-specific and relatively difficult to obtain. This limits the applicability of gene expression models that rely on ChIP-seq TF binding data.'),
(77158, 2012, 'bio', 'Application and evaluation of automated methods to extract neuroanatomical connectivity statements from free text', 'French, Leon|Lane, Suzanne|Xu, Lydia|Siu, Celia|Kwok, Cathy|Chen, Yiqi|Krebs, Claudia|Pavlidis, Paul', 'Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.|Department of Psychiatry, University of British Columbia, Vancouver, BC V6T 1Z4, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Artificial Intelligence|Data Mining|Databases, Factual|Neuroanatomy|Periodicals as Topic|Rats|Software', 'Journal Article', '10.1093/bioinformatics/bts542', '22954628', 'Automated annotation of neuroanatomical connectivity statements from the neuroscience literature would enable accessible and large-scale connectivity resources. Unfortunately, the connectivity findings are not formally encoded and occur as natural language text. This hinders aggregation, indexing, searching and integration of the reports. We annotated a set of 1377 abstracts for connectivity relations to facilitate automated extraction of connectivity relationships from neuroscience literature. We tested several baseline measures based on co-occurrence and lexical rules. We compare results from seven machine learning methods adapted from the protein interaction extraction domain that employ part-of-speech, dependency and syntax features.'),
(77159, 2012, 'bio', 'MaConDa: a publicly accessible mass spectrometry contaminants database', 'Weber, Ralf J M|Li, Eva|Bruty, Jonathan|He, Shan|Viant, Mark R', 'School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.|School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.|School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.|School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.|School of Biosciences, University of Birmingham, Birmingham B15 2TT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 19, 'Chemistry, Analytic|Databases, Chemical|Equipment Contamination|Information Storage and Retrieval|Internet|Mass Spectrometry|Metabolomics|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts527', '22954629', 'Mass spectrometry is widely used in bioanalysis, including the fields of metabolomics and proteomics, to simultaneously measure large numbers of molecules in complex biological samples. Contaminants routinely occur within these samples, for example, originating from the solvents or plasticware. Identification of these contaminants is crucial to enable their removal before data analysis, in particular to maintain the validity of conclusions drawn from uni- and multivariate statistical analyses. Although efforts have been made to report contaminants within mass spectra, this information is fragmented and its accessibility is relatively limited. In response to the needs of the bioanalytical community, here we report the creation of an extensive manually well-annotated database of currently known small molecule contaminants.'),
(77160, 2012, 'bio', 'SAPIN: a framework for the structural analysis of protein interaction networks', 'Yang, Jae-Seong|Campagna, Anne|Delgado, Javier|Vanhee, Peter|Serrano, Luis|Kiel, Christina', 'EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu|EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu|EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu|EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu|EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu|EMBL/CRG, Design of Biological Systems, Systems Biology Research Unit, Centre for Genomic Regulation-CRG, UPF, 08003 Barcelona, Spain. jae-seong.yang@crg.eu', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Humans|Protein Interaction Mapping|Protein Interaction Maps|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts539', '22954630', 'Protein interaction networks are widely used to depict the relationships between proteins. These networks often lack the information on physical binary interactions, and they do not inform whether there is incompatibility of structure between binding partners. Here, we introduce SAPIN, a framework dedicated to the structural analysis of protein interaction networks. SAPIN first identifies the protein parts that could be involved in the interaction and provides template structures. Next, SAPIN performs structural superimpositions to identify compatible and mutually exclusive interactions. Finally, the results are displayed using Cytoscape Web.'),
(77161, 2012, 'bio', 'Impact of ontology evolution on functional analyses', 'Groß, Anika|Hartung, Michael|Prüfer, Kay|Kelso, Janet|Rahm, Erhard', 'Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de|Department of Computer Science, University of Leipzig, Leipzig, Germany. gross@informatik.uni-leipzig.de', 'Germany|Germany|Germany|Germany|Germany', 24, 'Animals|Genes|Molecular Sequence Annotation|Primates|Rodentia|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts498', '22954631', 'Ontologies are used in the annotation and analysis of biological data. As knowledge accumulates, ontologies and annotation undergo constant modifications to reflect this new knowledge. These modifications may influence the results of statistical applications such as functional enrichment analyses that describe experimental data in terms of ontological groupings. Here, we investigate to what degree modifications of the Gene Ontology (GO) impact these statistical analyses for both experimental and simulated data. The analysis is based on new measures for the stability of result sets and considers different ontology and annotation changes.'),
(77162, 2012, 'bio', 'Comb-p: software for combining, analyzing, grouping and correcting spatially correlated P-values', 'Pedersen, Brent S|Schwartz, David A|Yang, Ivana V|Kechris, Katerina J', 'Department of Medicine, University of Colorado, Denver, Anschutz Medical Campus, Aurora, CO 80045, USA. bpederse@gmail.com|Department of Medicine, University of Colorado, Denver, Anschutz Medical Campus, Aurora, CO 80045, USA. bpederse@gmail.com|Department of Medicine, University of Colorado, Denver, Anschutz Medical Campus, Aurora, CO 80045, USA. bpederse@gmail.com|Department of Medicine, University of Colorado, Denver, Anschutz Medical Campus, Aurora, CO 80045, USA. bpederse@gmail.com', 'United States|United States|United States|United States', 125, 'DNA Probes|Genome-Wide Association Study|Genomics|Humans|Programming Languages|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts545', '22954632', 'comb-p is a command-line tool and a python library that manipulates BED files of possibly irregularly spaced P-values and (1) calculates auto-correlation, (2) combines adjacent P-values, (3) performs false discovery adjustment, (4) finds regions of enrichment (i.e. series of adjacent low P-values) and (5) assigns significance to those regions. In addition, tools are provided for visualization and assessment. We provide validation and example uses on bisulfite-seq with P-values from Fishers exact test, tiled methylation probes using a linear model and Dam-ID for chromatin binding using moderated t-statistics. Because the library accepts input in a simple, standardized format and is unaffected by the origin of the P-values, it can be used for a wide variety of applications.'),
(77163, 2012, 'bio', 'Mendel-GPU: haplotyping and genotype imputation on graphics processing units', 'Chen, Gary K|Wang, Kai|Stram, Alex H|Sobel, Eric M|Lange, Kenneth', 'Department of Preventive Medicine, USC, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu|Department of Preventive Medicine, USC, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu|Department of Preventive Medicine, USC, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu|Department of Preventive Medicine, USC, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu|Department of Preventive Medicine, USC, Los Angeles, CA 90089, USA. gary.k.chen@usc.edu', 'United States|United States|United States|United States|United States', 7, 'Algorithms|Genome, Human|Genome-Wide Association Study|Genotype|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts536', '22954633', 'In modern sequencing studies, one can improve the confidence of genotype calls by phasing haplotypes using information from an external reference panel of fully typed unrelated individuals. However, the computational demands are so high that they prohibit researchers with limited computational resources from haplotyping large-scale sequence data.'),
(77164, 2012, 'bio', 'RAPHAEL: recognition, periodicity and insertion assignment of solenoid protein structures', 'Walsh, Ian|Sirocco, Francesco G|Minervini, Giovanni|Di Domenico, Tomás|Ferrari, Carlo|Tosatto, Silvio C E', 'Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.|Department of Biology, University of Padua, Viale G. Colombo 3, 35131 Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Protein Structure, Tertiary|Proteins|Repetitive Sequences, Amino Acid|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bts550', '22962341', 'Repeat proteins form a distinct class of structures where folding is greatly simplified. Several classes have been defined, with solenoid repeats of periodicity between ca. 5 and 40 being the most challenging to detect. Such proteins evolve quickly and their periodicity may be rapidly hidden at sequence level. From a structural point of view, finding solenoids may be complicated by the presence of insertions or multiple domains. To the best of our knowledge, no automated methods are available to characterize solenoid repeats from structure.'),
(77165, 2012, 'bio', 'GREVE: Genomic Recurrent Event ViEwer to assist the identification of patterns across individual cancer samples', 'Cazier, Jean-Baptiste|Holmes, Chris C|Broxholme, John', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, OX3 7BN and Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, Oxford, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, OX3 7BN and Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, Oxford, UK.|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, OX3 7BN and Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, Oxford, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Chromosome Aberrations|Chromosome Breakpoints|Genome, Human|Humans|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts547', '22962342', 'GREVE has been developed to assist with the identification of recurrent genomic aberrations across cancer samples. The exact characterization of such aberrations remains a challenge despite the availability of increasing amount of data, from SNParray to next-generation sequencing. Furthermore, genomic aberrations in cancer are especially difficult to handle because they are, by nature, unique to the patients. However, their recurrence in specific regions of the genome has been shown to reflect their relevance in the development of tumors. GREVE makes use of previously characterized events to identify such regions and focus any further analysis.'),
(77166, 2012, 'bio', 'ImgLib2--generic image processing in Java', 'Pietzsch, Tobias|Preibisch, Stephan|Tomancák, Pavel|Saalfeld, Stephan', 'Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.|Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.|Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.|Max Planck Institute of Molecular Cell Biology and Genetics, 01307 Dresden, Germany.', 'Germany|Germany|Germany|Germany', 47, 'Algorithms|Image Processing, Computer-Assisted|Programming Languages|Software', 'Journal Article', '10.1093/bioinformatics/bts543', '22962343', 'ImgLib2 is an open-source Java library for n-dimensional data representation and manipulation with focus on image processing. It aims at minimizing code duplication by cleanly separating pixel-algebra, data access and data representation in memory. Algorithms can be implemented for classes of pixel types and generic access patterns by which they become independent of the specific dimensionality, pixel type and data representation. ImgLib2 illustrates that an elegant high-level programming interface can be achieved without sacrificing performance. It provides efficient implementations of common data types, storage layouts and algorithms. It is the data model underlying ImageJ2, the KNIME Image Processing toolbox and an increasing number of Fiji-Plugins.'),
(77167, 2012, 'bio', 'ChemBioServer: a web-based pipeline for filtering, clustering and visualization of chemical compounds used in drug discovery', 'Athanasiadis, Emmanouil|Cournia, Zoe|Spyrou, George', 'Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece.|Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece.|Biomedical Research Foundation, Academy of Athens, 4 Soranou Ephessiou, 11527 Athens, Greece.', 'Greece|Greece|Greece', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Drug Discovery|Internet|Software', 'Journal Article', '10.1093/bioinformatics/bts551', '22962344', 'ChemBioServer is a publicly available web application for effectively mining and filtering chemical compounds used in drug discovery. It provides researchers with the ability to (i) browse and visualize compounds along with their properties, (ii) filter chemical compounds for a variety of properties such as steric clashes and toxicity, (iii) apply perfect match substructure search, (iv) cluster compounds according to their physicochemical properties providing representative compounds for each cluster, (v) build custom compound mining pipelines and (vi) quantify through property graphs the top ranking compounds in drug discovery procedures. ChemBioServer allows for pre-processing of compounds prior to an in silico screen, as well as for post-processing of top-ranked molecules resulting from a docking exercise with the aim to increase the efficiency and the quality of compound selection that will pass to the experimental test phase.'),
(77168, 2012, 'bio', 'Pythoscape: a framework for generation of large protein similarity networks', 'Barber, Alan E|Babbitt, Patricia C', 'Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA.|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA.', 'United States|United States', 0, 'Base Sequence|Data Collection|Data Display|Glutathione Transferase|Multigene Family|Proteins|Software|Structure-Activity Relationship|Substrate Specificity', 'Journal Article', '10.1093/bioinformatics/bts532', '22962345', 'Pythoscape is a framework implemented in Python for processing large protein similarity networks for visualization in other software packages. Protein similarity networks are graphical representations of sequence, structural and other similarities among proteins for which pairwise all-by-all similarity connections have been calculated. Mapping of biological and other information to network nodes or edges enables hypothesis creation about sequence-structure-function relationships across sets of related proteins. Pythoscape provides several options to calculate pairwise similarities for input sequences or structures, applies filters to network edges and defines sets of similar nodes and their associated data as single nodes (termed representative nodes) for compression of network information and output data or formatted files for visualization.'),
(77169, 2012, 'bio', 'Comparing clustering and pre-processing in taxonomy analysis', 'Bonder, Marc J|Abeln, Sanne|Zaura, Egija|Brandt, Bernd W', 'Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam-ACTA, University of Amsterdam and VU University Amsterdam, VU University Amsterdam, The Netherlands. bonder.m.j@gmail.com|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam-ACTA, University of Amsterdam and VU University Amsterdam, VU University Amsterdam, The Netherlands. bonder.m.j@gmail.com|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam-ACTA, University of Amsterdam and VU University Amsterdam, VU University Amsterdam, The Netherlands. bonder.m.j@gmail.com|Department of Preventive Dentistry, Academic Centre for Dentistry Amsterdam-ACTA, University of Amsterdam and VU University Amsterdam, VU University Amsterdam, The Netherlands. bonder.m.j@gmail.com', 'Netherlands|Netherlands|Netherlands|Netherlands', 49, 'Algorithms|Bacteria|Bacterial Typing Techniques|Cluster Analysis|DNA, Bacterial|High-Throughput Nucleotide Sequencing|Humans|RNA, Ribosomal, 16S|Saliva', 'Comparative Study', '10.1093/bioinformatics/bts552', '22962346', 'Massively parallel sequencing allows for rapid sequencing of large numbers of sequences in just a single run. Thus, 16S ribosomal RNA (rRNA) amplicon sequencing of complex microbial communities has become possible. The sequenced 16S rRNA fragments (reads) are clustered into operational taxonomic units and taxonomic categories are assigned. Recent reports suggest that data pre-processing should be performed before clustering. We assessed combinations of data pre-processing steps and clustering algorithms on cluster accuracy for oral microbial sequence data.'),
(77170, 2012, 'bio', 'FetalQuant: deducing fractional fetal DNA concentration from massively parallel sequencing of DNA in maternal plasma', 'Jiang, Peiyong|Chan, K C Allen|Liao, Gary J W|Zheng, Yama W L|Leung, Tak Y|Chiu, Rossa W K|Lo, Yuk Ming Dennis|Sun, Hao', 'Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.|Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China.', 'China|China|China|China|China|China|China|China', 0, 'Aneuploidy|Bayes Theorem|Female|Fetus|High-Throughput Nucleotide Sequencing|Humans|Plasma|Polymorphism, Single Nucleotide|Pregnancy|Prenatal Diagnosis|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts549', '22962347', 'The fractional fetal DNA concentration is one of the critical parameters for non-invasive prenatal diagnosis based on the analysis of DNA in maternal plasma. Massively parallel sequencing (MPS) of DNA in maternal plasma has been demonstrated to be a powerful tool for the non-invasive prenatal diagnosis of fetal chromosomal aneuploidies. With the rapid advance of MPS technologies, the sequencing cost per base is dramatically reducing, especially when using targeted MPS. Even though several approaches have been developed for deducing the fractional fetal DNA concentration, none of them can be used to deduce the fractional fetal DNA concentration directly from the sequencing data without prior genotype information.'),
(77171, 2012, 'bio', 'Context-specific transcriptional regulatory network inference from global gene expression maps using double two-way t-tests', 'Qi, Jianlong|Michoel, Tom', 'School of Life Sciences-LifeNet, Freiburg Institute for Advanced Studies, University of Freiburg, Albertstrasse 19, D-79104 Freiburg im Breisgau, Germany.|School of Life Sciences-LifeNet, Freiburg Institute for Advanced Studies, University of Freiburg, Albertstrasse 19, D-79104 Freiburg im Breisgau, Germany.', 'Germany|Germany', 10, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Humans|Models, Statistical|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts434', '22962443', 'Transcriptional regulatory network inference methods have been studied for years. Most of them rely on complex mathematical and algorithmic concepts, making them hard to adapt, re-implement or integrate with other methods. To address this problem, we introduce a novel method based on a minimal statistical model for observing transcriptional regulatory interactions in noisy expression data, which is conceptually simple, easy to implement and integrate in any statistical software environment and equally well performing as existing methods.'),
(77172, 2012, 'bio', 'ECCB 2012: The 11th European Conference on Computational Biology', 'Schwede, Torsten|Iber, Dagmar', 'School of Life Sciences-LifeNet, Freiburg Institute for Advanced Studies, University of Freiburg, Albertstrasse 19, D-79104 Freiburg im Breisgau, Germany.|School of Life Sciences-LifeNet, Freiburg Institute for Advanced Studies, University of Freiburg, Albertstrasse 19, D-79104 Freiburg im Breisgau, Germany.', 'Germany|Germany', 2, 'Computational Biology|Molecular Biology', 'Editorial', '10.1093/bioinformatics/bts490', '22962444', '-'),
(77173, 2012, 'bio', 'Telescoper: de novo assembly of highly repetitive regions', 'Bresler, Maayan|Sheehan, Sara|Chan, Andrew H|Song, Yun S', 'Department of EECS, University of California, Berkeley, CA 94720, USA.|Department of EECS, University of California, Berkeley, CA 94720, USA.|Department of EECS, University of California, Berkeley, CA 94720, USA.|Department of EECS, University of California, Berkeley, CA 94720, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|DNA|Genome|Genomics|High-Throughput Nucleotide Sequencing|Repetitive Sequences, Nucleic Acid|Saccharomyces cerevisiae|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts399', '22962446', 'With advances in sequencing technology, it has become faster and cheaper to obtain short-read data from which to assemble genomes. Although there has been considerable progress in the field of genome assembly, producing high-quality de novo assemblies from short-reads remains challenging, primarily because of the complex repeat structures found in the genomes of most higher organisms. The telomeric regions of many genomes are particularly difficult to assemble, though much could be gained from the study of these regions, as their evolution has not been fully characterized and they have been linked to aging.'),
(77174, 2012, 'bio', 'Long read alignment based on maximal exact match seeds', 'Liu, Yongchao|Schmidt, Bertil', 'Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de', 'Germany|Germany', 66, 'Algorithms|Chromosome Mapping|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts414', '22962447', 'The explosive growth of next-generation sequencing datasets poses a challenge to the mapping of reads to reference genomes in terms of alignment quality and execution speed. With the continuing progress of high-throughput sequencing technologies, read length is constantly increasing and many existing aligners are becoming inefficient as generated reads grow larger.'),
(77175, 2012, 'bio', 'Indel-tolerant read mapping with trinucleotide frequencies using cache-oblivious kd-trees', 'Mahmud, Md Pavel|Wiedenhoeft, John|Schliep, Alexander', 'Department of Computer Science, Rutgers University, New Jersey, USA. pavelm@cs.rutgers.edu|Department of Computer Science, Rutgers University, New Jersey, USA. pavelm@cs.rutgers.edu|Department of Computer Science, Rutgers University, New Jersey, USA. pavelm@cs.rutgers.edu', 'Jersey|Jersey|Jersey', 0, 'Chromosome Mapping|Genetic Variation|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Nucleotides|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts380', '22962448', 'Mapping billions of reads from next generation sequencing experiments to reference genomes is a crucial task, which can require hundreds of hours of running time on a single CPU even for the fastest known implementations. Traditional approaches have difficulties dealing with matches of large edit distance, particularly in the presence of frequent or large insertions and deletions (indels). This is a serious obstacle both in determining the spectrum and abundance of genetic variations and in personal genomics.'),
(77176, 2012, 'bio', 'DELLY: structural variant discovery by integrated paired-end and split-read analysis', 'Rausch, Tobias|Zichner, Thomas|Schlattl, Andreas|Stütz, Adrian M|Benes, Vladimir|Korbel, Jan O', 'European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de|European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de|European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de|European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de|European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de|European Molecular Biology Laboratory, Genome Biology, Meyerhofstr. 1, 69117 Heidelberg, Germany. tobias.rausch@embl.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 679, 'Chromosome Mapping|Genome, Human|Genomic Structural Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA|Sequence Deletion|Software', 'Journal Article', '10.1093/bioinformatics/bts378', '22962449', 'The discovery of genomic structural variants (SVs) at high sensitivity and specificity is an essential requirement for characterizing naturally occurring variation and for understanding pathological somatic rearrangements in personal genome sequencing data. Of particular interest are integrated methods that accurately identify simple and complex rearrangements in heterogeneous sequencing datasets at single-nucleotide resolution, as an optimal basis for investigating the formation mechanisms and functional consequences of SVs.'),
(77177, 2012, 'bio', 'Decoding properties of tRNA leave a detectable signal in codon usage bias', 'Roth, Alexander C', 'Swiss Institute of Bioinformatics, and Department of Computer Science, ETH Zurich, 8092 Zurich, Switzerland. alexander.roth@isb-sib.ch', 'Switzerland', 0, 'Anticodon|Codon|Evolution, Molecular|Gene Dosage|Genetic Code|Genome, Fungal|Genomics|Markov Chains|RNA, Transfer|Regression Analysis|Saccharomyces cerevisiae|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/bts403', '22962450', 'The standard genetic code translates 61 codons into 20 amino acids using fewer than 61 transfer RNAs (tRNAs). This is possible because of the tRNAs ability to wobble at the third base to decode more than one codon. Although the anticodon-codon mapping of tRNA to mRNA is a prerequisite for certain codon usage indices and can contribute to the understanding of the evolution of alternative genetic codes, it is usually not determined experimentally because such assays are prohibitively expensive and elaborate. Instead, the codon reading is approximated from theoretical inferences of nucleotide binding, the wobble rules. Unfortunately, these rules fail to capture all of the nuances of codon reading. This study addresses the codon reading properties of tRNAs and their evolutionary impact on codon usage bias.'),
(77178, 2012, 'bio', 'Accurate estimation of short read mapping quality for next-generation genome sequencing', 'Ruffalo, Matthew|Koyutürk, Mehmet|Ray, Soumya|LaFramboise, Thomas', 'Department of Electrical Engineering & Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu|Department of Electrical Engineering & Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu|Department of Electrical Engineering & Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu|Department of Electrical Engineering & Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. matthew.ruffalo@case.edu', 'United States|United States|United States|United States', 0, 'Artificial Intelligence|Chromosome Mapping|Genome, Human|Genomics|High-Throughput Nucleotide Sequencing|Humans|Logistic Models|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts408', '22962451', 'Several software tools specialize in the alignment of short next-generation sequencing reads to a reference sequence. Some of these tools report a mapping quality score for each alignment-in principle, this quality score tells researchers the likelihood that the alignment is correct. However, the reported mapping quality often correlates weakly with actual accuracy and the qualities of many mappings are underestimated, encouraging the researchers to discard correct mappings. Further, these low-quality mappings tend to correlate with variations in the genome (both single nucleotide and structural), and such mappings are important in accurately identifying genomic variants.'),
(77179, 2012, 'bio', 'MetaCluster 50: a two-round binning approach for metagenomic data for low-abundance species in a noisy sample', 'Wang, Yi|Leung, Henry C M|Yiu, S M|Chin, Francis Y L', 'Department of Computer Science, The University of Hong Kong, Hong Kong.|Department of Computer Science, The University of Hong Kong, Hong Kong.|Department of Computer Science, The University of Hong Kong, Hong Kong.|Department of Computer Science, The University of Hong Kong, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 77, 'Algorithms|Metagenomics|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts397', '22962452', 'Metagenomic binning remains an important topic in metagenomic analysis. Existing unsupervised binning methods for next-generation sequencing (NGS) reads do not perform well on (i) samples with low-abundance species or (ii) samples (even with high abundance) when there are many extremely low-abundance species. These two problems are common for real metagenomic datasets. Binning methods that can solve these problems are desirable.'),
(77180, 2012, 'bio', 'Stitching gene fragments with a network matching algorithm improves gene assembly for metagenomics', 'Wu, Yu-Wei|Rho, Mina|Doak, Thomas G|Ye, Yuzhen', 'School of Informatics and Computing, Indiana University, Bloomington, IN 47405, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47405, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47405, USA.|School of Informatics and Computing, Indiana University, Bloomington, IN 47405, USA.', 'India|India|India|India', 0, 'Algorithms|Genes, Archaeal|Genes, Bacterial|Metagenome|Metagenomics', 'Journal Article', '10.1093/bioinformatics/bts388', '22962453', 'One of the difficulties in metagenomic assembly is that homologous genes from evolutionarily closely related species may behave like repeats and confuse assemblers. As a result, small contigs, each representing a short gene fragment, instead of complete genes, may be reported by an assembler. This further complicates annotation of metagenomic datasets, as annotation tools (such as gene predictors or similarity search tools) typically perform poorly on configs encoding short gene fragments.'),
(77181, 2012, 'bio', 'An exome sequencing pipeline for identifying and genotyping common CNVs associated with disease with application to psoriasis', 'Coin, Lachlan J M|Cao, Dandan|Ren, Jingjing|Zuo, Xianbo|Sun, Liangdan|Yang, Sen|Zhang, Xuejun|Cui, Yong|Li, Yingrui|Jin, Xin|Wang, Jun', 'BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn|BGI-Shenzhen, Shenzhen, 518083, China. Lachlan.J.M.Coin@genomics.org.cn', 'China|China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|DNA Copy Number Variations|Exome|Genome, Human|Genotype|Humans|Psoriasis|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts379', '22962454', 'Despite the prevalence of copy number variation (CNV) in the human genome, only a handful of confirmed associations have been reported between common CNVs and complex disease. This may be partially attributed to the difficulty in accurately genotyping CNVs in large cohorts using array-based technologies. Exome sequencing is now widely being applied to case-control cohorts and presents an exciting opportunity to look for common CNVs associated with disease.'),
(77182, 2012, 'bio', 'Nonlinear dimension reduction with Wright-Fisher kernel for genotype aggregation and association mapping', 'Zhu, Hongjie|Li, Lexin|Zhou, Hua', 'Department of Psychiatry and Behavior Science, Duke University, Durham, NC 27710, USA. hongjie.zhu@duke.edu|Department of Psychiatry and Behavior Science, Duke University, Durham, NC 27710, USA. hongjie.zhu@duke.edu|Department of Psychiatry and Behavior Science, Duke University, Durham, NC 27710, USA. hongjie.zhu@duke.edu', 'United States|United States|United States', 4, 'Algorithms|Genetic Association Studies|Genotype|High-Throughput Nucleotide Sequencing|Humans|Markov Chains|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/bts406', '22962455', 'Association tests based on next-generation sequencing data are often under-powered due to the presence of rare variants and large amount of neutral or protective variants. A successful strategy is to aggregate genetic information within meaningful single-nucleotide polymorphism (SNP) sets, e.g. genes or pathways, and test association on SNP sets. Many existing methods for group-wise tests require specific assumptions about the direction of individual SNP effects and/or perform poorly in the presence of interactions.'),
(77183, 2012, 'bio', 'Evolution of gene neighborhoods within reconciled phylogenies', 'Bxc3xa9rard, Sxc3xa8verine|Gallien, Coralie|Boussau, Bastien|Szxc3xb6llxc5x91si, Gergely J|Daubin, Vincent|Tannier, Eric', 'Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr|Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr|Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr|Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr|Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr|Univ Montpellier2, UMR AMAP, Montpellier F-34000, France. Severine.Berard@cirad.fr', 'France|France|France|France|France|France', 0, 'Algorithms|Animals|Evolution, Molecular|Gene Duplication|Genes|Genome|Genome, Plant|Mammals|Models, Genetic|Phylogeny', 'Journal Article', '10.1093/bioinformatics/bts374', '22962456', 'Most models of genome evolution integrating gene duplications, losses and chromosomal rearrangements are computationally intract  able, even when comparing only two genomes. This prevents large-scale studies that consider different types of genome structural variations.'),
(77184, 2012, 'bio', 'Uncovering the co-evolutionary network among prokaryotic genes', 'Cohen, Ofir|Ashkenazy, Haim|Burstein, David|Pupko, Tal', 'Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel', 0, 'Evolution, Molecular|Genes, Bacterial|Genome|Genomics|Models, Genetic|Multigene Family|Phylogeny|Probability', 'Journal Article', '10.1093/bioinformatics/bts396', '22962457', 'Correlated events of gains and losses enable inference of co-evolution relations. The reconstruction of the co-evolutionary interactions network in prokaryotic species may elucidate functional associations among genes.'),
(77185, 2012, 'bio', 'Genomic context analysis reveals dense interaction network between vertebrate ultraconserved non-coding elements', 'Dimitrieva, Slavica|Bucher, Philipp', 'Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.|Swiss Institute for Experimental Cancer Research (ISREC), School of Life Sciences, Swiss Federal Institute of Technology (EPFL), Lausanne, Switzerland.', 'Switzerland|Switzerland', 13, 'Animals|Base Sequence|Conserved Sequence|Evolution, Molecular|Fishes|Genes, Developmental|Genome|Genomics|Humans|Introns|Phylogeny|Regulatory Sequences, Nucleic Acid|Vertebrates', 'Journal Article', '10.1093/bioinformatics/bts400', '22962458', 'Genomic context analysis, also known as phylogenetic profiling, is widely used to infer functional interactions between proteins but rarely applied to non-coding cis-regulatory DNA elements. We were wondering whether this approach could provide insights about utlraconserved non-coding elements (UCNEs). These elements are organized as large clusters, so-called gene regulatory blocks (GRBs) around key developmental genes. Their molecular functions and the reasons for their high degree of conservation remain enigmatic.'),
(77186, 2012, 'bio', 'Fractionation, rearrangement and subgenome dominance', 'Sankoff, David|Zheng, Chunfang', 'Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada K1N 6N5. sankoff@uottawa.ca|Department of Mathematics and Statistics, University of Ottawa, Ottawa, Canada K1N 6N5. sankoff@uottawa.ca', 'Canada|Canada', 0, 'Algorithms|Evolution, Molecular|Gene Order|Genome|Genome, Plant|Populus|Synteny', 'Journal Article', '10.1093/bioinformatics/bts392', '22962459', 'Fractionation is arguably the greatest cause of gene order disruption following whole genome duplication, causing severe biases in chromosome rearrangement-based estimates of evolutionary divergence.'),
(77187, 2012, 'bio', 'Inferring duplications, losses, transfers and incomplete lineage sorting with nonbinary species trees', 'Stolzer, Maureen|Lai, Han|Xu, Minli|Sathaye, Deepa|Vernot, Benjamin|Durand, Dannie', 'Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu|Department of Biological Sciences, Carnegie Mellon University, Pittsburgh, PA 15213, USA. mstolzer@andrew.cmu.edu', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Evolution, Molecular|Gene Duplication|Gene Transfer, Horizontal|Models, Genetic|Multigene Family|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/bts386', '22962460', 'Gene duplication (D), transfer (T), loss (L) and incomplete lineage sorting (I) are crucial to the evolution of gene families and the emergence of novel functions. The history of these events can be inferred via comparison of gene and species trees, a process called reconciliation, yet current reconciliation algorithms model only a subset of these evolutionary processes.'),
(77188, 2012, 'bio', 'Multiple instance learning of Calmodulin binding sites', 'Minhas, Fayyaz ul Amir Afsar|Ben-Hur, Asa', 'Department of Computer Science, Colorado State University, Fort Collins, CO 80523-1873, USA.|Department of Computer Science, Colorado State University, Fort Collins, CO 80523-1873, USA.', 'United States|United States', 0, 'Arabidopsis Proteins|Binding Sites|Calmodulin|Calmodulin-Binding Proteins|Protein Interaction Domains and Motifs|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts416', '22962461', 'Calmodulin (CaM) is a ubiquitously conserved protein that acts as a calcium sensor, and interacts with a large number of proteins. Detection of CaM binding proteins and their interaction sites experimentally requires a significant effort, so accurate methods for their prediction are important.'),
(77189, 2012, 'bio', 'Side-chain rotamer changes upon ligand binding: common, crucial, correlate with entropy and rearrange hydrogen bonding', 'Gaudreault, Francis|Chartier, Matthieu|Najmanovich, Rafael', 'Department of Biochemistry, Université de Sherbrooke, 3001, Québec, Canada J1H 5N4.|Department of Biochemistry, Université de Sherbrooke, 3001, Québec, Canada J1H 5N4.|Department of Biochemistry, Université de Sherbrooke, 3001, Québec, Canada J1H 5N4.', 'Canada|Canada|Canada', 0, 'Amino Acids|Binding Sites|Databases, Protein|Entropy|Hydrogen Bonding|Ligands|Protein Binding|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/bts395', '22962462', 'Protein movements form a continuum from large domain rearrangements (including folding and restructuring) to side-chain rotamer changes and small rearrangements. Understanding side-chain flexibility upon binding is important to understand molecular recognition events and predict ligand binding.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77190, 2012, 'bio', 'A structure-based protocol for learning the family-specific mechanisms of membrane-binding domains', 'Källberg, Morten|Bhardwaj, Nitin|Langlois, Robert|Lu, Hui', 'Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.', 'United States|United States|United States|United States', 0, 'Artificial Intelligence|Membrane Proteins|Models, Molecular|Protein Kinase C-delta|Protein Sorting Signals|Protein Structure, Tertiary|Static Electricity', 'Journal Article', '10.1093/bioinformatics/bts409', '22962463', 'Peripheral membrane-targeting domain (MTD) families, such as C1-, C2- and PH domains, play a key role in signal transduction and membrane trafficking by dynamically translocating their parent proteins to specific plasma membranes when changes in lipid composition occur. It is, however, difficult to determine the subset of domains within families displaying this property, as sequence motifs signifying the membrane binding properties are not well defined. For this reason, procedures based on sequence similarity alone are often insufficient in computational identification of MTDs within families (yielding less than 65% accuracy even with a sequence identity of 70%).'),
(77191, 2012, 'bio', 'SANS: high-throughput retrieval of protein sequences allowing 50% mismatches', 'Koskinen, J Patrik|Holm, Liisa', 'Department of Biosciences, Division of Genetics. University of Helsinki, 00014 Helsinki, Finland.|Department of Biosciences, Division of Genetics. University of Helsinki, 00014 Helsinki, Finland.', 'Finland|Finland', 12, 'Algorithms|Bacterial Proteins|Databases, Protein|Genome|Metagenome|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/bts417', '22962464', 'The genomic era in molecular biology has brought on a rapidly widening gap between the amount of sequence data and first-hand experimental characterization of proteins. Fortunately, the theory of evolution provides a simple solution: functional and structural information can be transferred between homologous proteins. Sequence similarity searching followed by k-nearest neighbor classification is the most widely used tool to predict the function or structure of anonymous gene products that come out of genome sequencing projects.'),
(77192, 2012, 'bio', 'Protein domain recurrence and order can enhance prediction of protein functions', 'Messih, Mario Abdel|Chitale, Meghana|Bajic, Vladimir B|Kihara, Daisuke|Gao, Xin', 'Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.|Mathematical and Computer Sciences and Engineering Division, King Abdullah University of Science and Technology, Thuwal, 23955-6900, Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia', 0, 'Bayes Theorem|Models, Statistical|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bts398', '22962465', 'Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been developed to infer the protein functions based on either the sequences or domains of proteins. The existing methods, however, ignore the recurrence and the order of the protein domains in this function inference.'),
(77193, 2012, 'bio', 'EnrichNet: network-based gene set enrichment analysis', 'Glaab, Enrico|Baudot, Anaïs|Krasnogor, Natalio|Schneider, Reinhard|Valencia, Alfonso', 'Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.|Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4362 Esch-sur-Alzette, Luxembourg.', 'Luxembourg|Luxembourg|Luxembourg|Luxembourg|Luxembourg', 170, 'Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Gene Regulatory Networks|Genes|Humans|Internet|Neoplasms|Parkinson Disease|Protein Interaction Mapping|Protein Interaction Maps|Software', 'Journal Article', '10.1093/bioinformatics/bts389', '22962466', 'Assessing functional associations between an experimentally derived gene or protein set of interest and a database of known gene/protein sets is a common task in the analysis of large-scale functional genomics data. For this purpose, a frequently used approach is to apply an over-representation-based enrichment analysis. However, this approach has four drawbacks: (i) it can only score functional associations of overlapping gene/proteins sets, (ii) it disregards genes with missing annotations, (iii) it does not take into account the network structure of physical interactions between the gene/protein sets of interest and (iv) tissue-specific gene/protein set associations cannot be recognized.'),
(77194, 2012, 'bio', 'LocTree2 predicts localization for all domains of life', 'Goldberg, Tatyana|Hamp, Tobias|Rost, Burkhard', 'TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany. localization@rostlab.org|TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany. localization@rostlab.org|TUM, Bioinformatik-I12, Informatik, Boltzmannstrasse 3, Garching 85748, Germany. localization@rostlab.org', 'Germany|Germany|Germany', 66, 'Animals|Archaeal Proteins|Bacterial Proteins|Membrane Proteins|Molecular Sequence Annotation|Proteins|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/bts390', '22962467', 'Subcellular localization is one aspect of protein function. Despite advances in high-throughput imaging, localization maps remain incomplete. Several methods accurately predict localization, but many challenges remain to be tackled.'),
(77195, 2012, 'bio', 'Techniques to cope with missing data in host-pathogen protein interaction prediction', 'Kshirsagar, Meghana|Carbonell, Jaime|Klein-Seetharaman, Judith', 'School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.|School of Computer Science, Carnegie Mellon University, Pittsburgh, PA 15213, USA.', 'United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Bacterial Proteins|Gene Expression|Host-Pathogen Interactions|Humans|Protein Interaction Mapping|Salmonella|Sequence Analysis, Protein|Yersinia pestis', 'Journal Article', '10.1093/bioinformatics/bts375', '22962468', 'Approaches that use supervised machine learning techniques for protein-protein interaction (PPI) prediction typically use features obtained by integrating several sources of data. Often certain attributes of the data are not available, resulting in missing values. In particular, our host-pathogen PPI datasets have a large fraction, in the range of 58-85% of missing values, which makes it challenging to apply machine learning algorithms.'),
(77196, 2012, 'bio', 'Identifying functional modules in interaction networks through overlapping Markov clustering', 'Shih, Yu-Keng|Parthasarathy, Srinivasan', 'Department of Computer Science and Engineering, the Ohio State University, Columbus, OH 43210-1277, USA.|Department of Computer Science and Engineering, the Ohio State University, Columbus, OH 43210-1277, USA.', 'United States|United States', 66, 'Algorithms|Cluster Analysis|Markov Chains|Protein Interaction Mapping|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/bts370', '22962469', 'In recent years, Markov clustering (MCL) has emerged as an effective algorithm for clustering biological networks-for instance clustering protein-protein interaction (PPI) networks to identify functional modules. However, a limitation of MCL and its variants (e.g. regularized MCL) is that it only supports hard clustering often leading to an impedance mismatch given that there is often a significant overlap of proteins across functional modules.'),
(77197, 2012, 'bio', 'Graphlet-based edge clustering reveals pathogen-interacting proteins', 'Solava, R W|Michaels, R P|Milenkovic, T', 'Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA.', 'United States|United States|United States', 41, 'Cluster Analysis|Host-Pathogen Interactions|Humans|Protein Interaction Mapping|Protein Interaction Maps|Saccharomyces cerevisiae Proteins', 'Evaluation Studies', '10.1093/bioinformatics/bts376', '22962470', 'Prediction of protein function from protein interaction networks has received attention in the post-genomic era. A popular strategy has been to cluster the network into functionally coherent groups of proteins and assign the entire cluster with a function based on functions of its annotated members. Traditionally, network research has focused on clustering of nodes. However, clustering of edges may be preferred: nodes belong to multiple functional groups, but clustering of nodes typically cannot capture the group overlap, while clustering of edges can. Clustering of adjacent edges that share many neighbors was proposed recently, outperforming different node clustering methods. However, since some biological processes can have characteristic signatures throughout the network, not just locally, it may be of interest to consider edges that are not necessarily adjacent.'),
(77198, 2012, 'bio', 'Identification of chemogenomic features from drug-target interaction networks using interpretable classifiers', 'Tabei, Yasuo|Pauwels, Edouard|Stoven, Véronique|Takemoto, Kazuhiro|Yamanishi, Yoshihiro', 'ERATO Minato Project, Japan Science and Technology Agency, Sapporo 060-0814, Japan.|ERATO Minato Project, Japan Science and Technology Agency, Sapporo 060-0814, Japan.|ERATO Minato Project, Japan Science and Technology Agency, Sapporo 060-0814, Japan.|ERATO Minato Project, Japan Science and Technology Agency, Sapporo 060-0814, Japan.|ERATO Minato Project, Japan Science and Technology Agency, Sapporo 060-0814, Japan.', 'Japan|Japan|Japan|Japan|Japan', 50, 'Algorithms|Drug Delivery Systems|Drug Design|Humans|Ligands|Linear Models|Pharmaceutical Preparations|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/bts412', '22962471', 'Drug effects are mainly caused by the interactions between drug molecules and their target proteins including primary targets and off-targets. Identification of the molecular mechanisms behind overall drug-target interactions is crucial in the drug design process.'),
(77199, 2012, 'bio', 'Boolean approach to signalling pathway modelling in HGF-induced keratinocyte migration', 'Singh, Amit|Nascimento, Juliana M|Kowar, Silke|Busch, Hauke|Boerries, Melanie', 'Freiburg Institute for Advanced Studies, LifeNet, Albert-Ludwigs-University of Freiburg, Albertstrasse 19, Freiburg, Germany.|Freiburg Institute for Advanced Studies, LifeNet, Albert-Ludwigs-University of Freiburg, Albertstrasse 19, Freiburg, Germany.|Freiburg Institute for Advanced Studies, LifeNet, Albert-Ludwigs-University of Freiburg, Albertstrasse 19, Freiburg, Germany.|Freiburg Institute for Advanced Studies, LifeNet, Albert-Ludwigs-University of Freiburg, Albertstrasse 19, Freiburg, Germany.|Freiburg Institute for Advanced Studies, LifeNet, Albert-Ludwigs-University of Freiburg, Albertstrasse 19, Freiburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 33, 'Autocrine Communication|Cell Movement|Cells, Cultured|Hepatocyte Growth Factor|Humans|Keratinocytes|Models, Biological|Proto-Oncogene Proteins c-met|Signal Transduction|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts410', '22962472', 'Cell migration is a complex process that is controlled through the time-sequential feedback regulation of protein signalling and gene regulation. Based on prior knowledge and own experimental data, we developed a large-scale dynamic network describing the onset and maintenance of hepatocyte growth factor-induced migration of primary human keratinocytes. We applied Boolean logic to capture the qualitative behaviour as well as short-and long-term dynamics of the complex signalling network involved in this process, comprising protein signalling, gene regulation and autocrine feedback.'),
(77200, 2012, 'bio', 'Stoichiometric capacitance reveals the theoretical capabilities of metabolic networks', 'Larhlimi, Abdelhalim|Basler, Georg|Grimbs, Sergio|Selbig, Joachim|Nikoloski, Zoran', 'Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de|Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de|Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de|Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de|Institute of Biochemistry and Biology, University of Potsdam, Karl-Liebknecht-Str. 24-25, D-14476 Potsdam, Germany. larhlimi@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 7, 'Bacteria|Citric Acid Cycle|Gluconeogenesis|Glycolysis|Humans|Metabolic Networks and Pathways|Models, Biological', 'Journal Article', '10.1093/bioinformatics/bts381', '22962473', 'Metabolic engineering aims at modulating the capabilities of metabolic networks by changing the activity of biochemical reactions. The existing constraint-based approaches for metabolic engineering have proven useful, but are limited only to reactions catalogued in various pathway databases.'),
(77201, 2012, 'bio', 'The architecture of the gene regulatory networks of different tissues', 'Li, Jie|Hua, Xu|Haubrock, Martin|Wang, Jin|Wingender, Edgar', 'The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Göttingen, Germany.|The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Göttingen, Germany.|The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Göttingen, Germany.|The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Göttingen, Germany.|The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, Göttingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 20, 'Data Interpretation, Statistical|Gene Expression Regulation|Gene Regulatory Networks|Humans|MicroRNAs|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts387', '22962474', 'The great variety of human cell types in morphology and function is due to the diverse gene expression profiles that are governed by the distinctive regulatory networks in different cell types. It is still a challenging task to explain how the regulatory networks achieve the diversity of different cell types. Here, we report on our studies of the design principles of the tissue regulatory system by constructing the regulatory networks of eight human tissues, which subsume the regulatory interactions between transcription factors (TFs), microRNAs (miRNAs) and non-TF target genes. The results show that there are in-/out-hubs of high in-/out-degrees in tissue networks. Some hubs (strong hubs) maintain the hub status in all the tissues where they are expressed, whereas others (weak hubs), in spite of their ubiquitous expression, are hubs only in some tissues. The network motifs are mostly feed-forward loops. Some of them having no miRNAs are the common motifs shared by all tissues, whereas the others containing miRNAs are the tissue-specific ones owned by one or several tissues, indicating that the transcriptional regulation is more conserved across tissues than the post-transcriptional regulation. In particular, a common bow-tie framework was found that underlies the motif instances and shows diverse patterns in different tissues. Such bow-tie framework reflects the utilization efficiency of the regulatory system as well as its high variability in different tissues, and could serve as the model to further understand the structural adaptation of the regulatory system to the specific requirements of different cell functions.'),
(77202, 2012, 'bio', 'Random sampling of elementary flux modes in large-scale metabolic networks', 'Machado, Daniel|Soons, Zita|Patil, Kiran Raosaheb|Ferreira, Eugénio C|Rocha, Isabel', 'IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt|IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt|IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt|IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt|IBB-Institute for Biotechnology and Bioengineering/Centre of Biological Engineering, University of Minho, Campus de Gualtar, 4710-057 Braga, Portugal. dmachado@deb.uminho.pt', 'Portugal|Portugal|Portugal|Portugal|Portugal', 39, 'Algorithms|Escherichia coli|Metabolic Networks and Pathways|Succinic Acid', 'Journal Article', '10.1093/bioinformatics/bts401', '22962475', 'The description of a metabolic network in terms of elementary (flux) modes (EMs) provides an important framework for metabolic pathway analysis. However, their application to large networks has been hampered by the combinatorial explosion in the number of modes. In this work, we develop a method for generating random samples of EMs without computing the whole set.'),
(77203, 2012, 'bio', 'Relating drug-protein interaction network with drug side effects', 'Mizutani, Sayaka|Pauwels, Edouard|Stoven, Véronique|Goto, Susumu|Yamanishi, Yoshihiro', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611-0011, Japan.', 'Japan|Japan|Japan|Japan|Japan', 112, 'Drug-Related Side Effects and Adverse Reactions|Models, Statistical|Pharmaceutical Preparations|Phenotype|Proteins', 'Journal Article', '10.1093/bioinformatics/bts383', '22962476', 'Identifying the emergence and underlying mechanisms of drug side effects is a challenging task in the drug development process. This underscores the importance of system-wide approaches for linking different scales of drug actions, namely drug-protein interactions (molecular scale) and side effects (phenotypic scale) toward side effect prediction for uncharacterized drugs.'),
(77204, 2012, 'bio', 'Comprehensive estimation of input signals and dynamics in biochemical reaction networks', 'Schelker, M|Raue, A|Timmer, J|Kreutz, C', 'Institute for Physics, University of Freiburg, D-79104 Freiburg, Germany. max.schelker@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, D-79104 Freiburg, Germany. max.schelker@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, D-79104 Freiburg, Germany. max.schelker@fdm.uni-freiburg.de|Institute for Physics, University of Freiburg, D-79104 Freiburg, Germany. max.schelker@fdm.uni-freiburg.de', 'Germany|Germany|Germany|Germany', 15, 'Algorithms|Janus Kinases|Likelihood Functions|Models, Biological|STAT Transcription Factors|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bts393', '22962477', 'Cellular information processing can be described mathematically using differential equations. Often, external stimulation of cells by compounds such as drugs or hormones leading to activation has to be considered. Mathematically, the stimulus is represented by a time-dependent input function. Parameters such as rate constants of the molecular interactions are often unknown and need to be estimated from experimental data, e.g. by maximum likelihood estimation. For this purpose, the input function has to be defined for all times of the integration interval. This is usually achieved by approximating the input by interpolation or smoothing of the measured data. This procedure is suboptimal since the input uncertainties are not considered in the estimation process which often leads to overoptimistic confidence intervals of the inferred parameters and the model dynamics.'),
(77205, 2012, 'bio', 'Trajectory-oriented Bayesian experiment design versus Fisher A-optimal design: an in depth comparison study', 'Weber, Patrick|Kramer, Andrei|Dingler, Clemens|Radde, Nicole', 'Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70550, Germany. patrick.weber@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70550, Germany. patrick.weber@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70550, Germany. patrick.weber@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Pfaffenwaldring 9, Stuttgart 70550, Germany. patrick.weber@ist.uni-stuttgart.de', 'Germany|Germany|Germany|Germany', 11, 'Algorithms|Bayes Theorem|Models, Biological|Research Design|Secretory Pathway|Uncertainty|trans-Golgi Network', 'Comparative Study', '10.1093/bioinformatics/bts377', '22962478', 'Experiment design strategies for biomedical models with the purpose of parameter estimation or model discrimination are in the focus of intense research. Experimental limitations such as sparse and noisy data result in unidentifiable parameters and render-related design tasks challenging problems. Often, the temporal resolution of data is a limiting factor and the amount of possible experimental interventions is finite. To address this issue, we propose a Bayesian experiment design algorithm to minimize the prediction uncertainty for a given set of experiments and compare it to traditional A-optimal design.'),
(77206, 2012, 'bio', 'REVEAL--visual eQTL analytics', 'Jäger, Günter|Battke, Florian|Nieselt, Kay', 'Integrative Transcriptomics, Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany. guenter.jaeger@uni-tuebingen.de|Integrative Transcriptomics, Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany. guenter.jaeger@uni-tuebingen.de|Integrative Transcriptomics, Center for Bioinformatics, University of Tübingen, 72076 Tübingen, Germany. guenter.jaeger@uni-tuebingen.de', 'Germany|Germany|Germany', 1, 'Computer Graphics|Gene Expression|Gene Regulatory Networks|Genetic Association Studies|Genetic Variation|Genotype|Humans|Phenotype|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/bts382', '22962479', 'The analysis of expression quantitative trait locus (eQTL) data is a challenging scientific endeavor, involving the processing of very large, heterogeneous and complex data. Typical eQTL analyses involve three types of data: sequence-based data reflecting the genotypic variations, gene expression data and meta-data describing the phenotype. Based on these, certain genotypes can be connected with specific phenotypic outcomes to infer causal associations of genetic variation, expression and disease. To this end, statistical methods are used to find significant associations between single nucleotide polymorphisms (SNPs) or pairs of SNPs and gene expression. A major challenge lies in summarizing the large amount of data as well as statistical results and to generate informative, interactive visualizations.'),
(77207, 2012, 'bio', 'Hybrid spatial Gillespie and particle tracking simulation', 'Klann, Michael|Ganguly, Arnab|Koeppl, Heinz', 'BISON Group, Automatic Control Lab, ETH Zurich, Switzerland.|BISON Group, Automatic Control Lab, ETH Zurich, Switzerland.|BISON Group, Automatic Control Lab, ETH Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland', 21, 'Algorithms|Computer Simulation|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bts384', '22962480', 'Cellular signal transduction involves spatial-temporal dynamics and often stochastic effects due to the low particle abundance of some molecular species. Others can, however, be of high abundances. Such a system can be simulated either with the spatial Gillespie/Stochastic Simulation Algorithm (SSA) or Brownian/Smoluchowski dynamics if space and stochasticity are important. To combine the accuracy of particle-based methods with the superior performance of the SSA, we suggest a hybrid simulation.'),
(77208, 2012, 'bio', 'Imaging, quantification and visualization of spatio-temporal patterning in mESC colonies under different culture conditions', 'Scherf, N|Herberg, M|Thierbach, K|Zerjatke, T|Kalkan, T|Humphreys, P|Smith, A|Glauche, I|Roeder, I', 'Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de|Institute for Medical Informatics and Biometry, Medical Faculty Carl Gustav Carus, Dresden University of Technology, Fetscherstrasse 74, D-01307 Dresden, Germany. nico.scherf@tu-dresden.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|Cell Culture Techniques|Cells, Cultured|Embryonic Stem Cells|Image Processing, Computer-Assisted|Mice|Microscopy, Phase-Contrast|Time-Lapse Imaging', 'Journal Article', '10.1093/bioinformatics/bts404', '22962481', 'Mouse embryonic stem cells (mESCs) have developed into a prime system to study the regulation of pluripotency in stable cell lines. It is well recognized that different, established protocols for the maintenance of mESC pluripotency support morphologically and functionally different cell cultures. However, it is unclear how characteristic properties of cell colonies develop over time and how they are re-established after cell passage depending on the culture conditions. Furthermore, it appears that cell colonies have an internal structure with respect to cell size, marker expression or biomechanical properties, which is not sufficiently understood. The analysis of these phenotypic properties is essential for a comprehensive understanding of mESC development and ultimately requires a bioinformatics approach to guarantee reproducibility and high-throughput data analysis.'),
(77209, 2012, 'bio', 'An approach to describing and analysing bulk biological annotation quality: a case study using UniProtKB', 'Bell, Michael J|Gillespie, Colin S|Swan, Daniel|Lord, Phillip', 'School of Computing Science, Newcastle University, Newcastle-Upon-Tyne, NE1 7RU, UK.|School of Computing Science, Newcastle University, Newcastle-Upon-Tyne, NE1 7RU, UK.|School of Computing Science, Newcastle University, Newcastle-Upon-Tyne, NE1 7RU, UK.|School of Computing Science, Newcastle University, Newcastle-Upon-Tyne, NE1 7RU, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Databases, Protein|Knowledge Bases|Molecular Sequence Annotation|Proteins', 'Journal Article', '10.1093/bioinformatics/bts372', '22962482', 'Annotations are a key feature of many biological databases, used to convey our knowledge of a sequence to the reader. Ideally, annotations are curated manually, however manual curation is costly, time consuming and requires expert knowledge and training. Given these issues and the exponential increase of data, many databases implement automated annotation pipelines in an attempt to avoid un-annotated entries. Both manual and automated annotations vary in quality between databases and annotators, making assessment of annotation reliability problematic for users. The community lacks a generic measure for determining annotation quality and correctness, which we look at addressing within this article. Specifically we investigate word reuse within bulk textual annotations and relate this to Zipfs Principle of Least Effort. We use the UniProt Knowledgebase (UniProtKB) as a case study to demonstrate this approach since it allows us to compare annotation change, both over time and between automated and manually curated annotations.'),
(77210, 2012, 'bio', 'ReLiance: a machine learning and literature-based prioritization of receptor--ligand pairings', 'Iacucci, Ernesto|Tranchevent, Léon-Charles|Popovic, Dusan|Pavlopoulos, Georgios A|De Moor, Bart|Schneider, Reinhard|Moreau, Yves', 'IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com|IBBT Future Health Department/ESAT-SCD, KU Leuven, Kasteelpark Arenberg 10, 3001, Heverlee-Leuven, Belgium. ernesto.iacucci@gmail.com', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Animals|Artificial Intelligence|Data Mining|Databases, Protein|Dogs|Humans|Ligands|Mice|Rats|Receptors, Cell Surface', 'Journal Article', '10.1093/bioinformatics/bts391', '22962483', 'The prediction of receptor-ligand pairings is an important area of research as intercellular communications are mediated by the successful interaction of these key proteins. As the exhaustive assaying of receptor-ligand pairs is impractical, a computational approach to predict pairings is necessary. We propose a workflow to carry out this interaction prediction task, using a text mining approach in conjunction with a state of the art prediction method, as well as a widely accessible and comprehensive dataset. Among several modern classifiers, random forests have been found to be the best at this prediction task. The training of this classifier was carried out using an experimentally validated dataset of Database of Ligand-Receptor Partners (DLRP) receptor-ligand pairs. New examples, co-cited with the training receptors and ligands, are then classified using the trained classifier. After applying our method, we find that we are able to successfully predict receptor-ligand pairs within the GPCR family with a balanced accuracy of 0.96. Upon further inspection, we find several supported interactions that were not present in the Database of Interacting Proteins (DIPdatabase). We have measured the balanced accuracy of our method resulting in high quality predictions stored in the available database ReLiance.'),
(77211, 2012, 'bio', 'Event extraction across multiple levels of biological organization', 'Pyysalo, Sampo|Ohta, Tomoko|Miwa, Makoto|Cho, Han-Cheol|Tsujii, Junichi|Ananiadou, Sophia', 'National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk|National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk|National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk|National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk|National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk|National Centre for Text Mining and School of Computer Science, University of Manchester, Manchester, UK. pyysalos@cs.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Data Mining|Humans|Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts407', '22962484', 'Event extraction using expressive structured representations has been a significant focus of recent efforts in biomedical information extraction. However, event extraction resources and methods have so far focused almost exclusively on molecular-level entities and processes, limiting their applicability.'),
(77212, 2012, 'bio', 'Gene-gene interaction analysis for the survival phenotype based on the Cox model', 'Lee, Seungyeoun|Kwon, Min-Seok|Oh, Jung Mi|Park, Taesung', 'Department of Mathematics and Statistics, Sejong University, Seoul 143-747, Korea. leesy@sejong.ac.kr|Department of Mathematics and Statistics, Sejong University, Seoul 143-747, Korea. leesy@sejong.ac.kr|Department of Mathematics and Statistics, Sejong University, Seoul 143-747, Korea. leesy@sejong.ac.kr|Department of Mathematics and Statistics, Sejong University, Seoul 143-747, Korea. leesy@sejong.ac.kr', '-|-|-|-', 24, 'Algorithms|Female|Gene Frequency|Genome-Wide Association Study|Genotype|Humans|Leukemia, Myeloid, Acute|Male|Models, Genetic|Multifactor Dimensionality Reduction|Phenotype|Polymorphism, Single Nucleotide|Proportional Hazards Models', 'Journal Article', '10.1093/bioinformatics/bts415', '22962485', 'For the past few decades, many statistical methods in genome-wide association studies (GWAS) have been developed to identify SNP-SNP interactions for case-control studies. However, there has been less work for prospective cohort studies, involving the survival time. Recently, Gui et al. (2011) proposed a novel method, called Surv-MDR, for detecting gene-gene interactions associated with survival time. Surv-MDR is an extension of the multifactor dimensionality reduction (MDR) method to the survival phenotype by using the log-rank test for defining a binary attribute. However, the Surv-MDR method has some drawbacks in the sense that it needs more intensive computations and does not allow for a covariate adjustment. In this article, we propose a new approach, called Cox-MDR, which is an extension of the generalized multifactor dimensionality reduction (GMDR) to the survival phenotype by using a martingale residual as a score to classify multi-level genotypes as high- and low-risk groups. The advantages of Cox-MDR over Surv-MDR are to allow for the effects of discrete and quantitative covariates in the frame of Cox regression model and to require less computation than Surv-MDR.'),
(77213, 2012, 'bio', 'Improving HIV coreceptor usage prediction in the clinic using hints from next-generation sequencing data', 'Pfeifer, Nico|Lengauer, Thomas', 'Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Campus E1 4, 66123 Saarbrücken, Germany. nico.pfeifer@mpi-inf.mpg.de|Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Campus E1 4, 66123 Saarbrücken, Germany. nico.pfeifer@mpi-inf.mpg.de', 'Germany|Germany', 13, 'Anti-HIV Agents|CD4-Positive T-Lymphocytes|HIV Infections|High-Throughput Nucleotide Sequencing|Humans|Receptors, HIV|Sequence Analysis, DNA|Sequence Analysis, Protein|Viral Load|Virus Internalization|env Gene Products, Human Immunodeficiency Virus', 'Evaluation Studies', '10.1093/bioinformatics/bts373', '22962486', 'Due to the high mutation rate of human immunodeficiency virus (HIV), drug-resistant-variants emerge frequently. Therefore, researchers are constantly searching for new ways to attack the virus. One new class of anti-HIV drugs is the class of coreceptor antagonists that block cell entry by occupying a coreceptor on CD4 cells. This type of drug just has an effect on the subset of HIVs that use the inhibited coreceptor. A good prediction of whether the viral population inside a patient is susceptible to the treatment is hence very important for therapy decisions and pre-requisite to administering the respective drug. The first prediction models were based on data from Sanger sequencing of the V3 loop of HIV. Recently, a method based on next-generation sequencing (NGS) data was introduced that predicts labels for each read separately and decides on the patient label through a percentage threshold for the resistant viral minority.'),
(77214, 2012, 'bio', 'An accurate paired sample test for count data', 'Pham, Thang V|Jimenez, Connie R', 'OncoProteomics Laboratory, Department of Medical Oncology, VU University Medical Center De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. t.pham@vumc.nl|OncoProteomics Laboratory, Department of Medical Oncology, VU University Medical Center De Boelelaan 1117, 1081 HV Amsterdam, The Netherlands. t.pham@vumc.nl', 'Netherlands|Netherlands', 37, 'Binomial Distribution|Genomics|Humans|Models, Statistical|Neoplasms|Poisson Distribution|Proteomics', 'Journal Article', '10.1093/bioinformatics/bts394', '22962487', 'Recent technology platforms in proteomics and genomics produce count data for quantitative analysis. Previous works on statistical significance analysis for count data have mainly focused on the independent sample setting, which does not cover the case where pairs of measurements are taken from individual patients before and after treatment. This experimental setting requires paired sample testing such as the paired t-test often used for continuous measurements. A state-of-the-art method uses a negative binomial distribution in a generalized linear model framework for paired sample testing. A paired sample design assumes that the relative change within each pair is constant across biological samples. This model can be used as an approximation to the true model in cases of heterogeneity of response in complex biological systems. We aim to specify the variation in response explicitly in combination with the inherent technical variation.'),
(77215, 2012, 'bio', 'Bayesian assignment of gene ontology terms to gene expression experiments', 'Sykacek, P', 'Department of Biotechnology, BOKU University, Muthgasse 18, 1190 Vienna. peter.sykacek@boku.ac.at', '-', 3, 'Algorithms|Animals|Apoptosis|Bayes Theorem|Cell Differentiation|Endothelial Cells|Female|Gene Expression Profiling|Genes|Heat-Shock Response|Mammary Glands, Animal|Models, Statistical|Oligonucleotide Array Sequence Analysis|Probability|Saccharomyces cerevisiae|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts405', '22962488', 'Gene expression assays allow for genome scale analyses of molecular biological mechanisms. State-of-the-art data analysis provides lists of involved genes, either by calculating significance levels of mRNA abundance or by Bayesian assessments of gene activity. A common problem of such approaches is the difficulty of interpreting the biological implication of the resulting gene lists. This lead to an increased interest in methods for inferring high-level biological information. A common approach for representing high level information is by inferring gene ontology (GO) terms which may be attributed to the expression data experiment.'),
(77216, 2012, 'bio', 'Drug target prediction using adverse event report systems: a pharmacogenomic approach', 'Takarabe, Masataka|Kotera, Masaaki|Nishimura, Yosuke|Goto, Susumu|Yamanishi, Yoshihiro', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.', 'Japan|Japan|Japan|Japan|Japan', 79, 'Adverse Drug Reaction Reporting Systems|Drug-Related Side Effects and Adverse Reactions|Genomics|Humans|Pharmaceutical Preparations|Pharmacogenetics|Proteins|United States|United States Food and Drug Administration', 'Evaluation Studies', '10.1093/bioinformatics/bts413', '22962489', 'Unexpected drug activities derived from off-targets are usually undesired and harmful, however, they can occasionally be beneficial for different therapeutic indications. There are many uncharacterized drugs whose target proteins (including the primary target and off-targets) remain unknown. The identification of all potential drug targets has become an important issue in drug repositioning to reuse known drugs for new therapeutic indications.'),
(77217, 2012, 'bio', 'From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimers disease relevant SNPs', 'Wang, Hua|Nie, Feiping|Huang, Heng|Yan, Jingwen|Kim, Sungeun|Nho, Kwangsik|Risacher, Shannon L|Saykin, Andrew J|Shen, Li|Alzheimers Disease Neuroimaging Initiative', 'Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.|Department of Computer Science and Engineering, University of Texas at Arlington, TX 76019, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 38, 'Algorithms|Alzheimer Disease|Genetic Association Studies|Genotype|Humans|Phenotype|Polymorphism, Single Nucleotide|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/bts411', '22962490', 'Imaging genetic studies typically focus on identifying single-nucleotide polymorphism (SNP) markers associated with imaging phenotypes. Few studies perform regression of SNP values on phenotypic measures for examining how the SNP values change when phenotypic measures are varied. This alternative approach may have a potential to help us discover important imaging genetic associations from a different perspective. In addition, the imaging markers are often measured over time, and this longitudinal profile may provide increased power for differentiating genotype groups. How to identify the longitudinal phenotypic markers associated to disease sensitive SNPs is an important and challenging research topic.'),
(77218, 2012, 'bio', 'A novel approach for resolving differences in single-cell gene expression patterns from zygote to blastocyst', 'Buettner, Florian|Theis, Fabian J', 'Institute of Bioinformatics and Systems Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany. f.buettner@helmholtz-muenchen.de|Institute of Bioinformatics and Systems Biology, Helmholtz-Zentrum München, 85764 Neuherberg, Germany. f.buettner@helmholtz-muenchen.de', 'Germany|Germany', 0, 'Animals|Blastocyst|Cell Differentiation|Gene Expression|Gene Expression Profiling|Gene Expression Regulation, Developmental|Mice|Principal Component Analysis|Single-Cell Analysis|Zygote', 'Journal Article', '10.1093/bioinformatics/bts385', '22962491', 'Single-cell experiments of cells from the early mouse embryo yield gene expression data for different developmental stages from zygote to blastocyst. To better understand cell fate decisions during differentiation, it is desirable to analyse the high-dimensional gene expression data and assess differences in gene expression patterns between different developmental stages as well as within developmental stages. Conventional methods include univariate analyses of distributions of genes at different stages or multivariate linear methods such as principal component analysis (PCA). However, these approaches often fail to resolve important differences as each lineage has a unique gene expression pattern which changes gradually over time yielding different gene expressions both between different developmental stages as well as heterogeneous distributions at a specific stage. Furthermore, to date, no approach taking the temporal structure of the data into account has been presented.'),
(77219, 2012, 'bio', 'Finding differentially expressed regions of arbitrary length in quantitative genomic data based on marked point process model', 'Hatsuda, Hiroshi', 'Department of Statistics, the University of Warwick, Coventry CV4 7AL, UK. H.Hatsuda@warwick.ac.uk', 'United Kingdom', 1, 'Algorithms|Animals|Drosophila melanogaster|Gene Expression Profiling|Genomics|High-Throughput Nucleotide Sequencing|Models, Genetic|Models, Statistical|Monte Carlo Method|RNA', 'Evaluation Studies', '10.1093/bioinformatics/bts371', '22962492', 'High-throughput nucleotide sequencing technologies provide large amounts of quantitative genomic data at nucleotide resolution, which are important for the present and future biomedical researches, for example differential analysis of base-level RNA expression data will improve our understanding of transcriptome, including both coding and non-coding genes. However, most studies of these data have relied on existing genome annotations and thus are limited to the analysis of known transcripts.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77220, 2012, 'bio', 'PARADIGM-SHIFT predicts the function of mutations in multiple cancers using pathway impact analysis', 'Ng, Sam|Collisson, Eric A|Sokolov, Artem|Goldstein, Theodore|Gonzalez-Perez, Abel|Lopez-Bigas, Nuria|Benz, Christopher|Haussler, David|Stuart, Joshua M', 'Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.|Department of Biomolecular Engineering and CBSE, University of California Santa Cruz, Santa Cruz, CA 95064, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 69, 'Algorithms|Gene Expression|Genes, Neoplasm|Genes, p53|Humans|Mutation|NF-E2-Related Factor 2|Neoplasms|Retinoblastoma Protein', 'Journal Article', '10.1093/bioinformatics/bts402', '22962493', 'A current challenge in understanding cancer processes is to pinpoint which mutations influence the onset and progression of disease. Toward this goal, we describe a method called PARADIGM-SHIFT that can predict whether a mutational event is neutral, gain-or loss-of-function in a tumor sample. The method uses a belief-propagation algorithm to infer gene activity from gene expression and copy number data in the context of a set of pathway interactions.'),
(77221, 2012, 'bio', 'VarB: a variation browsing and analysis tool for variants derived from next-generation sequencing data', 'Preston, Mark D|Manske, Magnus|Horner, Neil|Assefa, Samuel|Campino, Susana|Auburn, Sarah|Zongo, Issaka|Ouedraogo, Jean-Bosco|Nosten, Francois|Anderson, Tim|Clark, Taane G', 'Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.|Faculties of Epidemiology & Population Health and Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Genetic Variation|Genome, Protozoan|High-Throughput Nucleotide Sequencing|INDEL Mutation|Plasmodium falciparum|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts557', '22976080', 'There is an immediate need for tools to both analyse and visualize in real-time single-nucleotide polymorphisms, insertions and deletions, and other structural variants from new sequence file formats. We have developed VarB software that can be used to visualize variant call format files in real time, as well as identify regions under balancing selection and informative markers to differentiate user-defined groups (e.g. populations). We demonstrate its utility using sequence data from 50 Plasmodium falciparum isolates comprising two different continents and confirm known signals from genomic regions that contain important antigenic and anti-malarial drug-resistance genes.'),
(77222, 2012, 'bio', 'Phylogenetics, likelihood, evolution and complexity', 'de Koning, A P Jason|Gu, Wanjun|Castoe, Todd A|Pollock, David D', 'Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Aurora, CO 80045, USA.|Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Aurora, CO 80045, USA.|Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Aurora, CO 80045, USA.|Department of Biochemistry and Molecular Genetics, School of Medicine, University of Colorado, Aurora, CO 80045, USA.', 'United States|United States|United States|United States', 4, 'Algorithms|Animals|Bayes Theorem|Biological Evolution|Markov Chains|Monte Carlo Method|Phylogeny|Probability|Software', 'Journal Article', '10.1093/bioinformatics/bts555', '22976081', 'Phylogenetics, likelihood, evolution and complexity (PLEX) is a flexible and fast Bayesian Markov chain Monte Carlo software program for large-scale analysis of nucleotide and amino acid data using complex evolutionary models in a phylogenetic framework. The program gains large speed improvements over standard approaches by implementing partial sampling of substitution histories, a data augmentation approach that can reduce data analysis times from months to minutes on large comparative datasets. A variety of nucleotide and amino acid substitution models are currently implemented, including non-reversible and site-heterogeneous mixture models. Due to efficient algorithms that scale well with data size and model complexity, PLEX can be used to make inferences from hundreds to thousands of taxa in only minutes on a desktop computer. It also performs probabilistic ancestral sequence reconstruction. Future versions will support detection of co-evolutionary interactions between sites, probabilistic tests of convergent evolution and rigorous testing of evolutionary hypotheses in a Bayesian framework.'),
(77223, 2012, 'bio', 'An RNA Mapping DataBase for curating RNA structure mapping experiments', 'Cordero, Pablo|Lucks, Julius B|Das, Rhiju', 'Department of Biochemistry and Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA.|Department of Biochemistry and Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA.|Department of Biochemistry and Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA.', 'United States|United States|United States', 49, 'Algorithms|Base Sequence|Computers|Databases, Nucleic Acid|Nucleic Acid Conformation|RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts554', '22976082', 'We have established an RNA mapping database (RMDB) to enable structural, thermodynamic and kinetic comparisons across single-nucleotide-resolution RNA structure mapping experiments. The volume of structure mapping data has greatly increased since the development of high-throughput sequencing techniques, accelerated software pipelines and large-scale mutagenesis. For scientists wishing to infer relationships between RNA sequence/structure and these mapping data, there is a need for a database that is curated, tagged with error estimates and interfaced with tools for sharing, visualization, search and meta-analysis. Through its on-line front-end, the RMDB allows users to explore single-nucleotide-resolution mapping data in heat-map, bar-graph and colored secondary structure graphics, to leverage these data to generate secondary structure hypotheses, and to download the data in standardized and computer-friendly files, including the RDAT and community-consensus SNRNASM formats. At the time of writing, the database houses 53 entries, describing more than 2848 experiments of 1098 RNA constructs in several solution conditions and is growing rapidly.'),
(77224, 2012, 'bio', 'Extra-binomial variation approach for analysis of pooled DNA sequencing data', 'Yang, Xin|Todd, John A|Clayton, David|Wallace, Chris', 'Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrookes Hospital, Cambridge CB2 0XY, UK.|Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrookes Hospital, Cambridge CB2 0XY, UK.|Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrookes Hospital, Cambridge CB2 0XY, UK.|Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory, Department of Medical Genetics, Cambridge Institute for Medical Research, University of Cambridge, Wellcome Trust/MRC Building, Addenbrookes Hospital, Cambridge CB2 0XY, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 4, 'Diabetes Mellitus, Type 1|Humans|Models, Statistical|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts553', '22976083', 'The invention of next-generation sequencing technology has made it possible to study the rare variants that are more likely to pinpoint causal disease genes. To make such experiments financially viable, DNA samples from several subjects are often pooled before sequencing. This induces large between-pool variation which, together with other sources of experimental error, creates over-dispersed data. Statistical analysis of pooled sequencing data needs to appropriately model this additional variance to avoid inflating the false-positive rate.'),
(77225, 2012, 'bio', 'NetworkView: 3D display and analysis of protein·RNA interaction networks', 'Eargle, John|Luthey-Schulten, Zaida', 'Department of Chemistry, University of Illinois at Urbana-Champaign, 505 South Mathews Avenue Urbana, IL 61801, USA.|Department of Chemistry, University of Illinois at Urbana-Champaign, 505 South Mathews Avenue Urbana, IL 61801, USA.', 'United States|United States', 83, 'Molecular Dynamics Simulation|RNA|RNA-Binding Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts546', '22982572', 'NetworkView is an application for the display and analysis of protein·RNA interaction networks derived from structure and/or dynamics. These networks typically model individual protein residues and nucleic acid monomers as nodes and their pairwise contacts as edges with associated weights. NetworkView projects the network onto the underlying 3D molecular structure so that visualization and analysis of the network can be coupled to physical and biological properties. NetworkView is implemented as a plugin to the molecular visualization software VMD.'),
(77226, 2012, 'bio', 'DLRS: gene tree evolution in light of a species tree', 'Sjöstrand, Joel|Sennblad, Bengt|Arvestad, Lars|Lagergren, Jens', 'Science for Life Laboratory, Stockholm University, SE-17121, Solna, Sweden. joel.sjostrand@scilifelab.se|Science for Life Laboratory, Stockholm University, SE-17121, Solna, Sweden. joel.sjostrand@scilifelab.se|Science for Life Laboratory, Stockholm University, SE-17121, Solna, Sweden. joel.sjostrand@scilifelab.se|Science for Life Laboratory, Stockholm University, SE-17121, Solna, Sweden. joel.sjostrand@scilifelab.se', 'Sweden|Sweden|Sweden|Sweden', 26, 'Algorithms|Animals|Bayes Theorem|Evolution, Molecular|Models, Statistical|Phylogeny|Programming Languages|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts548', '22982573', 'PrIME-DLRS (or colloquially: Delirious) is a phylogenetic software tool to simultaneously infer and reconcile a gene tree given a species tree. It accounts for duplication and loss events, a relaxed molecular clock and is intended for the study of homologous gene families, for example in a comparative genomics setting involving multiple species. PrIME-DLRS uses a Bayesian MCMC framework, where the input is a known species tree with divergence times and a multiple sequence alignment, and the output is a posterior distribution over gene trees and model parameters.'),
(77227, 2012, 'bio', 'Efficient methods for identifying mutated driver pathways in cancer', 'Zhao, Junfei|Zhang, Shihua|Wu, Ling-Yun|Zhang, Xiang-Sun', 'National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.|National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.|National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.|National Center for Mathematics and Interdisciplinary Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China.', 'China|China|China|China', 92, 'Algorithms|DNA Mutational Analysis|Gene Expression Profiling|Genomics|Humans|Models, Genetic|Mutation|Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts564', '22982574', 'The first step for clinical diagnostics, prognostics and targeted therapeutics of cancer is to comprehensively understand its molecular mechanisms. Large-scale cancer genomics projects are providing a large volume of data about genomic, epigenomic and gene expression aberrations in multiple cancer types. One of the remaining challenges is to identify driver mutations, driver genes and driver pathways promoting cancer proliferation and filter out the unfunctional and passenger ones.'),
(77228, 2012, 'bio', 'MeDIP-HMM: genome-wide identification of distinct DNA methylation states from high-density tiling arrays', 'Seifert, Michael|Cortijo, Sandra|Colomé-Tatché, Maria|Johannes, Frank|Roudier, François|Colot, Vincent', 'Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de|Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de|Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de|Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de|Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de|Department of Molecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research-IPK, Gatersleben, Germany. seifert@ipk-gatersleben.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Arabidopsis|Bayes Theorem|DNA Methylation|Epigenesis, Genetic|Genome-Wide Association Study|Genomics|Immunoprecipitation|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/bts562', '22989518', 'Methylation of cytosines in DNA is an important epigenetic mechanism involved in transcriptional regulation and preservation of genome integrity in a wide range of eukaryotes. Immunoprecipitation of methylated DNA followed by hybridization to genomic tiling arrays (MeDIP-chip) is a cost-effective and sensitive method for methylome analyses. However, existing bioinformatics methods only enable a binary classification into unmethylated and methylated genomic regions, which limit biological interpretations. Indeed, DNA methylation levels can vary substantially within a given DNA fragment depending on the number and degree of methylated cytosines. Therefore, a method for the identification of more than two methylation states is highly desirable.'),
(77229, 2012, 'bio', 'integIRTy: a method to identify genes altered in cancer by accounting for multiple mechanisms of regulation using item response theory', 'Tong, Pan|Coombes, Kevin R', 'Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX, USA.', 'United States|United States', 4, 'Breast Neoplasms|Computer Simulation|Female|Gene Expression Profiling|Glioblastoma|High-Throughput Nucleotide Sequencing|Humans|Models, Genetic|Mutation|Ovarian Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts561', '23014630', 'Identifying genes altered in cancer plays a crucial role in both understanding the mechanism of carcinogenesis and developing novel therapeutics. It is known that there are various mechanisms of regulation that can lead to gene dysfunction, including copy number change, methylation, abnormal expression, mutation and so on. Nowadays, all these types of alterations can be simultaneously interrogated by different types of assays. Although many methods have been proposed to identify altered genes from a single assay, there is no method that can deal with multiple assays accounting for different alteration types systematically.'),
(77230, 2012, 'bio', 'SGNS2: a compartmentalized stochastic chemical kinetics simulator for dynamic cell populations', 'Lloyd-Price, Jason|Gupta, Abhishekh|Ribeiro, Andre S', 'Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland. jason.lloyd-price@tut.fi|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland. jason.lloyd-price@tut.fi|Department of Signal Processing, Tampere University of Technology, 33101 Tampere, Finland. jason.lloyd-price@tut.fi', 'Finland|Finland|Finland', 18, 'Algorithms|Bacteriophages|Cell Division|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression|Genetic Variation|Kinetics|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bts556', '23014631', 'Cell growth and division affect the kinetics of internal cellular processes and the phenotype diversity of cell populations. Since the effects are complex, e.g. different cellular components are partitioned differently in cell division, to account for them in silico, one needs to simulate these processes in great detail.'),
(77231, 2012, 'bio', 'SpolPred: rapid and accurate prediction of Mycobacterium tuberculosis spoligotypes from short genomic sequences', 'Coll, Francesc|Mallard, Kim|Preston, Mark D|Bentley, Stephen|Parkhill, Julian|McNerney, Ruth|Martin, Nigel|Clark, Taane G', 'Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk|Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London, UK. francesc.coll@lshtm.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Bacterial Typing Techniques|Genome, Bacterial|Genotype|Humans|Mycobacterium tuberculosis|Phylogeny|Software|Tuberculosis', 'Journal Article', '10.1093/bioinformatics/bts544', '23014632', 'Spoligotyping is a well-established genotyping technique based on the presence of unique DNA sequences in Mycobacterium tuberculosis (Mtb), the causal agent of tuberculosis disease (TB). Although advances in sequencing technologies are leading to whole-genome bacterial characterization, tens of thousands of isolates have been spoligotyped, giving a global view of Mtb strain diversity. To bridge the gap, we have developed SpolPred, a software to predict the spoligotype from raw sequence reads. Our approach is compared with experimentally and de novo assembly determined strain types in a set of 44 Mtb isolates. In silico and experimental results are identical for almost all isolates (39/44). However, SpolPred detected five experimentally false spoligotypes and was more accurate and faster than the assembling strategy. Application of SpolPred to an additional seven isolates with no laboratory data led to types that clustered with identical experimental types in a phylogenetic analysis using single-nucleotide polymorphisms. Our results demonstrate the usefulness of the tool and its role in revealing experimental limitations.'),
(77232, 2012, 'bio', 'Advanced complex trait analysis', 'Gray, A|Stewart, I|Tenesa, A', 'EPCC, The University of Edinburgh, Edinburgh EH9 3JZ, UK. a.gray@ed.ac.uk|EPCC, The University of Edinburgh, Edinburgh EH9 3JZ, UK. a.gray@ed.ac.uk|EPCC, The University of Edinburgh, Edinburgh EH9 3JZ, UK. a.gray@ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computational Biology|Genotype|Humans|Likelihood Functions|Linear Models|Phenotype|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts571', '23023980', 'The Genome-wide Complex Trait Analysis (GCTA) software package can quantify the contribution of genetic variation to phenotypic variation for complex traits. However, as those datasets of interest continue to increase in size, GCTA becomes increasingly computationally prohibitive. We present an adapted version, Advanced Complex Trait Analysis (ACTA), demonstrating dramatically improved performance.'),
(77233, 2012, 'bio', 'FeatureStack: Perl module for comparative visualization of gene features', 'Frech, Christian|Choo, Caleb|Chen, Nansheng', 'Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6.|Department of Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, British Columbia, Canada V5A 1S6.', 'Canada|Canada|Canada', 0, 'Computer Graphics|Exons|Genes|Introns|Protein Interaction Domains and Motifs|Proteins|Regulatory Elements, Transcriptional|Software', 'Journal Article', '10.1093/bioinformatics/bts572', '23023981', 'FeatureStack is a Perl module for the automatic generation of multi-gene images. FeatureStack takes BioPerl-compliant gene or transcript features as input and renders them side by side using a user-defined BioPerl glyph. Output images can be generated in SVG or PNG format. FeatureStack comes with a new BioPerl glyph, decorated_gene, which can highlight protein features on top of gene models. Used in combination, FeatureStack and decorated_gene enable rapid and automated generation of annotation-rich images of stacked gene models that greatly facilitate evolutionary studies of related gene structures and gene families.'),
(77234, 2012, 'bio', 'HiCNorm: removing biases in Hi-C data via Poisson regression', 'Hu, Ming|Deng, Ke|Selvaraj, Siddarth|Qin, Zhaohui|Ren, Bing|Liu, Jun S', 'Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.|Department of Statistics, Harvard University, Cambridge, MA 02138, USA.', 'United States|United States|United States|United States|United States|United States', 120, 'Base Composition|Chromatin|Chromosome Mapping|Genomic Library|Internet|Linear Models|Reproducibility of Results|Software|Statistics, Nonparametric', 'Journal Article', '10.1093/bioinformatics/bts570', '23023982', 'We propose a parametric model, HiCNorm, to remove systematic biases in the raw Hi-C contact maps, resulting in a simple, fast, yet accurate normalization procedure. Compared with the existing Hi-C normalization method developed by Yaffe and Tanay, HiCNorm has fewer parameters, runs >1000 times faster and achieves higher reproducibility.'),
(77235, 2012, 'bio', 'Adding unaligned sequences into an existing alignment using MAFFT and LAST', 'Katoh, Kazutaka|Frith, Martin C', 'Laboratory of Systems Immunology, Immunology Frontier Research Center, Osaka University, Yamadaoka, Suita 565-0871, Japan. katoh@ifrec.osaka-u.ac.jp|Laboratory of Systems Immunology, Immunology Frontier Research Center, Osaka University, Yamadaoka, Suita 565-0871, Japan. katoh@ifrec.osaka-u.ac.jp', 'Japan|Japan', 105, 'Algorithms|Base Sequence|Computational Biology|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts578', '23023983', 'Two methods to add unaligned sequences into an existing multiple sequence alignment have been implemented as the --add and --addfragments options in the MAFFT package. The former option is a basic one and applicable only to full-length sequences, whereas the latter option is applicable even when the unaligned sequences are short and fragmentary. These methods internally infer the phylogenetic relationship among the sequences in the existing alignment and the phylogenetic positions of unaligned sequences. Benchmarks based on two independent simulations consistently suggest that the --addfragments option outperforms recent methods, PaPaRa and PAGAN, in accuracy for difficult problems and that these three methods appropriately handle easy problems.'),
(77236, 2012, 'bio', 'InterMine: a flexible data warehouse system for the integration and analysis of heterogeneous biological data', 'Smith, Richard N|Aleksic, Jelena|Butano, Daniela|Carr, Adrian|Contrino, Sergio|Hu, Fengyuan|Lyne, Mike|Lyne, Rachel|Kalderimis, Alex|Rutherford, Kim|Stepan, Radek|Sullivan, Julie|Wakeling, Matthew|Watkins, Xavier|Micklem, Gos', 'Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.|Department of Genetics, University of Cambridge, Cambridge CB2 3EH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 141, 'Algorithms|Computational Biology|Data Mining|Database Management Systems|Databases, Factual|Genomics|Internet|Programming Languages', 'Journal Article', '10.1093/bioinformatics/bts577', '23023984', 'InterMine is an open-source data warehouse system that facilitates the building of databases with complex data integration requirements and a need for a fast customizable query facility. Using InterMine, large biological databases can be created from a range of heterogeneous data sources, and the extensible data model allows for easy integration of new data types. The analysis tools include a flexible query builder, genomic region search and a library of widgets performing various statistical analyses. The results can be exported in many commonly used formats. InterMine is a fully extensible framework where developers can add new tools and functionality. Additionally, there is a comprehensive set of web services, for which client libraries are provided in five commonly used programming languages.'),
(77237, 2012, 'bio', 'Site identification in high-throughput RNA-protein interaction data', 'Uren, Philip J|Bahrami-Samani, Emad|Burns, Suzanne C|Qiao, Mei|Karginov, Fedor V|Hodges, Emily|Hannon, Gregory J|Sanford, Jeremy R|Penalva, Luiz O F|Smith, Andrew D', 'Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.|Molecular and Computational Biology, University of Southern California, Los Angeles, CA 90089, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 138, 'Base Sequence|Binding Sites|Computational Biology|HEK293 Cells|HeLa Cells|High-Throughput Nucleotide Sequencing|Humans|RNA|RNA-Binding Proteins|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts569', '23024010', 'Post-transcriptional and co-transcriptional regulation is a crucial link between genotype and phenotype. The central players are the RNA-binding proteins, and experimental technologies [such as cross-linking with immunoprecipitation- (CLIP-) and RIP-seq] for probing their activities have advanced rapidly over the course of the past decade. Statistically robust, flexible computational methods for binding site identification from high-throughput immunoprecipitation assays are largely lacking however.'),
(77238, 2012, 'bio', 'Creating reusable tools from scripts: the Galaxy Tool Factory', 'Lazarus, Ross|Kaspi, Antony|Ziemann, Mark|Galaxy Team', 'Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia. ross.lazarus@channing.harvard.edu|Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia. ross.lazarus@channing.harvard.edu|Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia. ross.lazarus@channing.harvard.edu|Baker IDI Heart and Diabetes Institute, Melbourne, Victoria 3004, Australia. ross.lazarus@channing.harvard.edu', 'Australia|Australia|Australia|Australia', 8, 'Computational Biology|Electronic Data Processing|High-Throughput Nucleotide Sequencing|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts573', '23024011', 'Galaxy is a software application supporting high-throughput biology analyses and work flows, available as a free on-line service or as source code for local deployment. New tools can be written to extend Galaxy, and these can be shared using public Galaxy Tool Shed (GTS) repositories, but converting even simple scripts into tools requires effort from a skilled developer.'),
(77239, 2012, 'bio', 'MesoRD 10: Stochastic reaction-diffusion simulations in the microscopic limit', 'Fange, David|Mahmutovic, Anel|Elf, Johan', 'Department of Cell & Molecular Biology, Science for Life Laboratory, Uppsala University, BMC Box 596, SE-751 24 Uppsala, Sweden.|Department of Cell & Molecular Biology, Science for Life Laboratory, Uppsala University, BMC Box 596, SE-751 24 Uppsala, Sweden.|Department of Cell & Molecular Biology, Science for Life Laboratory, Uppsala University, BMC Box 596, SE-751 24 Uppsala, Sweden.', 'Sweden|Sweden|Sweden', 26, 'Algorithms|Computer Simulation|Diffusion|Models, Chemical|Software|Stochastic Processes|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts584', '23044538', 'MesoRD is a tool for simulating stochastic reaction-diffusion systems as modeled by the reaction diffusion master equation. The simulated systems are defined in the Systems Biology Markup Language with additions to define compartment geometries. MesoRD 1.0 supports scale-dependent reaction rate constants and reactions between reactants in neighbouring subvolumes. These new features make it possible to construct physically consistent models of diffusion-controlled reactions also at fine spatial discretization.'),
(77240, 2012, 'bio', 'Gene set analysis for self-contained tests: complex null and specific alternative hypotheses', 'Rahmatallah, Y|Emmert-Streib, F|Glazko, G', 'Division of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. yrahmatallah@uams.edu|Division of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. yrahmatallah@uams.edu|Division of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USA. yrahmatallah@uams.edu', 'United States|United States|United States', 16, 'Computational Biology|Computer Simulation|Gene Expression Profiling|Humans|Models, Statistical|Multivariate Analysis|Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts579', '23044539', 'The analysis of differentially expressed gene sets became a routine in the analyses of gene expression data. There is a multitude of tests available, ranging from aggregation tests that summarize gene-level statistics for a gene set to true multivariate tests, accounting for intergene correlations. Most of them detect complex departures from the null hypothesis but when the null hypothesis is rejected, the specific alternative leading to the rejection is not easily identifiable.'),
(77241, 2012, 'bio', 'A novel missense-mutation-related feature extraction scheme for driver mutation identification', 'Tan, Hua|Bao, Jiguang|Zhou, Xiaobo', 'School of Mathematical Sciences, Beijing Normal University, Laboratory of Mathematics and Complex Systems, Ministry of Education, Beijing 100875, P.R. China.|School of Mathematical Sciences, Beijing Normal University, Laboratory of Mathematics and Complex Systems, Ministry of Education, Beijing 100875, P.R. China.|School of Mathematical Sciences, Beijing Normal University, Laboratory of Mathematics and Complex Systems, Ministry of Education, Beijing 100875, P.R. China.', 'China|China|China', 36, 'Algorithms|Artificial Intelligence|Humans|Mutation, Missense|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts558', '23044540', 'It becomes widely accepted that human cancer is a disease involving dynamic changes in the genome and that the missense mutations constitute the bulk of human genetic variations. A multitude of computational algorithms, especially the machine learning-based ones, has consequently been proposed to distinguish missense changes that contribute to the cancer progression (driver mutation) from those that do not (passenger mutation). However, the existing methods have multifaceted shortcomings, in the sense that they either adopt incomplete feature space or depend on protein structural databases which are usually far from integrated.'),
(77242, 2012, 'bio', 'Pinstripe: a suite of programs for integrating transcriptomic and proteomic datasets identifies novel proteins and improves differentiation of protein-coding and non-coding genes', 'Gascoigne, Dennis K|Cheetham, Seth W|Cattenoz, Pierre B|Clark, Michael B|Amaral, Paulo P|Taft, Ryan J|Wilhelm, Dagmar|Dinger, Marcel E|Mattick, John S', 'Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.|Institute for Molecular Bioscience, The University of Queensland, St Lucia, Brisbane, Queensland 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia|Australia', 47, 'Computational Biology|Databases, Protein|Exons|Gene Expression Profiling|Gene Library|Genome|Genomics|Humans|Molecular Sequence Annotation|Open Reading Frames|Proteins|Proteomics|RNA, Long Noncoding|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts582', '23044541', 'Comparing transcriptomic data with proteomic data to identify protein-coding sequences is a long-standing challenge in molecular biology, one that is exacerbated by the increasing size of high-throughput datasets. To address this challenge, and thereby to improve the quality of genome annotation and understanding of genome biology, we have developed an integrated suite of programs, called Pinstripe. We demonstrate its application, utility and discovery power using transcriptomic and proteomic data from publicly available datasets.'),
(77243, 2012, 'bio', 'VIPR HMM: a hidden Markov model for detecting recombination with microbial detection microarrays', 'Allred, Adam F|Renshaw, Hilary|Weaver, Scott|Tesh, Robert B|Wang, David', 'Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA.|Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA.|Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA.|Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA.|Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO 63110, USA.', 'United States|United States|United States|United States|United States', 3, 'Algorithms|Alphavirus|Animals|Cercopithecus aethiops|Flaviviridae|Genomics|Markov Chains|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Recombination, Genetic|Vero Cells', 'Journal Article', '10.1093/bioinformatics/bts560', '23044542', 'Current methods in diagnostic microbiology typically focus on the detection of a single genomic locus or protein in a candidate agent. The presence of the entire microbe is then inferred from this isolated result. Problematically, the presence of recombination in microbial genomes would go undetected unless other genomic loci or protein components were specifically assayed. Microarrays lend themselves well to the detection of multiple loci from a given microbe, furthermore, the inherent nature of microarrays facilitates highly parallel interrogation of multiple microbes. However, none of the existing methods for analyzing diagnostic microarray data has the capacity to specifically identify recombinant microbes. In previous work, we developed a novel algorithm, VIPR, for analyzing diagnostic microarray data.'),
(77244, 2012, 'bio', 'ncPRO-seq: a tool for annotation and profiling of ncRNAs in sRNA-seq data', 'Chen, Chong-Jian|Servant, Nicolas|Toedling, Joern|Sarazin, Alexis|Marchais, Antonin|Duvernois-Berthet, Evelyne|Cognat, Valérie|Colot, Vincent|Voinnet, Olivier|Heard, Edith|Ciaudo, Constance|Barillot, Emmanuel', 'Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr|Institut Curie, F-75248 Paris, France. bioinfo.ncproseq@curie.fr', 'France|France|France|France|France|France|France|France|France|France|France|France', 56, 'Base Sequence|Computational Biology|Internet|RNA, Small Interfering|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts587', '23044543', 'Non-coding RNA (ncRNA) PROfiling in small RNA (sRNA)-seq (ncPRO-seq) is a stand-alone, comprehensive and flexible ncRNA analysis pipeline. It can interrogate and perform detailed profiling analysis on sRNAs derived from annotated non-coding regions in miRBase, Rfam and RepeatMasker, as well as specific regions defined by users. The ncPRO-seq pipeline performs both gene-based and family-based analyses of sRNAs. It also has a module to identify regions significantly enriched with short reads, which cannot be classified under known ncRNA families, thus enabling the discovery of previously unknown ncRNA- or small interfering RNA (siRNA)-producing regions. The ncPRO-seq pipeline supports input read sequences in fastq, fasta and color space format, as well as alignment results in BAM format, meaning that sRNA raw data from the three current major platforms (Roche-454, Illumina-Solexa and Life technologies-SOLiD) can be analyzed with this pipeline. The ncPRO-seq pipeline can be used to analyze read and alignment data, based on any sequenced genome, including mammals and plants.'),
(77245, 2012, 'bio', 'KGBassembler: a karyotype-based genome assembler for Brassicaceae species', 'Ma, Chuang|Chen, Hao|Xin, Mingming|Yang, Ruolin|Wang, Xiangfeng', 'School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.|School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.|School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.|School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.|School of Plant Sciences, University of Arizona, Tucson, AZ 85721, USA.', 'United States|United States|United States|United States|United States', 7, 'Algorithms|Brassicaceae|Chromosome Painting|Computational Biology|Computer Graphics|Contig Mapping|Genome, Plant|Karyotyping|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts586', '23044544', 'The Brassicaceae family includes the most important plant model Arabidopsis thaliana and many cruciferous vegetable crops. A number of close relatives of Arabidopsis and economically important Brassica species are being sequenced with whole-genome shotgun sequencing technologies. However, de novo assembly of full chromosomes is difficult, since many non-model Brassicaceae species are lacking genetic and/or physical maps. As a unique feature for Brassicaceae, the genome of each member is composed of 24 conserved chromosomal blocks, and the arrangement of the 24 blocks can be obtained from karyotype analysis via comparative chromosome painting experiments. Taking this advantage, we developed a bioinformatic tool named KGBassembler to automatically finalize assembly of full chromosomes from contigs and/or scaffolds based on available karyotypes of Brassicaceae species.'),
(77246, 2012, 'bio', 'fRMA ST: frozen robust multiarray analysis for Affymetrix Exon and Gene ST arrays', 'McCall, Matthew N|Jaffee, Harris A|Irizarry, Rafael A', 'Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 265 Crittenden Blvd., CU 420630, Rochester, NY 14642, USA. mccallm@gmail.com|Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 265 Crittenden Blvd., CU 420630, Rochester, NY 14642, USA. mccallm@gmail.com|Department of Biostatistics and Computational Biology, University of Rochester Medical Center, 265 Crittenden Blvd., CU 420630, Rochester, NY 14642, USA. mccallm@gmail.com', 'United States|United States|United States', 24, 'Algorithms|Alternative Splicing|Computational Biology|Exons|Humans|Models, Theoretical|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Software', 'Journal Article', '10.1093/bioinformatics/bts588', '23044545', 'Frozen robust multiarray analysis (fRMA) is a single-array preprocessing algorithm that retains the advantages of multiarray algorithms and removes certain batch effects by downweighting probes that have high between-batch residual variance. Here, we extend the fRMA algorithm to two new microarray platforms--Affymetrix Human Exon and Gene 1.0 ST--by modifying the fRMA probe-level model and extending the frma package to work with oligo ExonFeatureSet and GeneFeatureSet objects.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77247, 2012, 'bio', 'miR-EdiTar: a database of predicted A-to-I edited miRNA target sites', 'Laganà, Alessandro|Paone, Alessio|Veneziano, Dario|Cascione, Luciano|Gasparini, Pierluigi|Carasi, Stefania|Russo, Francesco|Nigita, Giovanni|Macca, Valentina|Giugno, Rosalba|Pulvirenti, Alfredo|Shasha, Dennis|Ferro, Alfredo|Croce, Carlo M', 'Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.edu|Department of Molecular Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio State University, Columbus, OH, USA. alessandro.lagana@osumc.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|United States|United States', 19, 'Adenosine|Binding Sites|Databases, Genetic|Gene Expression Regulation|Humans|Inosine|Internet|MicroRNAs|Nucleic Acid Conformation|RNA Editing', 'Journal Article', '10.1093/bioinformatics/bts589', '23044546', 'A-to-I RNA editing is an important mechanism that consists of the conversion of specific adenosines into inosines in RNA molecules. Its dysregulation has been associated to several human diseases including cancer. Recent work has demonstrated a role for A-to-I editing in microRNA (miRNA)-mediated gene expression regulation. In fact, edited forms of mature miRNAs can target sets of genes that differ from the targets of their unedited forms. The specific deamination of mRNAs can generate novel binding sites in addition to potentially altering existing ones.'),
(77248, 2012, 'bio', 'Robust design of microbial strains', 'Costanza, Jole|Carapezza, Giovanni|Angione, Claudio|Lió, Pietro|Nicosia, Giuseppe', 'Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.|Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.|Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.|Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.|Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125 Catania, Italy.', 'Italy|Italy|Italy|Italy|Italy', 44, 'Algorithms|Biotechnology|Computational Biology|Escherichia coli|Gene Knockout Techniques|Metabolic Engineering|Metabolic Networks and Pathways', 'Journal Article', '10.1093/bioinformatics/bts590', '23044547', 'Metabolic engineering algorithms provide means to optimize a biological process leading to the improvement of a biotechnological interesting molecule. Therefore, it is important to understand how to act in a metabolic pathway in order to have the best results in terms of productions. In this work, we present a computational framework that searches for optimal and robust microbial strains that are able to produce target molecules. Our framework performs three tasks: it evaluates the parameter sensitivity of the microbial model, searches for the optimal genetic or fluxes design and finally calculates the robustness of the microbial strains. We are capable to combine the exploration of species, reactions, pathways and knockout parameter spaces with the Pareto-optimality principle.'),
(77249, 2012, 'bio', 'Location, Location, Location: a spatial approach for rare variant analysis and an application to a study on non-syndromic cleft lip with or without cleft palate', 'Fier, Heide|Won, Sungho|Prokopenko, Dmitry|AlChawa, Taofik|Ludwig, Kerstin U|Fimmers, Rolf|Silverman, Edwin K|Pagano, Marcello|Mangold, Elisabeth|Lange, Christoph', 'Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com|Department of Genomic Mathematics, University of Bonn, 53127, Germany. heide.fier@googlemail.com', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 16, 'Alleles|Brain|Chromosomes, Human, Pair 15|Cleft Lip|Cleft Palate|Cluster Analysis|Computer Simulation|Gene Frequency|Genome-Wide Association Study|Genotype|Humans', 'Journal Article', '10.1093/bioinformatics/bts568', '23044548', 'For the analysis of rare variants in sequence data, numerous approaches have been suggested. Fixed and flexible threshold approaches collapse the rare variant information of a genomic region into a test statistic with reduced dimensionality. Alternatively, the rare variant information can be combined in statistical frameworks that are based on suitable regression models, machine learning, etc. Although the existing approaches provide powerful tests that can incorporate information on allele frequencies and prior biological knowledge, differences in the spatial clustering of rare variants between cases and controls cannot be incorporated. Based on the assumption that deleterious variants and protective variants cluster or occur in different parts of the genomic region of interest, we propose a testing strategy for rare variants that builds on spatial cluster methodology and that guides the identification of the biological relevant segments of the region. Our approach does not require any assumption about the directions of the genetic effects.'),
(77250, 2013, 'bio', 'MGAviewer: a desktop visualization tool for analysis of metagenomics alignment data', 'Zhu, Zhengwei|Niu, Beifang|Chen, Jing|Wu, Sitao|Sun, Shulei|Li, Weizhong', 'Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States|United States|United States', 8, 'Computer Graphics|Genome|Humans|Internet|Metagenomics|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts567', '23044549', 'Numerous metagenomics projects have produced tremendous amounts of sequencing data. Aligning these sequences to reference genomes is an essential analysis in metagenomics studies. Large-scale alignment data call for intuitive and efficient visualization tool. However, current tools such as various genome browsers are highly specialized to handle intraspecies mapping results. They are not suitable for alignment data in metagenomics, which are often interspecies alignments. We have developed a web browser-based desktop application for interactively visualizing alignment data of metagenomic sequences. This viewer is easy to use on all computer systems with modern web browsers and requires no software installation.'),
(77251, 2012, 'bio', 'SemMedDB: a PubMed-scale repository of biomedical semantic predications', 'Kilicoglu, Halil|Shin, Dongwook|Fiszman, Marcelo|Rosemblat, Graciela|Rindflesch, Thomas C', 'Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. kilicogluh@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. kilicogluh@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. kilicogluh@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. kilicogluh@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. kilicogluh@mail.nih.gov', 'United States|United States|United States|United States|United States', 125, 'Algorithms|Data Mining|Databases, Factual|Humans|PubMed|Semantics|Unified Medical Language System', 'Journal Article', '10.1093/bioinformatics/bts591', '23044550', 'Effective access to the vast biomedical knowledge present in the scientific literature is challenging. Semantic relations are increasingly used in knowledge management applications supporting biomedical research to help address this challenge. We describe SemMedDB, a repository of semantic predications (subject-predicate-object triples) extracted from the entire set of PubMed citations. We propose the repository as a knowledge resource that can assist in hypothesis generation and literature-based discovery in biomedicine as well as in clinical decision-making support.'),
(77252, 2012, 'bio', 'COPE: an accurate k-mer-based pair-end reads connection tool to facilitate genome assembly', 'Liu, Binghang|Yuan, Jianying|Yiu, Siu-Ming|Li, Zhenyu|Xie, Yinlong|Chen, Yanxiang|Shi, Yujian|Zhang, Hao|Li, Yingrui|Lam, Tak-Wah|Luo, Ruibang', 'HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.|HKU-BGI BAL-Bioinformatics Algorithms and Core Technology Research Laboratory, The University of Hong Kong, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|', 96, 'Algorithms|Arabidopsis|Chromosome Mapping|Contig Mapping|Genomics|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts563', '23044551', 'The boost of next-generation sequencing technologies provides us with an unprecedented opportunity for elucidating genetic mysteries, yet the short-read length hinders us from better assembling the genome from scratch. New protocols now exist that can generate overlapping pair-end reads. By joining the 3 ends of each read pair, one is able to construct longer reads for assembling. However, effectively joining two overlapped pair-end reads remains a challenging task.'),
(77253, 2012, 'bio', 'Predicting pseudoknotted structures across two RNA sequences', 'Sperschneider, Jana|Datta, Amitava|Wise, Michael J', 'School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia. janaspe@csse.uwa.edu.au|School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia. janaspe@csse.uwa.edu.au|School of Computer Science and Software Engineering, University of Western Australia, Perth, Australia. janaspe@csse.uwa.edu.au', 'Australia|Australia|Australia', 6, 'Algorithms|Base Sequence|Computational Biology|RNA|RNA Folding|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1093/bioinformatics/bts575', '23044552', 'Laboratory RNA structure determination is demanding and costly and thus, computational structure prediction is an important task. Single sequence methods for RNA secondary structure prediction are limited by the accuracy of the underlying folding model, if a structure is supported by a family of evolutionarily related sequences, one can be more confident that the prediction is accurate. RNA pseudoknots are functional elements, which have highly conserved structures. However, few comparative structure prediction methods can handle pseudoknots due to the computational complexity.'),
(77254, 2012, 'bio', 'Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks', 'Flassig, R J|Sundmacher, K', 'Otto-von-Guericke University, Process Systems Engineering, Universitätsplatz 2, D-39106 Magdeburg, Germany. flassig@mpi-magdeburg.mpg.de|Otto-von-Guericke University, Process Systems Engineering, Universitätsplatz 2, D-39106 Magdeburg, Germany. flassig@mpi-magdeburg.mpg.de', 'Germany|Germany', 0, 'Algorithms|Computational Biology|Models, Biological|Nonlinear Dynamics|Probability|Research Design', 'Journal Article', '10.1093/bioinformatics/bts585', '23047554', 'Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs).'),
(77255, 2012, 'bio', 'An unbiased evaluation of gene prioritization tools', 'Börnigen, Daniela|Tranchevent, Léon-Charles|Bonachela-Capdevila, Francisco|Devriendt, Koenraad|De Moor, Bart|De Causmaecker, Patrick|Moreau, Yves', 'Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.|Department of Electrical Engineering, ESAT-SCD, Katholieke Universiteit Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 64, 'Databases, Genetic|Genetic Association Studies|Humans|Internet', 'Comparative Study', '10.1093/bioinformatics/bts581', '23047555', 'Gene prioritization aims at identifying the most promising candidate genes among a large pool of candidates-so as to maximize the yield and biological relevance of further downstream validation experiments and functional studies. During the past few years, several gene prioritization tools have been defined, and some of them have been implemented and made available through freely available web tools. In this study, we aim at comparing the predictive performance of eight publicly available prioritization tools on novel data. We have performed an analysis in which 42 recently reported disease-gene associations from literature are used to benchmark these tools before the underlying databases are updated.'),
(77256, 2012, 'bio', 'Global network alignment using multiscale spectral signatures', 'Patro, Rob|Kingsford, Carl', 'Center for Bioinformatics and Computational Biology, Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, College Park, MD 20742, USA. rob@cs.umd.edu|Center for Bioinformatics and Computational Biology, Institute for Advanced Computer Studies and Department of Computer Science, University of Maryland, College Park, MD 20742, USA. rob@cs.umd.edu', 'United States|United States', 0, 'Algorithms|Protein Interaction Mapping|Protein Interaction Maps|Proteins', 'Journal Article', '10.1093/bioinformatics/bts592', '23047556', 'Protein interaction networks provide an important system-level view of biological processes. One of the fundamental problems in biological network analysis is the global alignment of a pair of networks, which puts the proteins of one network into correspondence with the proteins of another network in a manner that conserves their interactions while respecting other evidence of their homology. By providing a mapping between the networks of different species, alignments can be used to inform hypotheses about the functions of unannotated proteins, the existence of unobserved interactions, the evolutionary divergence between the two species and the evolution of complexes and pathways.'),
(77257, 2012, 'bio', 'SCALCE: boosting sequence compression algorithms using locally consistent encoding', 'Hach, Faraz|Numanagic, Ibrahim|Alkan, Can|Sahinalp, S Cenk', 'School of Computing Science, Simon Fraser University, Burnaby, Canada, V5A 1S6. fhach@cs.sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, Canada, V5A 1S6. fhach@cs.sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, Canada, V5A 1S6. fhach@cs.sfu.ca|School of Computing Science, Simon Fraser University, Burnaby, Canada, V5A 1S6. fhach@cs.sfu.ca', 'Canada|Canada|Canada|Canada', 92, 'Algorithms|Computational Biology|Data Compression|Genome|Genomics|High-Throughput Nucleotide Sequencing|Humans|Pseudomonas aeruginosa|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bts593', '23047557', 'The high throughput sequencing (HTS) platforms generate unprecedented amounts of data that introduce challenges for the computational infrastructure. Data management, storage and analysis have become major logistical obstacles for those adopting the new platforms. The requirement for large investment for this purpose almost signalled the end of the Sequence Read Archive hosted at the National Center for Biotechnology Information (NCBI), which holds most of the sequence data generated world wide. Currently, most HTS data are compressed through general purpose algorithms such as gzip. These algorithms are not designed for compressing data generated by the HTS platforms, for example, they do not take advantage of the specific nature of genomic sequence data, that is, limited alphabet size and high similarity among reads. Fast and efficient compression algorithms designed specifically for HTS data should be able to address some of the issues in data management, storage and communication. Such algorithms would also help with analysis provided they offer additional capabilities such as random access to any read and indexing for efficient sequence similarity search. Here we present SCALCE, a boosting scheme based on Locally Consistent Parsing technique, which reorganizes the reads in a way that results in a higher compression speed and compression rate, independent of the compression algorithm in use and without using a reference genome.'),
(77258, 2012, 'bio', 'Bayesian correlated clustering to integrate multiple datasets', 'Kirk, Paul|Griffin, Jim E|Savage, Richard S|Ghahramani, Zoubin|Wild, David L', 'Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, University of Warwick, Coventry, CV4 7AL, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 89, 'Bayes Theorem|Chromatin Immunoprecipitation|Cluster Analysis|Gene Expression|Gene Expression Profiling|Genomics|Models, Statistical|Normal Distribution|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Saccharomyces cerevisiae|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts595', '23047558', 'The integration of multiple datasets remains a key challenge in systems biology and genomic medicine. Modern high-throughput technologies generate a broad array of different data types, providing distinct-but often complementary-information. We present a Bayesian method for the unsupervised integrative modelling of multiple datasets, which we refer to as MDI (Multiple Dataset Integration). MDI can integrate information from a wide range of different datasets and data types simultaneously (including the ability to model time series data explicitly using Gaussian processes). Each dataset is modelled using a Dirichlet-multinomial allocation (DMA) mixture model, with dependencies between these models captured through parameters that describe the agreement among the datasets.'),
(77259, 2013, 'bio', 'Promoter-proximal CCCTC-factor binding is associated with an increase in the transcriptional pausing index', 'Paredes, Sur Herrera|Melgar, Michael F|Sethupathy, Praveen', 'Curriculum in Bioinformatics and Computational Biology, Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Curriculum in Bioinformatics and Computational Biology, Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Curriculum in Bioinformatics and Computational Biology, Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.', 'United States|United States|United States', 0, 'Animals|Binding Sites|CCCTC-Binding Factor|Cell Line|Cells, Cultured|Humans|Mice|Promoter Regions, Genetic|RNA Polymerase II|Repressor Proteins|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/bts596', '23047559', 'It has been known for more than 2 decades that after RNA polymerase II (RNAPII) initiates transcription, it can enter into a paused or stalled state immediately downstream of the transcription start site before productive elongation. Recent advances in high-throughput genomic technologies facilitated the discovery that RNAPII pausing at promoters is a widespread physiologically regulated phenomenon. The molecular underpinnings of pausing are incompletely understood. The CCCTC-factor (CTCF) is a ubiquitous nuclear factor that has diverse regulatory functions, including a recently discovered role in promoting RNAPII pausing at splice sites.'),
(77260, 2012, 'bio', 'KASpOD--a web service for highly specific and explorative oligonucleotide design', 'Parisot, Nicolas|Denonfoux, Jérémie|Dugat-Bony, Eric|Peyret, Pierre|Peyretaillade, Eric', 'Clermont Université, Université dAuvergne, EA 4678 CIDAM, BP 10448, France.|Clermont Université, Université dAuvergne, EA 4678 CIDAM, BP 10448, France.|Clermont Université, Université dAuvergne, EA 4678 CIDAM, BP 10448, France.|Clermont Université, Université dAuvergne, EA 4678 CIDAM, BP 10448, France.|Clermont Université, Université dAuvergne, EA 4678 CIDAM, BP 10448, France.', 'France|France|France|France|France', 0, 'Algorithms|Cluster Analysis|Internet|Oligonucleotide Array Sequence Analysis|Oligonucleotide Probes|Software', 'Journal Article', '10.1093/bioinformatics/bts597', '23047560', 'KASpOD is a web service dedicated to the design of signature sequences using a k-mer-based algorithm. Such highly specific and explorative oligonucleotides are then suitable for various goals, including Phylogenetic Oligonucleotide Arrays.'),
(77261, 2012, 'bio', 'Predicting protein residue-residue contacts using deep networks and boosting', 'Eickholt, Jesse|Cheng, Jianlin', 'Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, Columbia, MO 65211, USA.', 'United States|United States', 0, 'Artificial Intelligence|Computational Biology|Internet|Models, Statistical|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1093/bioinformatics/bts598', '23047561', 'Protein residue-residue contacts continue to play a larger and larger role in protein tertiary structure modeling and evaluation. Yet, while the importance of contact information increases, the performance of sequence-based contact predictors has improved slowly. New approaches and methods are needed to spur further development and progress in the field.'),
(77262, 2012, 'bio', 'Real time metagenomics: using k-mers to annotate metagenomes', 'Edwards, Robert A|Olson, Robert|Disz, Terry|Pusch, Gordon D|Vonstein, Veronika|Stevens, Rick|Overbeek, Ross', 'Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu|Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL 60439, USA. redwards@mail.sdsu.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Metagenome|Metagenomics|Molecular Sequence Annotation|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts599', '23047562', 'Annotation of metagenomes involves comparing the individual sequence reads with a database of known sequences and assigning a unique function to each read. This is a time-consuming task that is computationally intensive (though not computationally complex). Here we present a novel approach to annotate metagenomes using unique k-mer oligopeptide sequences from 7 to 12 amino acids long. We demonstrate that k-mer-based annotations are faster and approach the sensitivity and precision of blastx-based annotations without loosing accuracy. A last-common ancestor approach was also developed to describe the members of the community.'),
(77263, 2012, 'bio', 'De novo detection of copy number variation by co-assembly', 'Nijkamp, Jurgen F|van den Broek, Marcel A|Geertman, Jan-Maarten A|Reinders, Marcel J T|Daran, Jean-Marc G|de Ridder, Dick', 'The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.|The Delft Bioinformatics Lab, Department of Intelligent Systems, Delft University of Technology, 2628 CD Delft, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|DNA Copy Number Variations|Genome, Fungal|Genomics|High-Throughput Nucleotide Sequencing|Saccharomyces|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts601', '23047563', 'Comparing genomes of individual organisms using next-generation sequencing data is, until now, mostly performed using a reference genome. This is challenging when the reference is distant and introduces bias towards the exact sequence present in the reference. Recent improvements in both sequencing read length and efficiency of assembly algorithms have brought direct comparison of individual genomes by de novo assembly, rather than through a reference genome, within reach.'),
(77264, 2012, 'bio', 'Pathway-based visualization of cross-platform microarray datasets', 'Wrzodek, Clemens|Eichner, Johannes|Zell, Andreas', 'Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de', 'Germany|Germany|Germany', 0, 'Computational Biology|Computer Graphics|DNA|Databases, Genetic|Gene Expression Profiling|Genomics|Metabolic Networks and Pathways|MicroRNAs|Microarray Analysis|Proteins|Proteomics|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/bts583', '23047564', 'Traditionally, microarrays were almost exclusively used for the genome-wide analysis of differential gene expression. But nowadays, their scope of application has been extended to various genomic features, such as microRNAs (miRNAs), proteins and DNA methylation (DNAm). Most available methods for the visualization of these datasets are focused on individual platforms and are not capable of integratively visualizing multiple microarray datasets from cross-platform studies. Above all, there is a demand for methods that can visualize genomic features that are not directly linked to protein-coding genes, such as regulatory RNAs (e.g. miRNAs) and epigenetic alterations (e.g. DNAm), in a pathway-centred manner.'),
(77265, 2012, 'bio', 'Navigating the unexplored seascape of pre-miRNA candidates in single-genome approaches', 'Mendes, Nuno D|Heyne, Steffen|Freitas, Ana T|Sagot, Marie-France|Backofen, Rolf', 'Équipe BAOBAB, Laboratoire de Biométrie et Biologie Évolutive (UMR 5558), CNRS, University of Lyon 1, Lyon 69622, Villeurbanne Cedex, France.|Équipe BAOBAB, Laboratoire de Biométrie et Biologie Évolutive (UMR 5558), CNRS, University of Lyon 1, Lyon 69622, Villeurbanne Cedex, France.|Équipe BAOBAB, Laboratoire de Biométrie et Biologie Évolutive (UMR 5558), CNRS, University of Lyon 1, Lyon 69622, Villeurbanne Cedex, France.|Équipe BAOBAB, Laboratoire de Biométrie et Biologie Évolutive (UMR 5558), CNRS, University of Lyon 1, Lyon 69622, Villeurbanne Cedex, France.|Équipe BAOBAB, Laboratoire de Biométrie et Biologie Évolutive (UMR 5558), CNRS, University of Lyon 1, Lyon 69622, Villeurbanne Cedex, France.', 'France|France|France|France|France', 0, 'Algorithms|Animals|Anopheles|Base Sequence|Cluster Analysis|Computational Biology|Drosophila melanogaster|Genome|MicroRNAs|Nucleic Acid Conformation|Principal Component Analysis|ROC Curve|Software', 'Journal Article', '10.1093/bioinformatics/bts574', '23052038', 'The computational search for novel microRNA (miRNA) precursors often involves some sort of structural analysis with the aim of identifying which type of structures are prone to being recognized and processed by the cellular miRNA-maturation machinery. A natural way to tackle this problem is to perform clustering over the candidate structures along with known miRNA precursor structures. Mixed clusters allow then the identification of candidates that are similar to known precursors. Given the large number of pre-miRNA candidates that can be identified in single-genome approaches, even after applying several filters for precursor robustness and stability, a conventional structural clustering approach is unfeasible.'),
(77266, 2012, 'bio', 'Olorin: combining gene flow with exome sequencing in large family studies of complex disease', 'Morris, James A|Barrett, Jeffrey C', 'Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK. olorin@sanger.ac.uk|Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1HH, UK. olorin@sanger.ac.uk', 'United Kingdom|United Kingdom', 0, 'Alleles|Disease|Exome|Gene Flow|Genetic Linkage|High-Throughput Nucleotide Sequencing|Humans|Mutation|Pedigree|Software', 'Journal Article', '10.1093/bioinformatics/bts609', '23052039', 'The existence of families with many individuals affected by the same complex disease has long suggested the possibility of rare alleles of high penetrance. In contrast to Mendelian diseases, however, linkage studies have identified very few reproducibly linked loci in diseases such as diabetes and autism. Genome-wide association studies have had greater success with such diseases, but these results explain neither the extreme disease load nor the within-family linkage peaks, of some large pedigrees. Combining linkage information with exome or genome sequencing from large complex disease pedigrees might finally identify family-specific, high-penetrance mutations.'),
(77267, 2012, 'bio', 'GWASTools: an R/Bioconductor package for quality control and analysis of genome-wide association studies', 'Gogarten, Stephanie M|Bhangale, Tushar|Conomos, Matthew P|Laurie, Cecelia A|McHugh, Caitlin P|Painter, Ian|Zheng, Xiuwen|Crosslin, David R|Levine, David|Lumley, Thomas|Nelson, Sarah C|Rice, Kenneth|Shen, Jess|Swarnkar, Rohit|Weir, Bruce S|Laurie, Cathy C', 'Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.edu|Department of Biostatistics, University of Washington, Seattle, WA, USA. sdmorris@uw.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|United States|United States|United States|United States', 76, 'Genome-Wide Association Study|Genotype|Humans|Polymorphism, Single Nucleotide|Quality Control|Software', 'Journal Article', '10.1093/bioinformatics/bts610', '23052040', 'GWASTools is an R/Bioconductor package for quality control and analysis of genome-wide association studies (GWAS). GWASTools brings the interactive capability and extensive statistical libraries of R to GWAS. Data are stored in NetCDF format to accommodate extremely large datasets that cannot fit within Rs memory limits. The documentation includes instructions for converting data from multiple formats, including variants called from sequencing. GWASTools provides a convenient interface for linking genotypes and intensity data with sample and single nucleotide polymorphism annotation.'),
(77268, 2012, 'bio', 'Application of asymmetric statistical potentials to antibody-protein docking', 'Brenke, Ryan|Hall, David R|Chuang, Gwo-Yu|Comeau, Stephen R|Bohnuud, Tanggis|Beglov, Dmitri|Schueler-Furman, Ora|Vajda, Sandor|Kozakov, Dima', 'Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.|Department of Biomedical Engineering, Boston University, Boston, MA, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Antigen-Antibody Complex|Data Interpretation, Statistical|Fourier Analysis|Knowledge Bases|Molecular Docking Simulation|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/bts493', '23053206', 'An effective docking algorithm for antibody-protein antigen complex prediction is an important first step toward design of biologics and vaccines. We have recently developed a new class of knowledge-based interaction potentials called Decoys as the Reference State (DARS) and incorporated DARS into the docking program PIPER based on the fast Fourier transform correlation approach. Although PIPER was the best performer in the latest rounds of the CAPRI protein docking experiment, it is much less accurate for docking antibody-protein antigen pairs than other types of complexes, in spite of incorporating sequence-based information on the location of the paratope. Analysis of antibody-protein antigen complexes has revealed an inherent asymmetry within these interfaces. Specifically, phenylalanine, tryptophan and tyrosine residues highly populate the paratope of the antibody but not the epitope of the antigen.'),
(77269, 2012, 'bio', 'CD-HIT: accelerated for clustering the next-generation sequencing data', 'Fu, Limin|Niu, Beifang|Zhu, Zhengwei|Wu, Sitao|Li, Weizhong', 'Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.|Center for Research in Biological Systems, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States|United States|United States|United States', 2062, 'Algorithms|Cluster Analysis|Computational Biology|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts565', '23060610', 'CD-HIT is a widely used program for clustering biological sequences to reduce sequence redundancy and improve the performance of other sequence analyses. In response to the rapid increase in the amount of sequencing data produced by the next-generation sequencing technologies, we have developed a new CD-HIT program accelerated with a novel parallelization strategy and some other techniques to allow efficient clustering of such datasets. Our tests demonstrated very good speedup derived from the parallelization for up to xe2x88xbc24 cores and a quasi-linear speedup for up to xe2x88xbc8 cores. The enhanced CD-HIT is capable of handling very large datasets in much shorter time than previous versions.'),
(77270, 2012, 'bio', 'Network-based inference from complex proteomic mixtures using SNIPE', 'Nusinow, David P|Kiezun, Adam|OConnell, Daniel J|Chick, Joel M|Yue, Yingzi|Maas, Richard L|Gygi, Steven P|Sunyaev, Shamil R', 'Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.|Division of Genetics, Brigham and Womens Hospital, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Animals|Computational Biology|Mice|Proteome|Proteomics|Software|Tooth', 'Journal Article', '10.1093/bioinformatics/bts594', '23060611', 'Proteomics presents the opportunity to provide novel insights about the global biochemical state of a tissue. However, a significant problem with current methods is that shotgun proteomics has limited success at detecting many low abundance proteins, such as transcription factors from complex mixtures of cells and tissues. The ability to assay for these proteins in the context of the entire proteome would be useful in many areas of experimental biology.'),
(77271, 2013, 'bio', 'Towards the development of standardized methods for comparison, ranking and evaluation of structure alignments', 'Slater, Alex W|Castellanos, Javier I|Sippl, Manfred J|Melo, Francisco', 'Molecular Bioinformatics Laboratory, Millennium Institute on Immunology and Immunotherapy, Portugal 49, Santiago, CP 8330025, Chile.|Molecular Bioinformatics Laboratory, Millennium Institute on Immunology and Immunotherapy, Portugal 49, Santiago, CP 8330025, Chile.|Molecular Bioinformatics Laboratory, Millennium Institute on Immunology and Immunotherapy, Portugal 49, Santiago, CP 8330025, Chile.|Molecular Bioinformatics Laboratory, Millennium Institute on Immunology and Immunotherapy, Portugal 49, Santiago, CP 8330025, Chile.', 'Chile|Chile|Chile|Chile', 14, 'Algorithms|Computational Biology|Models, Molecular|Proteins|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts600', '23060612', 'Pairwise alignment of protein structures is a fundamental task in structural bioinformatics. There are numerous computer programs in the public domain that produce alignments for a given pair of protein structures, but the results obtained by the various programs generally differ substantially. Hence, in the application of such programs the question arises which of the alignment programs are the most trustworthy in the sense of overall performance, and which programs provide the best result for a given pair of proteins. The major problem in comparing, evaluating and judging alignment results is that there is no clear notion of the optimality of an alignment. As a consequence, the numeric criteria and scores reported by the individual structure alignment programs are largely incomparable.'),
(77272, 2012, 'bio', 'An ensemble correlation-based gene selection algorithm for cancer classification with gene expression data', 'Piao, Yongjun|Piao, Minghao|Park, Kiejung|Ryu, Keun Ho', 'Department of Electrical and Computer Engineering, Chungbuk National University, Chungbuk, Korea.|Department of Electrical and Computer Engineering, Chungbuk National University, Chungbuk, Korea.|Department of Electrical and Computer Engineering, Chungbuk National University, Chungbuk, Korea.|Department of Electrical and Computer Engineering, Chungbuk National University, Chungbuk, Korea.', '-|-|-|-', 54, 'Algorithms|Artificial Intelligence|Gene Expression|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Support Vector Machine', 'Evaluation Studies', '10.1093/bioinformatics/bts602', '23060613', 'Gene selection for cancer classification is one of the most important topics in the biomedical field. However, microarray data pose a severe challenge for computational techniques. We need dimension reduction techniques that identify a small set of genes to achieve better learning performance. From the perspective of machine learning, the selection of genes can be considered to be a feature selection problem that aims to find a small subset of features that has the most discriminative information for the target.'),
(77273, 2012, 'bio', 'Tools for mapping high-throughput sequencing data', 'Fonseca, Nuno A|Rung, Johan|Brazma, Alvis|Marioni, John C', 'EMBL Outstation, European Bioinformatics Institute (EBI), Hinxton, Cambridge CB10 ISD, UK. nf@ebi.ac.uk|EMBL Outstation, European Bioinformatics Institute (EBI), Hinxton, Cambridge CB10 ISD, UK. nf@ebi.ac.uk|EMBL Outstation, European Bioinformatics Institute (EBI), Hinxton, Cambridge CB10 ISD, UK. nf@ebi.ac.uk|EMBL Outstation, European Bioinformatics Institute (EBI), Hinxton, Cambridge CB10 ISD, UK. nf@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 164, 'Algorithms|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts605', '23060614', 'A ubiquitous and fundamental step in high-throughput sequencing analysis is the alignment (mapping) of the generated reads to a reference sequence. To accomplish this task, numerous software tools have been proposed. Determining the mappers that are most suitable for a specific application is not trivial.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77274, 2012, 'bio', 'A high-performance computing toolset for relatedness and principal component analysis of SNP data', 'Zheng, Xiuwen|Levine, David|Shen, Jess|Gogarten, Stephanie M|Laurie, Cathy|Weir, Bruce S', 'Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu|Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu|Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu|Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu|Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu|Department of Biostatistics, University of Washington, Seattle, WA 98195-7232, USA. zhengx@u.washington.edu', 'United States|United States|United States|United States|United States|United States', 618, 'Algorithms|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide|Principal Component Analysis|Software', 'Journal Article', '10.1093/bioinformatics/bts606', '23060615', 'Genome-wide association studies are widely used to investigate the genetic basis of diseases and traits, but they pose many computational challenges. We developed gdsfmt and SNPRelate (R packages for multi-core symmetric multiprocessing computer architectures) to accelerate two key computations on SNP data: principal component analysis (PCA) and relatedness analysis using identity-by-descent measures. The kernels of our algorithms are written in C/C++ and highly optimized. Benchmarks show the uniprocessor implementations of PCA and identity-by-descent are xe2x88xbc8-50 times faster than the implementations provided in the popular EIGENSTRAT (v3.0) and PLINK (v1.07) programs, respectively, and can be sped up to 30-300-fold by using eight cores. SNPRelate can analyse tens of thousands of samples with millions of SNPs. For example, our package was used to perform PCA on 55 324 subjects from the Gene-Environment Association Studies consortium studies.'),
(77275, 2012, 'bio', 'CLEVER: clique-enumerating variant finder', 'Marschall, Tobias|Costa, Ivan G|Canzar, Stefan|Bauer, Markus|Klau, Gunnar W|Schliep, Alexander|Schönhuth, Alexander', 'Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl|Centrum Wiskunde & Informatica, Life Sciences Group, Amsterdam, The Netherlands. tm@cwi.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 44, 'Algorithms|Computer Simulation|Genetic Variation|Genome, Human|Humans|INDEL Mutation', 'Journal Article', '10.1093/bioinformatics/bts566', '23060616', 'Next-generation sequencing techniques have facilitated a large-scale analysis of human genetic variation. Despite the advances in sequencing speed, the computational discovery of structural variants is not yet standard. It is likely that many variants have remained undiscovered in most sequenced individuals.'),
(77276, 2012, 'bio', 'Transcriptome assembly and isoform expression level estimation from biased RNA-Seq reads', 'Li, Wei|Jiang, Tao', 'Department of Computer Science and Engineering, University of California, Riverside, Riverside CA 92507, USA. liw@cs.ucr.edu|Department of Computer Science and Engineering, University of California, Riverside, Riverside CA 92507, USA. liw@cs.ucr.edu', 'United States|United States', 48, 'Algorithms|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Protein Isoforms|Sequence Analysis, RNA|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/bts559', '23060617', 'RNA-Seq uses the high-throughput sequencing technology to identify and quantify transcriptome at an unprecedented high resolution and low cost. However, RNA-Seq reads are usually not uniformly distributed and biases in RNA-Seq data post great challenges in many applications including transcriptome assembly and the expression level estimation of genes or isoforms. Much effort has been made in the literature to calibrate the expression level estimation from biased RNA-Seq data, but the effect of biases on transcriptome assembly remains largely unexplored.'),
(77277, 2012, 'bio', 'DAFS: simultaneous aligning and folding of RNA sequences via dual decomposition', 'Sato, Kengo|Kato, Yuki|Akutsu, Tatsuya|Asai, Kiyoshi|Sakakibara, Yasubumi', 'Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. satoken@bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. satoken@bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. satoken@bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. satoken@bio.keio.ac.jp|Department of Biosciences and Informatics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan. satoken@bio.keio.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 18, 'Algorithms|Base Pairing|Nucleic Acid Conformation|RNA|RNA Folding|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/bts612', '23060618', 'It is well known that the accuracy of RNA secondary structure prediction from a single sequence is limited, and thus a comparative approach that predicts a common secondary structure from aligned sequences is a better choice if homologous sequences with reliable alignments are available. However, correct secondary structure information is needed to produce reliable alignments of RNA sequences. To tackle this dilemma, we require a fast and accurate aligner that takes structural information into consideration to yield reliable structural alignments, which are suitable for common secondary structure prediction.'),
(77278, 2012, 'bio', 'TIBA: a tool for phylogeny inference from rearrangement data with bootstrap analysis', 'Lin, Yu|Rajan, Vaibhav|Moret, Bernard M E', 'Laboratory for Computational Biology and Bioinformatics, EPFL, EPFL-IC-LCBB INJ 230, Station 14, CH-1015 Lausanne, Switzerland.|Laboratory for Computational Biology and Bioinformatics, EPFL, EPFL-IC-LCBB INJ 230, Station 14, CH-1015 Lausanne, Switzerland.|Laboratory for Computational Biology and Bioinformatics, EPFL, EPFL-IC-LCBB INJ 230, Station 14, CH-1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland', 10, 'Evolution, Molecular|Genome|Phylogeny|Software|Synteny', 'Journal Article', '10.1093/bioinformatics/bts603', '23060619', 'TIBA is a tool to reconstruct phylogenetic trees from rearrangement data that consist of ordered lists of synteny blocks (or genes), where each synteny block is shared with all of its homologues in the input genomes. The evolution of these synteny blocks, through rearrangement operations, is modelled by the uniform Double-Cut-and-Join model. Using a true distance estimate under this model and simple distance-based methods, TIBA reconstructs a phylogeny of the input genomes. Unlike any previous tool for inferring phylogenies from rearrangement data, TIBA uses novel methods of robustness estimation to provide support values for the edges in the inferred tree.'),
(77279, 2012, 'bio', 'Aragonite-associated biomineralization proteins are disordered and contain interactive motifs', 'Evans, John Spencer', 'Laboratory for Chemical Physics, Department of Basic Sciences and Craniofacial Biology, New York University, New York, NY 10012, USA. jse1@nyu.edu', 'United States', 53, 'Animals|Calcification, Physiologic|Calcium Carbonate|Extracellular Matrix Proteins|Mollusca|Nacre|Protein Conformation|Protein Interaction Domains and Motifs|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bts604', '23060620', 'The formation of aragonite mineral in the mollusk shell or pearl nacre requires the participation of a diverse set of proteins that form the mineralized extracellular matrix. Although self-assembly processes have been identified for several nacre proteins, these proteins do not contain known globular protein-protein binding domains. Thus, we hypothesize that other sequence features are responsible for nacre matrix protein-protein assembly processes and ultimately aragonite biosynthesis.'),
(77280, 2012, 'bio', 'A counting renaissance: combining stochastic mapping and empirical Bayes to quickly detect amino acid sites under positive selection', 'Lemey, Philippe|Minin, Vladimir N|Bielejec, Filip|Kosakovsky Pond, Sergei L|Suchard, Marc A', 'Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be|Department of Microbiology and Immunology, Rega Institute, KU Leuven, B-3000 Leuven, Belgium. philippe.lemey@rega.kuleuven.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 41, 'Amino Acid Substitution|Amino Acids|Bayes Theorem|Codon|Evolution, Molecular|Models, Genetic|Phylogeny|Selection, Genetic|Sequence Alignment|Stochastic Processes|Viruses', 'Journal Article', '10.1093/bioinformatics/bts580', '23064000', 'Statistical methods for comparing relative rates of synonymous and non-synonymous substitutions maintain a central role in detecting positive selection. To identify selection, researchers often estimate the ratio of these relative rates (dN/dS) at individual alignment sites. Fitting a codon substitution model that captures heterogeneity in dN/dS across sites provides a reliable way to perform such estimation, but it remains computationally prohibitive for massive datasets. By using crude estimates of the numbers of synonymous and non-synonymous substitutions at each site, counting approaches scale well to large datasets, but they fail to account for ancestral state reconstruction uncertainty and to provide site-specific dN/dS estimates.'),
(77281, 2012, 'bio', 'Multinomial modeling and an evaluation of common data-mining algorithms for identifying signals of disproportionate reporting in pharmacovigilance databases', 'Johnson, Kjell|Guo, Cen|Gosink, Mark|Wang, Vicky|Hauben, Manfred', 'Arbor Analytics LLC, Ann Arbor, MI, USA. kjell@arboranalytics.com|Arbor Analytics LLC, Ann Arbor, MI, USA. kjell@arboranalytics.com|Arbor Analytics LLC, Ann Arbor, MI, USA. kjell@arboranalytics.com|Arbor Analytics LLC, Ann Arbor, MI, USA. kjell@arboranalytics.com|Arbor Analytics LLC, Ann Arbor, MI, USA. kjell@arboranalytics.com', 'United States|United States|United States|United States|United States', 10, 'Adverse Drug Reaction Reporting Systems|Algorithms|Data Mining|Databases, Factual|Medical Informatics|Models, Statistical|Pharmacovigilance|Software', 'Journal Article', '10.1093/bioinformatics/bts576', '23064001', 'A principal objective of pharmacovigilance is to detect adverse drug reactions that are unknown or novel in terms of their clinical severity or frequency. One method is through inspection of spontaneous reporting system databases, which consist of millions of reports of patients experiencing adverse effects while taking one or more drugs. For such large databases, there is an increasing need for quantitative and automated screening tools to assist drug safety professionals in identifying drug-event combinations (DECs) worthy of further investigation. Existing algorithms can effectively identify problematic DECs when the frequencies are high. However these algorithms perform differently for low-frequency DECs.'),
(77282, 2012, 'bio', 'SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data', 'Kopylova, Evguenia|Noé, Laurent|Touzet, Hélène', 'LIFL (UMR CNRS 8022 Université Lille 1), France. evguenia.kopylova@lifl.fr|LIFL (UMR CNRS 8022 Université Lille 1), France. evguenia.kopylova@lifl.fr|LIFL (UMR CNRS 8022 Université Lille 1), France. evguenia.kopylova@lifl.fr', 'France|France|France', 691, 'Algorithms|Ecosystem|Gene Expression Profiling|Phylogeny|RNA, Messenger|RNA, Ribosomal|RNA, Ribosomal, 16S|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts611', '23071270', 'The application of next-generation sequencing (NGS) technologies to RNAs directly extracted from a community of organisms yields a mixture of fragments characterizing both coding and non-coding types of RNAs. The task to distinguish among these and to further categorize the families of messenger RNAs and ribosomal RNAs (rRNAs) is an important step for examining gene expression patterns of an interactive environment and the phylogenetic classification of the constituting species.'),
(77283, 2012, 'bio', 'MULTOVL: fast multiple overlaps of genomic regions', 'Aszódi, András', 'Scientific Computing Core Facility, Campus Science Support Facilities, 1030 Vienna, Austria. andras.aszodi@csf.ac.at', 'Austria', 16, 'Algorithms|Genomics|Probability|Software', 'Journal Article', '10.1093/bioinformatics/bts607', '23071271', 'We present the MULTOVL application suite that detects and statistically analyses multiple overlaps of genomic regions in a fast and efficient manner. The package supports the detection of multiple region intersections, unions and solitary genomic regions. The significance of actually observed overlaps is estimated by comparing them with empirical null distributions generated by random shuffling of the input regions.'),
(77284, 2012, 'bio', 'Inference of temporally varying Bayesian networks', 'Thorne, Thomas|Stumpf, Michael P H', 'Centre of Integrative Systems Biology and Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK. thomas.thorne@imperial.ac.uk|Centre of Integrative Systems Biology and Bioinformatics, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK. thomas.thorne@imperial.ac.uk', 'United Kingdom|United Kingdom', 14, 'Animals|Arabidopsis|Bayes Theorem|Drosophila melanogaster|Gene Expression|Gene Expression Profiling|Gene Regulatory Networks|Markov Chains|Starch', 'Journal Article', '10.1093/bioinformatics/bts614', '23074260', 'When analysing gene expression time series data, an often overlooked but crucial aspect of the model is that the regulatory network structure may change over time. Although some approaches have addressed this problem previously in the literature, many are not well suited to the sequential nature of the data.'),
(77285, 2012, 'bio', 'Reference-independent comparative metagenomics using cross-assembly: crAss', 'Dutilh, Bas E|Schmieder, Robert|Nulton, Jim|Felts, Ben|Salamon, Peter|Edwards, Robert A|Mokili, John L', 'Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl|Centre for Molecular and Biomolecular Informatics, Nijmegen Centre for Molecular Life Sciences, Radboud University Medical Centre, 6525 GA Nijmegen, The Netherlands. dutilh@cmbi.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Computational Biology|Genome, Viral|Humans|Metagenome|Metagenomics|Software', 'Journal Article', '10.1093/bioinformatics/bts613', '23074261', 'Metagenomes are often characterized by high levels of unknown sequences. Reads derived from known microorganisms can easily be identified and analyzed using fast homology search algorithms and a suitable reference database, but the unknown sequences are often ignored in further analyses, biasing conclusions. Nevertheless, it is possible to use more data in a comparative metagenomic analysis by creating a cross-assembly of all reads, i.e. a single assembly of reads from different samples. Comparative metagenomics studies the interrelationships between metagenomes from different samples. Using an assembly algorithm is a fast and intuitive way to link (partially) homologous reads without requiring a database of reference sequences.'),
(77286, 2012, 'bio', 'Interactive exploration of RNA22 microRNA target predictions', 'Loher, Phillipe|Rigoutsos, Isidore', 'Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA.|Computational Medicine Center, Thomas Jefferson University, Philadelphia, PA 19107, USA.', 'United States|United States', 0, 'Algorithms|Animals|Caenorhabditis elegans|Drosophila melanogaster|Gene Expression Regulation|Humans|Mice|MicroRNAs|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts615', '23074262', 'MicroRNA (miRNA) target prediction is an important problem. Given an miRNA sequence the task is to determine the identity of the messenger RNAs targeted by it, the locations within them where the interactions happen and the specifics of the formed heteroduplexes. Here, we describe a web-based application, RNA22-GUI, which we have designed and implemented for the interactive exploration and in-context visualization of predictions by RNA22, one of the popular miRNA target prediction algorithms. Central to our design has been the requirement to provide informative and comprehensive visualization that is integrated with interactive search capabilities and permits one to selectively isolate and focus on relevant information that is distilled on-the-fly from a large repository of pre-compiled predictions. RNA22-GUI is currently available for Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans.'),
(77287, 2012, 'bio', 'Discriminative modelling of context-specific amino acid substitution probabilities', 'Angermüller, Christof|Biegert, Andreas|Söding, Johannes', 'Gene Center Munich and Department of Biochemistry, Ludwig-Maximilians-Universtät München, 81377 Munich, Germany.|Gene Center Munich and Department of Biochemistry, Ludwig-Maximilians-Universtät München, 81377 Munich, Germany.|Gene Center Munich and Department of Biochemistry, Ludwig-Maximilians-Universtät München, 81377 Munich, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Substitution|Models, Statistical|Probability|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts622', '23080114', 'Protein sequence searching and alignment are fundamental tools of modern biology. Alignments are assessed using their similarity scores, essentially the sum of substitution matrix scores over all pairs of aligned amino acids. We previously proposed a generative probabilistic method that yields scores that take the sequence context around each aligned residue into account. This method showed drastically improved sensitivity and alignment quality compared with standard substitution matrix-based alignment.'),
(77288, 2013, 'bio', 'Human protein-protein interaction prediction by a novel sequence-based co-evolution method: co-evolutionary divergence', 'Hsin Liu, Chia|Li, Ker-Chau|Yuan, Shinsheng', 'Institute of Statistical Science, Academia Sinica, Nangang, Taipei 115, Taiwan.|Institute of Statistical Science, Academia Sinica, Nangang, Taipei 115, Taiwan.|Institute of Statistical Science, Academia Sinica, Nangang, Taipei 115, Taiwan.', '-|-|-', 0, 'Amino Acid Substitution|Animals|Bayes Theorem|Evolution, Molecular|Humans|Phylogeny|Protein Interaction Mapping|Proteins|Proteome|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bts620', '23080115', 'Protein-protein interaction (PPI) plays an important role in understanding gene functions, and many computational PPI prediction methods have been proposed in recent years. Despite the extensive efforts, PPI prediction still has much room to improve. Sequence-based co-evolution methods include the substitution rate method and the mirror tree method, which compare sequence substitution rates and topological similarity of phylogenetic trees, respectively. Although they have been used to predict PPI in species with small genomes like Escherichia coli, such methods have not been tested in large scale proteome like Homo sapiens.'),
(77289, 2013, 'bio', 'NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference', 'Zhang, Xiujun|Liu, Keqin|Liu, Zhi-Ping|Duval, Béatrice|Richer, Jean-Michel|Zhao, Xing-Ming|Hao, Jin-Kao|Chen, Luonan', 'Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Institute of Systems Biology, Shanghai University, Shanghai 200444, China.', 'China|China|China|China|China|China|China|China', 0, 'Algorithms|Escherichia coli|Gene Regulatory Networks|Transcriptome', 'Evaluation Studies', '10.1093/bioinformatics/bts619', '23080116', 'Reconstruction of gene regulatory networks (GRNs) is of utmost interest to biologists and is vital for understanding the complex regulatory mechanisms within the cell. Despite various methods developed for reconstruction of GRNs from gene expression profiles, they are notorious for high false positive rate owing to the noise inherited in the data, especially for the dataset with a large number of genes but a small number of samples.'),
(77290, 2012, 'bio', 'Lengthening of 3UTR increases with morphological complexity in animal evolution', 'Chen, Cho-Yi|Chen, Shui-Tein|Juan, Hsueh-Fen|Huang, Hsuan-Cheng', 'Genome and Systems Biology Degree Program, Department of Life Science, Institute of Molecular and Cellular Biology, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 116, Taiwan.|Genome and Systems Biology Degree Program, Department of Life Science, Institute of Molecular and Cellular Biology, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 116, Taiwan.|Genome and Systems Biology Degree Program, Department of Life Science, Institute of Molecular and Cellular Biology, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 116, Taiwan.|Genome and Systems Biology Degree Program, Department of Life Science, Institute of Molecular and Cellular Biology, Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei 116, Taiwan.', '-|-|-|-', 25, '3 Untranslated Regions|Animals|Biological Evolution|Cells|Humans', 'Journal Article', '10.1093/bioinformatics/bts623', '23080117', 'Evolutionary expansion of gene regulatory circuits seems to boost morphological complexity. However, the expansion patterns and the quantification relationships have not yet been identified. In this study, we focus on the regulatory circuits at the post-transcriptional level, investigating whether and how this principle may apply.'),
(77291, 2012, 'bio', 'Assessing the relationship between conservation of function and conservation of sequence using photosynthetic proteins', 'Ashkenazi, Shaul|Snir, Rotem|Ofran, Yanay', 'The Goodman faculty of life sciences, Bar Ilan University, Ramat Gan 52900, Israel.|The Goodman faculty of life sciences, Bar Ilan University, Ramat Gan 52900, Israel.|The Goodman faculty of life sciences, Bar Ilan University, Ramat Gan 52900, Israel.', 'Israel|Israel|Israel', 8, 'Amino Acid Motifs|Amino Acid Sequence|Conserved Sequence|Molecular Sequence Annotation|Photosynthesis|Proteins|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/bts608', '23080118', 'Assessing the false positive rate of function prediction methods is difficult, as it is hard to establish that a protein does not have a certain function. To determine to what extent proteins with similar sequences have a common function, we focused on photosynthesis-related proteins. A protein that comes from a non-photosynthetic organism is, undoubtedly, not involved in photosynthesis.'),
(77292, 2012, 'bio', 'CDRUG: a web server for predicting anticancer activity of chemical compounds', 'Li, Gong-Hua|Huang, Jing-Fei', 'State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.|State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China.', 'China|China', 27, 'Antineoplastic Agents|Drug Discovery|Internet|Software', 'Journal Article', '10.1093/bioinformatics/bts625', '23080119', 'Cancer is the leading cause of death worldwide. Screening anticancer candidates from tens of millions of chemical compounds is expensive and time-consuming. A rapid and user-friendly web server, known as CDRUG, is described here to predict the anticancer activity of chemical compounds. In CDRUG, a hybrid score was developed to measure the similarity of different compounds. The performance analysis shows that CDRUG has the area under curve of 0.878, indicating that CDRUG is effective to distinguish active and inactive compounds.'),
(77293, 2012, 'bio', 'Discovering chimeric transcripts in paired-end RNA-seq data by using EricScript', 'Benelli, Matteo|Pescucci, Chiara|Marseglia, Giuseppina|Severgnini, Marco|Torricelli, Francesca|Magi, Alberto', 'Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com|Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com|Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com|Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com|Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com|Diagnostic Genetic Unit, Laboratory Department, Careggi University Hospital, 50134 Florence, Italy. matteo.benelli@gmail.com', 'Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Cell Line, Tumor|Gene Expression Profiling|Gene Fusion|Genomics|High-Throughput Nucleotide Sequencing|Humans|RNA, Neoplasm|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/bts617', '23093608', 'The discovery of novel gene fusions can lead to a better comprehension of cancer progression and development. The emergence of deep sequencing of trancriptome, known as RNA-seq, has opened many opportunities for the identification of this class of genomic alterations, leading to the discovery of novel chimeric transcripts in melanomas, breast cancers and lymphomas. Nowadays, few computational approaches have been developed for the detection of chimeric transcripts. Although all of these computational methods show good sensitivity, much work remains to reduce the huge number of false-positive calls that arises from this analysis.'),
(77294, 2012, 'bio', 'Fast protein structure alignment using Gaussian overlap scoring of backbone peptide fragment similarity', 'Ritchie, David W|Ghoorah, Anisah W|Mavridis, Lazaros|Venkatraman, Vishwesh', 'Dave.Ritchie@inria.fr|Dave.Ritchie@inria.fr|Dave.Ritchie@inria.fr|Dave.Ritchie@inria.fr', '-|-|-|-', 23, 'Algorithms|Databases, Protein|Models, Molecular|Normal Distribution|Peptides|Protein Structure, Secondary|Proteins|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts618', '23093609', 'Aligning and comparing protein structures is important for understanding their evolutionary and functional relationships. With the rapid growth of protein structure databases in recent years, the need to align, superpose and compare protein structures rapidly and accurately has never been greater. Many structural alignment algorithms have been described in the past 20 years. However, achieving an algorithm that is both accurate and fast remains a considerable challenge.'),
(77295, 2013, 'bio', 'Genotype calling and phasing using next-generation sequencing reads and a haplotype scaffold', 'Menelaou, Androniki|Marchini, Jonathan', 'Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.', 'United Kingdom|United Kingdom', 27, 'Algorithms|Alleles|Chromosomes, Human, Pair 20|Gene Frequency|Genotype|Genotyping Techniques|Haplotypes|High-Throughput Nucleotide Sequencing|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/bts632', '23093610', 'Given the current costs of next-generation sequencing, large studies carry out low-coverage sequencing followed by application of methods that leverage linkage disequilibrium to infer genotypes. We propose a novel method that assumes study samples are sequenced at low coverage and genotyped on a genome-wide microarray, as in the 1000 Genomes Project (1KGP). We assume polymorphic sites have been detected from the sequencing data and that genotype likelihoods are available at these sites. We also assume that the microarray genotypes have been phased to construct a haplotype scaffold. We then phase each polymorphic site using an MCMC algorithm that iteratively updates the unobserved alleles based on the genotype likelihoods at that site and local haplotype information. We use a multivariate normal model to capture both allele frequency and linkage disequilibrium information around each site. When sequencing data are available from trios, Mendelian transmission constraints are easily accommodated into the updates. The method is highly parallelizable, as it analyses one position at a time.'),
(77296, 2012, 'bio', 'A method for integrative structure determination of protein-protein complexes', 'Schneidman-Duhovny, Dina|Rossi, Andrea|Avila-Sakar, Agustin|Kim, Seung Joong|Velázquez-Muriel, Javier|Strop, Pavel|Liang, Hong|Krukenberg, Kristin A|Liao, Maofu|Kim, Ho Min|Sobhanifar, Solmaz|Dötsch, Volker|Rajpal, Arvind|Pons, Jaume|Agard, David A|Cheng, Yifan|Sali, Andrej', 'Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.org|Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA 94158, USA. dina@salilab.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|United States|United States|United States|United States', 0, 'Antigen-Antibody Complex|Crystallography, X-Ray|Microscopy, Electron|Molecular Docking Simulation|Multiprotein Complexes|Scattering, Small Angle|Software|X-Ray Diffraction', 'Journal Article', '10.1093/bioinformatics/bts628', '23093611', 'Structural characterization of protein interactions is necessary for understanding and modulating biological processes. On one hand, X-ray crystallography or NMR spectroscopy provide atomic resolution structures but the data collection process is typically long and the success rate is low. On the other hand, computational methods for modeling assembly structures from individual components frequently suffer from high false-positive rate, rarely resulting in a unique solution.'),
(77297, 2012, 'bio', 'Two distinct SSB protein families in nucleo-cytoplasmic large DNA viruses', 'Kazlauskas, Darius|Venclovas, Ceslovas', 'Institute of Biotechnology, Vilnius University, LT-02241 Vilnius, Lithuania.|Institute of Biotechnology, Vilnius University, LT-02241 Vilnius, Lithuania.', 'Lithuania|Lithuania', 0, 'Amino Acid Sequence|Binding Sites|DNA Viruses|DNA, Single-Stranded|DNA-Binding Proteins|Evolution, Molecular|Molecular Sequence Data|Poxviridae|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/bts626', '23097418', 'Eukaryote-infecting nucleo-cytoplasmic large DNA viruses (NCLDVs) feature some of the largest genomes in the viral world. These viruses typically do not strongly depend on the host DNA replication systems. In line with this observation, a number of essential DNA replication proteins, such as DNA polymerases, primases, helicases and ligases, have been identified in the NCLDVs. One other ubiquitous component of DNA replisomes is the single-stranded DNA-binding (SSB) protein. Intriguingly, no NCLDV homologs of canonical OB-fold-containing SSB proteins had previously been detected. Only in poxviruses, one of seven NCLDV families, I3 was identified as the SSB protein. However, whether I3 is related to any known protein structure has not yet been established.'),
(77298, 2013, 'bio', 'Simultaneous alignment and clustering of peptide data using a Gibbs sampling approach', 'Andreatta, Massimo|Lund, Ole|Nielsen, Morten', 'Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark. massimo@cbs.dtu.dk|Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark. massimo@cbs.dtu.dk|Center for Biological Sequence Analysis, Technical University of Denmark, DK-2800 Lyngby, Denmark. massimo@cbs.dtu.dk', 'Denmark|Denmark|Denmark', 51, 'Algorithms|Alleles|Cluster Analysis|Genes, MHC Class I|Genes, MHC Class II|HLA Antigens|Humans|Ligands|Peptides|Position-Specific Scoring Matrices|Protein Binding|Protein Interaction Domains and Motifs|Sequence Alignment|Sequence Analysis, Protein|src Homology Domains', 'Journal Article', '10.1093/bioinformatics/bts621', '23097419', 'Proteins recognizing short peptide fragments play a central role in cellular signaling. As a result of high-throughput technologies, peptide-binding protein specificities can be studied using large peptide libraries at dramatically lower cost and time. Interpretation of such large peptide datasets, however, is a complex task, especially when the data contain multiple receptor binding motifs, and/or the motifs are found at different locations within distinct peptides.'),
(77299, 2013, 'bio', 'AffyRNADegradation: control and correction of RNA quality effects in GeneChip expression data', 'Fasold, Mario|Binder, Hans', 'Interdisciplinary Center for Bioinformatics, Universität Leipzig, D-4107 Leipzig, Haertelstr. 16-18, Germany.|Interdisciplinary Center for Bioinformatics, Universität Leipzig, D-4107 Leipzig, Haertelstr. 16-18, Germany.', 'Germany|Germany', 0, 'Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|RNA Stability|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/bts629', '23097420', 'Gene expression experiments aim to accurately quantify thousands of transcripts in parallel. Factors posterior to RNA extraction can, however, impair their accurate representation. RNA degradation and differences in the efficiency of amplification affect raw intensity measurements using Affymetrix expression arrays. The positional intensity decay of specifically hybridized probes along the transcript they intend to interrogate is used to estimate the RNA quality in a sample and to correct probe intensities for the degradation bias. This functionality, for which no previous software solution is available, is implemented in the R/Bioconductor package AffyRNADegradation presented here.'),
(77300, 2012, 'bio', 'FFPopSim: an efficient forward simulation package for the evolution of large populations', 'Zanini, Fabio|Neher, Richard A', 'Evolutionary Dynamics and Biophysics Group, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.|Evolutionary Dynamics and Biophysics Group, Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany.', 'Germany|Germany', 22, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Genetics, Population|Genotype|Models, Genetic|Population Density|Software', 'Journal Article', '10.1093/bioinformatics/bts633', '23097421', 'The analysis of the evolutionary dynamics of a population with many polymorphic loci is challenging, as a large number of possible genotypes needs to be tracked. In the absence of analytical solutions, forward computer simulations are an important tool in multi-locus population genetics. The run time of standard algorithms to simulate sexual populations increases as 8(L) with the number of loci L, or with the square of the population size N.'),
(77301, 2012, 'bio', 'Distinction immune genes of hepatitis-induced heptatocellular carcinoma', 'Hu, Jinyu|Gao, David Zhiwei', 'Department of Automation, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.|Department of Automation, School of Electrical Engineering and Automation, Tianjin University, Tianjin 300072, China.', 'China|China', 0, 'Carcinoma, Hepatocellular|Gene Expression|Hepatitis B|Hepatitis C|Humans|Immunity|Liver Neoplasms', 'Journal Article', '10.1093/bioinformatics/bts624', '23104883', 'Hepatitis B virus and hepatitis C virus are the two leading causes resulting in hepatocellular carcinoma (HCC). It is observed that hepatitis C virus (HCV) is relatively difficult to induce HCC compared with hepatitis B virus (HBV). This motivates us to reveal the reasons behind this from the viewpoint of immune genes.'),
(77302, 2013, 'bio', 'PriVar: a toolkit for prioritizing SNVs and indels from next-generation sequencing data', 'Zhang, Lu|Zhang, Jing|Yang, Jing|Ying, Dingge|Lau, Yu Lung|Yang, Wanling', 'Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.|Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.|Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.|Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.|Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.|Department of Paediatrics and Adolescent Medicine, LKS Faculty of Medicine, The University of Hong Kong, 21 Sassoon Road, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 25, 'Exome|Genetic Linkage|Genetic Variation|High-Throughput Nucleotide Sequencing|Humans|INDEL Mutation|Mutation|Software', 'Journal Article', '10.1093/bioinformatics/bts627', '23104884', 'Next-generation sequencing has become a valuable tool for detecting mutations involved in Mendelian diseases. However, it is a challenge to identify the small subset of functionally important mutations from tens of thousands of rare variants in a whole exome/genome. Therefore, we developed a toolkit called PriVar, a systematic prioritization pipeline that takes into consideration calling quality of the variants, their predicted functional impact, known connection of the gene to the disease and the number of mutations in a gene, and inference from linkage analysis.'),
(77303, 2013, 'bio', 'XiP: a computational environment to create, extend and share workflows', 'Nagasaki, Masao|Fujita, Andrxc3xa9|Sekiya, Yayoi|Saito, Ayumu|Ikeda, Emi|Li, Chen|Miyano, Satoru', 'Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp|Department of Integrative Genomics, Tohoku Medical Megabank Organization, Tohoku University, Japan. nagasaki@megabank.tohoku.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 4, 'Genomics|Software|Workflow', 'Journal Article', '10.1093/bioinformatics/bts630', '23104885', 'XiP (eXtensible integrative Pipeline) is a flexible, editable and modular environment with a user-friendly interface that does not require previous advanced programming skills to run, construct and edit workflows. XiP allows the construction of workflows by linking components written in both R and Java, the analysis of high-throughput data in grid engine systems and also the development of customized pipelines that can be encapsulated in a package and distributed. XiP already comes with several ready-to-use pipeline flows for the most common genomic and transcriptomic analysis and xe2x88xbc300 computational components.'),
(77304, 2013, 'bio', 'STAR: ultrafast universal RNA-seq aligner', 'Dobin, Alexander|Davis, Carrie A|Schlesinger, Felix|Drenkow, Jorg|Zaleski, Chris|Jha, Sonali|Batut, Philippe|Chaisson, Mark|Gingeras, Thomas R', 'Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu|Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA. dobin@cshl.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 8644, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Genome, Human|Humans|RNA Splicing|Sequence Alignment|Sequence Analysis, RNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts635', '23104886', 'Accurate alignment of high-throughput RNA-seq data is a challenging and yet unsolved problem because of the non-contiguous transcript structure, relatively short read lengths and constantly increasing throughput of the sequencing technologies. Currently available RNA-seq aligners suffer from high mapping error rates, low mapping speed, read length limitation and mapping biases.'),
(77305, 2013, 'bio', 'Introducing Drugster: a comprehensive and fully integrated drug design, lead and structure optimization toolkit', 'Vlachakis, Dimitrios|Tsagrasoulis, Dimosthenis|Megalooikonomou, Vasileios|Kossida, Sophia', 'Bioinformatics and Medical Informatics Team, Biomedical Research Foundation, Academy of Athens, Athens, Greece.|Bioinformatics and Medical Informatics Team, Biomedical Research Foundation, Academy of Athens, Athens, Greece.|Bioinformatics and Medical Informatics Team, Biomedical Research Foundation, Academy of Athens, Athens, Greece.|Bioinformatics and Medical Informatics Team, Biomedical Research Foundation, Academy of Athens, Athens, Greece.', 'Greece|Greece|Greece|Greece', 0, 'Drug Design|Ligands|Pharmaceutical Preparations|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts637', '23104887', 'Drugster is a fully interactive pipeline designed to break the command line barrier and introduce a new user-friendly environment to perform drug design, lead and structure optimization experiments through an efficient combination of the PDB2PQR, Ligbuilder, Gromacs and Dock suites. Our platform features a novel workflow that guides the user through each logical step of the iterative 3D structural optimization setup and drug design process, by providing a seamless interface to all incorporated packages.'),
(77306, 2013, 'bio', 'MycPermCheck: the Mycobacterium tuberculosis permeability prediction tool for small molecules', 'Merget, Benjamin|Zilian, David|Müller, Tobias|Sotriffer, Christoph A', 'Institute of Pharmacy and Food Chemistry, University of Würzburg, D-97074 Würzburg, Germany.|Institute of Pharmacy and Food Chemistry, University of Würzburg, D-97074 Würzburg, Germany.|Institute of Pharmacy and Food Chemistry, University of Würzburg, D-97074 Würzburg, Germany.|Institute of Pharmacy and Food Chemistry, University of Würzburg, D-97074 Würzburg, Germany.', 'Germany|Germany|Germany|Germany', 21, 'Antitubercular Agents|Cell Membrane Permeability|Data Mining|Drug Discovery|Mycobacterium tuberculosis|Software', 'Journal Article', '10.1093/bioinformatics/bts641', '23104888', 'With >8 million new cases in 2010, particularly documented in developing countries, tuberculosis (TB) is still a highly present pandemic and often terminal. This is also due to the emergence of antibiotic-resistant strains (MDR-TB and XDR-TB) of the primary causative TB agent Mycobacterium tuberculosis (MTB). Efforts to develop new effective drugs against MTB are restrained by the unique and largely impermeable composition of the mycobacterial cell wall.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77307, 2013, 'bio', 'SPSens: a software package for stochastic parameter sensitivity analysis of biochemical reaction networks', 'Sheppard, Patrick W|Rathinam, Muruhan|Khammash, Mustafa', 'Department of Biosystems Science and Engineering, ETH-Zurich, Basel 4058, Switzerland.|Department of Biosystems Science and Engineering, ETH-Zurich, Basel 4058, Switzerland.|Department of Biosystems Science and Engineering, ETH-Zurich, Basel 4058, Switzerland.', 'Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Biochemical Phenomena|Monte Carlo Method|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bts642', '23104889', 'SPSens is a software package for the efficient computation of stochastic parameter sensitivities of biochemical reaction networks. Parameter sensitivity analysis is a valuable tool that can be used to study robustness properties, for drug targeting, and many other purposes. However its application to stochastic models has been limited when Monte Carlo methods are required due to extremely high computational costs. SPSens provides efficient, state of the art sensitivity analysis algorithms in a single software package so that sensitivity analysis can be easily performed on stochastic models of biochemical reaction networks. SPSens implements the algorithms in C and estimates sensitivities with respect to both infinitesimal and finite perturbations to system parameters, in many cases reducing variance by orders of magnitude compared to basic methods. Included among the features of SPSens are serial and parallel command line versions, an interface with Matlab, and several example problems.'),
(77308, 2013, 'bio', 'A hidden Markov model to identify combinatorial epigenetic regulation patterns for estrogen receptor xcexb1 target genes', 'Bonneville, Russell|Jin, Victor X', 'Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.|Department of Biomedical Informatics, The Ohio State University, Columbus, OH 43210, USA.', 'United States|United States', 8, 'Antineoplastic Agents, Hormonal|Bayes Theorem|Breast Neoplasms|Chromatin Immunoprecipitation|DNA Methylation|Drug Resistance, Neoplasm|Epigenesis, Genetic|Estrogen Receptor alpha|Female|Gene Expression Regulation, Neoplastic|Genomics|Humans|MCF-7 Cells|Markov Chains|Sequence Analysis, DNA|Tamoxifen', 'Journal Article', '10.1093/bioinformatics/bts639', '23104890', 'Many studies have shown that epigenetic changes, such as altered DNA methylation and histone modifications, are linked to estrogen receptor xcexb1 (ERxcexb1)-positive tumors and disease prognoses. Several recent studies have applied high-throughput technologies such as ChIP-seq and MBD-seq to interrogate the altered architectures of ERxcexb1 regulation in tamoxifen (Tam)-resistant breast cancer cells. However, the details of combinatorial epigenetic regulation of ERxcexb1 target genes in breast cancers with acquired Tam resistance have not yet been fully examined.'),
(77309, 2013, 'bio', 'RIP-chip enrichment analysis', 'Erhard, Florian|Dölken, Lars|Zimmer, Ralf', 'Institut für Informatik, Ludwig-Maximilians-Universität München, 80333 München, Germany. florian.erhard@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, 80333 München, Germany. florian.erhard@bio.ifi.lmu.de|Institut für Informatik, Ludwig-Maximilians-Universität München, 80333 München, Germany. florian.erhard@bio.ifi.lmu.de', 'Germany|Germany|Germany', 9, 'Argonaute Proteins|Gene Expression|Immunoprecipitation|MicroRNAs|Oligonucleotide Array Sequence Analysis|RNA, Messenger|RNA-Binding Proteins', 'Journal Article', '10.1093/bioinformatics/bts631', '23104891', 'RIP-chip is a high-throughput method to identify mRNAs that are targeted by RNA-binding proteins. The protein of interest is immunoprecipitated, and the identity and relative amount of mRNA associated with it is measured on microarrays. Even if a variety of methods is available to analyse microarray data, e.g. to detect differentially regulated genes, the additional experimental steps in RIP-chip require specialized methods. Here, we focus on two aspects of RIP-chip data: First, the efficiency of the immunoprecipitation step performed in the RIP-chip protocol varies in between different experiments introducing bias not existing in standard microarray experiments. This requires an additional normalization step to compare different samples and even technical replicates. Second, in contrast to standard differential gene expression experiments, the distribution of measurements is not normal. We exploit this fact to define a set of biologically relevant genes in a statistically meaningful way.'),
(77310, 2013, 'bio', 'Rare variant discovery and calling by sequencing pooled samples with overlaps', 'Wang, Wenhui|Yin, Xiaolin|Soo Pyon, Yoon|Hayes, Matthew|Li, Jing', 'Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Gene Frequency|Genetic Loci|Humans|Phenotype|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts645', '23104896', 'For many complex traits/diseases, it is believed that rare variants account for some of the missing heritability that cannot be explained by common variants. Sequencing a large number of samples through DNA pooling is a cost-effective strategy to discover rare variants and to investigate their associations with phenotypes. Overlapping pool designs provide further benefit because such approaches can potentially identify variant carriers, which is important for downstream applications of association analysis of rare variants. However, existing algorithms for analysing sequence data from overlapping pools are limited.'),
(77311, 2013, 'bio', 'ADAM: automated data management for research datasets', 'Woodbridge, Mark|Tomlinson, Christopher D|Butcher, Sarah A', 'Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ, UK. m.woodbridge@imperial.ac.uk|Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ, UK. m.woodbridge@imperial.ac.uk|Centre for Integrative Systems Biology and Bioinformatics, Imperial College London, London SW7 2AZ, UK. m.woodbridge@imperial.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Abstracting and Indexing as Topic|Computational Biology|Database Management Systems|Research|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts644', '23109181', 'Existing repositories for experimental datasets typically capture snapshots of data acquired using a single experimental technique and often require manual population and continual curation. We present a storage system for heterogeneous research data that performs dynamic automated indexing to provide powerful search, discovery and collaboration features without the restrictions of a structured repository. ADAM is able to index many commonly used file formats generated by laboratory assays and therefore offers specific advantages to the experimental biology community. However, it is not domain specific and can promote sharing and re-use of working data across scientific disciplines.'),
(77312, 2013, 'bio', 'Dragon TIS Spotter: an Arabidopsis-derived predictor of translation initiation sites in plants', 'Magana-Mora, Arturo|Ashoor, Haitham|Jankovic, Boris R|Kamau, Allan|Awara, Karim|Chowdhary, Rajesh|Archer, John A C|Bajic, Vladimir B', 'King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.|King Abdullah University of Science and Technology (KAUST), Computational Bioscience Research Center, Thuwal 23955-6900, Saudi Arabia.', 'Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Arabia|Saudi Ara', 8, 'Arabidopsis|Genome, Plant|Genomics|Internet|Neural Networks (Computer)|Nucleotide Motifs|Peptide Chain Initiation, Translational|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts638', '23110968', 'In higher eukaryotes, the identification of translation initiation sites (TISs) has been focused on finding these signals in cDNA or mRNA sequences. Using Arabidopsis thaliana (A.t.) information, we developed a prediction tool for signals within genomic sequences of plants that correspond to TISs. Our tool requires only genome sequence, not expressed sequences. Its sensitivity/specificity is for A.t. (90.75%/92.2%), for Vitis vinifera (66.8%/94.4%) and for Populus trichocarpa (81.6%/94.4%), which suggests that our tool can be used in annotation of different plant genomes. We provide a list of features used in our model. Further study of these features may improve our understanding of mechanisms of the translation initiation.'),
(77313, 2013, 'bio', 'MP-T: improving membrane protein alignment for structure prediction', 'Hill, Jamie R|Deane, Charlotte M', 'Department of Statistics, University of Oxford, Oxford, OX1 3TG, UK.|Department of Statistics, University of Oxford, Oxford, OX1 3TG, UK.', 'United Kingdom|United Kingdom', 0, 'Membrane Proteins|Models, Molecular|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/bts640', '23110969', 'Membrane proteins are clinically relevant, yet their crystal structures are rare. Models of membrane proteins are typically built from template structures with low sequence identity to the target sequence, using a sequence-structure alignment as a blueprint. This alignment is usually made with programs designed for use on soluble proteins. Biological membranes have layers of varying hydrophobicity, and membrane proteins have different amino-acid substitution preferences from their soluble counterparts. Here we include these factors into an alignment method to improve alignments and consequently improve membrane protein models.'),
(77314, 2013, 'bio', '13CFLUX2--high-performance software suite for (13)C-metabolic flux analysis', 'Weitzel, Michael|Nöh, Katharina|Dalman, Tolga|Niedenführ, Sebastian|Stute, Birgit|Wiechert, Wolfgang', 'Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.|Institute of Bio- and Geosciences, IBG-1: Biotechnology, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 111, 'Algorithms|Carbon Isotopes|Metabolism|Software', 'Journal Article', '10.1093/bioinformatics/bts646', '23110970', '(13)C-based metabolic flux analysis ((13)C-MFA) is the state-of-the-art method to quantitatively determine in vivo metabolic reaction rates in microorganisms. 13CFLUX2 contains all tools for composing flexible computational (13)C-MFA workflows to design and evaluate carbon labeling experiments. A specially developed XML language, FluxML, highly efficient data structures and simulation algorithms achieve a maximum of performance and effectiveness. Support of multicore CPUs, as well as compute clusters, enables scalable investigations. 13CFLUX2 outperforms existing tools in terms of universality, flexibility and built-in features. Therewith, 13CFLUX2 paves the way for next-generation high-resolution (13)C-MFA applications on the large scale.'),
(77315, 2013, 'bio', 'LOGICOIL--multi-state prediction of coiled-coil oligomeric state', 'Vincent, Thomas L|Green, Peter J|Woolfson, Derek N', 'School of Chemistry, University of Bristol, Bristol BS8 1TS, UK.|School of Chemistry, University of Bristol, Bristol BS8 1TS, UK.|School of Chemistry, University of Bristol, Bristol BS8 1TS, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Bayes Theorem|Protein Multimerization|Protein Structure, Secondary|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bts648', '23129295', 'The coiled coil is a ubiquitous xcexb1-helical protein-structure domain that directs and facilitates protein-protein interactions in a wide variety of biological processes. At the protein-sequence level, the coiled coil is readily recognized via a conspicuous heptad repeat of hydrophobic and polar residues. However, structurally coiled coils are more complicated, existing in a wide range of oligomer states and topologies. As a consequence, predicting these various states from sequence remains an unmet challenge.'),
(77316, 2013, 'bio', 'PBSIM: PacBio reads simulator--toward accurate genome assembly', 'Ono, Yukiteru|Asai, Kiyoshi|Hamada, Michiaki', 'Information and Mathematical Science and Bioinformatics Co., Ltd., Toshima-ku, Tokyo 170-0013, Japan.|Information and Mathematical Science and Bioinformatics Co., Ltd., Toshima-ku, Tokyo 170-0013, Japan.|Information and Mathematical Science and Bioinformatics Co., Ltd., Toshima-ku, Tokyo 170-0013, Japan.', 'Japan|Japan|Japan', 0, 'Genomics|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts649', '23129296', 'PacBio sequencers produce two types of characteristic reads (continuous long reads: long and high error rate and circular consensus sequencing: short and low error rate), both of which could be useful for de novo assembly of genomes. Currently, there is no available simulator that targets the specific generation of PacBio libraries.'),
(77317, 2013, 'bio', 'DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data', 'Pacini, Clare|Iorio, Francesco|Gonçalves, Emanuel|Iskar, Murat|Klabunde, Thomas|Bork, Peer|Saez-Rodriguez, Julio', 'European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.|European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Cambridge, UK CB10 1SD.', '-|-|-|-|-|-|-', 47, 'Drug Repositioning|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts656', '23129297', 'Drug versus Disease (DvD) provides a pipeline, available through R or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray repositories. Negatively correlated profiles can be used to generate hypotheses of drug-repurposing, whereas positively correlated profiles may be used to infer side effects of drugs. DvD allows users to compare drug and disease signatures with dynamic access to databases Array Express, Gene Expression Omnibus and data from the Connectivity Map.'),
(77318, 2013, 'bio', 'Binary Interval Search: a scalable algorithm for counting interval intersections', 'Layer, Ryan M|Skadron, Kevin|Robins, Gabriel|Hall, Ira M|Quinlan, Aaron R', 'Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA.|Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA.|Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA.|Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA.|Department of Computer Science, University of Virginia, Charlottesville, VA 22904, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Genomics|Monte Carlo Method|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts652', '23129298', 'The comparison of diverse genomic datasets is fundamental to understand genome biology. Researchers must explore many large datasets of genome intervals (e.g. genes, sequence alignments) to place their experimental results in a broader context and to make new discoveries. Relationships between genomic datasets are typically measured by identifying intervals that intersect, that is, they overlap and thus share a common genome interval. Given the continued advances in DNA sequencing technologies, efficient methods for measuring statistically significant relationships between many sets of genomic features are crucial for future discovery.'),
(77319, 2013, 'bio', 'Pathway hunting by random survival forests', 'Chen, Xi|Ishwaran, Hemant', 'Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA. xi.steven.chen@gmail.com|Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA. xi.steven.chen@gmail.com', 'United States|United States', 21, 'Algorithms|Colonic Neoplasms|Female|Humans|Ovarian Neoplasms|Signal Transduction|Survival Analysis|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts643', '23129299', 'Pathway or gene set analysis has been widely applied to genomic data. Many current pathway testing methods use univariate test statistics calculated from individual genomic markers, which ignores the correlations and interactions between candidate markers. Random forests-based pathway analysis is a promising approach for incorporating complex correlation and interaction patterns, but one limitation of previous approaches is that pathways have been considered separately, thus pathway cross-talk information was not considered.'),
(77320, 2013, 'bio', 'MetaGeneTack: ab initio detection of frameshifts in metagenomic sequences', 'Tang, Shiyuyun|Antonov, Ivan|Borodovsky, Mark', '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', 0, 'Algorithms|Frameshift Mutation|Metagenomics|Models, Statistical|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts636', '23129300', 'Frameshift (FS) prediction is important for analysis and biological interpretation of metagenomic sequences. Since a genomic context of a short metagenomic sequence is rarely known, there is not enough data available to estimate parameters of species-specific statistical models of protein-coding and non-coding regions. The challenge of ab initio FS detection is, therefore, two fold: (i) to find a way to infer necessary model parameters and (ii) to identify positions of frameshifts (if any). Here we describe a new tool, MetaGeneTack, which uses a heuristic method to estimate parameters of sequence models used in the FS detection algorithm. It is shown on multiple test sets that the MetaGeneTack FS detection performance is comparable or better than the one of earlier developed program FragGeneScan.'),
(77321, 2013, 'bio', 'HD-CNV: hotspot detector for copy number variants', 'Butler, Jenna L|Osborne Locke, Marjorie Elizabeth|Hill, Kathleen A|Daley, Mark', 'Department of Computer Science, The University of Western Ontario, London, ON, Canada N6A 3K7. jcamer7@uwo.ca|Department of Computer Science, The University of Western Ontario, London, ON, Canada N6A 3K7. jcamer7@uwo.ca|Department of Computer Science, The University of Western Ontario, London, ON, Canada N6A 3K7. jcamer7@uwo.ca|Department of Computer Science, The University of Western Ontario, London, ON, Canada N6A 3K7. jcamer7@uwo.ca', 'Canada|Canada|Canada|Canada', 0, 'DNA Copy Number Variations|Genome, Human|Genomics|Humans|Karyotype|Software', 'Journal Article', '10.1093/bioinformatics/bts650', '23129301', 'Copy number variants (CNVs) are a major source of genetic variation. Comparing CNVs between samples is important in elucidating their potential effects in a wide variety of biological contexts. HD-CNV (hotspot detector for copy number variants) is a tool for downstream analysis of previously identified CNV regions from multiple samples, and it detects recurrent regions by finding cliques in an interval graph generated from the input. It creates a unique graphical representation of the data, as well as summary spreadsheets and UCSC (University of California, Santa Cruz) Genome Browser track files. The interval graph, when viewed with other software or by automated graph analysis, is useful in identifying genomic regions of interest for further study.'),
(77322, 2012, 'bio', 'FOLD-EM: automated fold recognition in medium- and low-resolution (4-15 Å) electron density maps', 'Saha, Mitul|Morais, Marc C', 'Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 7555-0647, USA. mitul@cs.stanford.edu|Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, 301 University Boulevard, Galveston, TX 7555-0647, USA. mitul@cs.stanford.edu', 'United States|United States', 0, 'Algorithms|Chaperonin 60|Cryoelectron Microscopy|Databases, Protein|Electrons|Macromolecular Substances|Models, Molecular|Molecular Docking Simulation|Protein Folding|Protein Structure, Tertiary|Software|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts616', '23131460', 'Owing to the size and complexity of large multi-component biological assemblies, the most tractable approach to determining their atomic structure is often to fit high-resolution radiographic or nuclear magnetic resonance structures of isolated components into lower resolution electron density maps of the larger assembly obtained using cryo-electron microscopy (cryo-EM). This hybrid approach to structure determination requires that an atomic resolution structure of each component, or a suitable homolog, is available. If neither is available, then the amount of structural information regarding that component is limited by the resolution of the cryo-EM map. However, even if a suitable homolog cannot be identified using sequence analysis, a search for structural homologs should still be performed because structural homology often persists throughout evolution even when sequence homology is undetectable, As macromolecules can often be described as a collection of independently folded domains, one way of searching for structural homologs would be to systematically fit representative domain structures from a protein domain database into the medium/low resolution cryo-EM map and return the best fits. Taken together, the best fitting non-overlapping structures would constitute a mosaic backbone model of the assembly that could aid map interpretation and illuminate biological function.'),
(77323, 2013, 'bio', 'iBAG: integrative Bayesian analysis of high-dimensional multiplatform genomics data', 'Wang, Wenting|Baladandayuthapani, Veerabhadran|Morris, Jeffrey S|Broom, Bradley M|Manyam, Ganiraju|Do, Kim-Anh', 'Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Biostatistics, The University of Texas, MD Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States', 62, 'Bayes Theorem|Brain Neoplasms|DNA Methylation|Gene Expression Profiling|Genomics|Glioblastoma|Humans|Models, Statistical', 'Journal Article', '10.1093/bioinformatics/bts655', '23142963', 'Analyzing data from multi-platform genomics experiments combined with patients clinical outcomes helps us understand the complex biological processes that characterize a disease, as well as how these processes relate to the development of the disease. Current data integration approaches are limited in that they do not consider the fundamental biological relationships that exist among the data obtained from different platforms. Statistical Model: We propose an integrative Bayesian analysis of genomics data (iBAG) framework for identifying important genes/biomarkers that are associated with clinical outcome. This framework uses hierarchical modeling to combine the data obtained from multiple platforms into one model.'),
(77324, 2013, 'bio', 'Density parameter estimation for finding clusters of homologous proteins--tracing actinobacterial pathogenicity lifestyles', 'Röttger, Richard|Kalaghatgi, Prabhav|Sun, Peng|Soares, Siomar de Castro|Azevedo, Vasco|Wittkop, Tobias|Baumbach, Jan', 'Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de|Max Planck Institute for Informatics, Saarland University, 66123 Saarbrücken, Germany. roettger@mpi-inf.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Actinobacteria|Algorithms|Bacterial Proteins|Cluster Analysis|Genome, Bacterial|Models, Genetic|Phylogeny|Sequence Alignment|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/bts653', '23142964', 'Homology detection is a long-standing challenge in computational biology. To tackle this problem, typically all-versus-all BLAST results are coupled with data partitioning approaches resulting in clusters of putative homologous proteins. One of the main problems, however, has been widely neglected: all clustering tools need a density parameter that adjusts the number and size of the clusters. This parameter is crucial but hard to estimate without gold standard data at hand. Developing a gold standard, however, is a difficult and time consuming task. Having a reliable method for detecting clusters of homologous proteins between a huge set of species would open opportunities for better understanding the genetic repertoire of bacteria with different lifestyles.'),
(77325, 2013, 'bio', 'DLocalMotif: a discriminative approach for discovering local motifs in protein sequences', 'Mehdi, Ahmed M|Sehgal, Muhammad Shoaib B|Kobe, Bostjan|Bailey, Timothy L|Bodén, Mikael', 'Institute for Molecular Bioscience, The University of Queensland, Australia.|Institute for Molecular Bioscience, The University of Queensland, Australia.|Institute for Molecular Bioscience, The University of Queensland, Australia.|Institute for Molecular Bioscience, The University of Queensland, Australia.|Institute for Molecular Bioscience, The University of Queensland, Australia.', 'Australia|Australia|Australia|Australia|Australia', 7, 'Algorithms|Amino Acid Motifs|Protein Sorting Signals|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bts654', '23142965', 'Local motifs are patterns of DNA or protein sequences that occur within a sequence interval relative to a biologically defined anchor or landmark. Current protein motif discovery methods do not adequately consider such constraints to identify biologically significant motifs that are only weakly over-represented but spatially confined. Using negatives, i.e. sequences known to not contain a local motif, can further increase the specificity of their discovery.'),
(77326, 2013, 'bio', 'NetCAD: a network analysis tool for coronary artery disease-associated PPI network', 'Ren, Guomin|Liu, Zhihua', 'Department of Computational Biology and Bioinformatics, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.|Department of Computational Biology and Bioinformatics, Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100193, China.', 'China|China', 0, 'Coronary Artery Disease|Humans|Protein Interaction Mapping|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts666', '23162052', 'The systematic and unbiased charting of protein-protein interaction (PPI) networks relevant to health or diseases has become an important and burgeoning challenge in systems biology. Further, current reports have supported that good correlation exists between the topological properties and biological function of protein nodes in networks. Coronary artery disease (CAD, also called coronary heart disease) is the most common type of heart disease worldwide. Traditional approaches of studying individual gene or protein have shown their weakness in such complex disease. Here, we provide NetCAD, a web-based tool for systematic investigation of CAD-specific proteins in human PPI network. The features of NetCAD includes the following: proposing a novel method combining biological principles and graph theory, quantified topological analysis tools, build-in PPI information database consolidated from major public databases, creating CAD-associated subnetwork and visualizing network graph with good visual effects. NetCAD may provide important biological information for uncovering the molecular mechanisms and potential targets for therapies of CAD, which could not be found merely through molecular biology methods.'),
(77327, 2013, 'bio', 'PASS-bis: a bisulfite aligner suitable for whole methylome analysis of Illumina and SOLiD reads', 'Campagna, Davide|Telatin, Andrea|Forcato, Claudio|Vitulo, Nicola|Valle, Giorgio', 'CRIBI Biotechnology Centre, Università di Padova, 35131 Padova, Italy.|CRIBI Biotechnology Centre, Università di Padova, 35131 Padova, Italy.|CRIBI Biotechnology Centre, Università di Padova, 35131 Padova, Italy.|CRIBI Biotechnology Centre, Università di Padova, 35131 Padova, Italy.|CRIBI Biotechnology Centre, Università di Padova, 35131 Padova, Italy.', 'Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Color|DNA Methylation|Genomics|Humans|Sequence Alignment|Sequence Analysis, DNA|Sulfites', 'Journal Article', '10.1093/bioinformatics/bts675', '23162053', 'The sequencing of bisulfite-treated DNA (Bi-Seq) is becoming a gold standard for methylation studies. The mapping of Bi-Seq reads is complex and requires special alignment algorithms. This problem is particularly relevant for SOLiD color space, where the bisulfite conversion C/T changes two adjacent colors into 16 possible combinations. Here, we present an algorithm that efficiently aligns Bi-Seq reads obtained either from SOLiD or Illumina. An accompanying methylation-caller program creates a genomic view of methylated and unmethylated Cs on both DNA strands.'),
(77328, 2013, 'bio', 'mzMatch-ISO: an R tool for the annotation and relative quantification of isotope-labelled mass spectrometry data', 'Chokkathukalam, Achuthanunni|Jankevics, Andris|Creek, Darren J|Achcar, Fiona|Barrett, Michael P|Breitling, Rainer', 'College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.|College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.|College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.|College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.|College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.|College of Medical Veterinary and Life Sciences, Institute of Molecular Cell and Systems Biology, University of Glasgow, Glasgow G12 8QQ, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Carbon Isotopes|Chromatography, Liquid|Mass Spectrometry|Metabolome|Metabolomics|Software|Trypanosoma brucei brucei', 'Journal Article', '10.1093/bioinformatics/bts674', '23162054', 'Stable isotope-labelling experiments have recently gained increasing popularity in metabolomics studies, providing unique insights into the dynamics of metabolic fluxes, beyond the steady-state information gathered by routine mass spectrometry. However, most liquid chromatography-mass spectrometry data analysis software lacks features that enable automated annotation and relative quantification of labelled metabolite peaks. Here, we describe mzMatch-ISO, a new extension to the metabolomics analysis pipeline mzMatch.R.'),
(77329, 2013, 'bio', 'Drug-target interaction prediction by learning from local information and neighbors', 'Mei, Jian-Ping|Kwoh, Chee-Keong|Yang, Peng|Li, Xiao-Li|Zheng, Jie', 'Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. jpmei@ntu.edu.sg|Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. jpmei@ntu.edu.sg|Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. jpmei@ntu.edu.sg|Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. jpmei@ntu.edu.sg|Bioinformatics Research Centre, School of Computer Engineering, Nanyang Technological University, 50 Nanyang Avenue, Singapore 639798. jpmei@ntu.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|Artificial Intelligence|Drug Discovery|Models, Theoretical|Pharmaceutical Preparations|Proteins|Receptors, Cytoplasmic and Nuclear', 'Journal Article', '10.1093/bioinformatics/bts670', '23162055', 'In silico methods provide efficient ways to predict possible interactions between drugs and targets. Supervised learning approach, bipartite local model (BLM), has recently been shown to be effective in prediction of drug-target interactions. However, for drug-candidate compounds or target-candidate proteins that currently have no known interactions available, its pure local model is not able to be learned and hence BLM may fail to make correct prediction when involving such kind of new candidates.'),
(77330, 2013, 'bio', 'DoseSim: a tool for pharmacokinetic/pharmacodynamic analysis and dose reconstruction', 'Reisfeld, Brad|Ivy, Jaime H|Lyons, Michael A|Wright, Jesse M|Rogers, Justin L|Mayeno, Arthur N', 'Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu|Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu|Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu|Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu|Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu|Department of Chemical and Biological Engineering, School of Biomedical Engineering, Colorado State University, Fort Collins, CO 80523, USA. brad.reisfeld@colostate.edu', 'United States|United States|United States|United States|United States|United States', 2, 'Biomarkers|Models, Biological|Pharmacokinetics|Pharmacological Phenomena|Software|Tissue Distribution', 'Journal Article', '10.1093/bioinformatics/bts671', '23162056', 'Assessing and improving the safety of chemicals and the efficacy of drugs depends on an understanding of the biodistribution, clearance and biological effects of the chemical(s) of interest. A promising methodology for the prediction of these phenomena is physiologically based pharmacokinetic/pharmacodynamic modeling, which centers on the prediction of chemical absorption, distribution, metabolism and excretion (pharmacokinetics) and the biological effects (pharmacodynamics) of the chemical on the organism. Strengths of this methodology include modeling across multiple scales of biological organization and facilitate the extrapolation of results across routes of exposure, dosing levels and species. It is also useful as the foundation for tools to (i) predict biomarker levels (concentrations of chemical species found in the body that indicate exposure to a foreign chemical), given a chemical dose or exposure, (ii) reconstruct a dose, given the levels of relevant biomarkers, and (iii) estimate population variability. Despite the importance and promise of physiologically based pharmacokinetic /pharmacodynamics-based approaches to forward and reverse dosimetry, there is currently a lack of user-friendly, freely available implementations that are accessible and useful to a broad range of users. DoseSim was developed to begin to fill this gap.'),
(77331, 2013, 'bio', 'Largenet2: an object-oriented programming library for simulating large adaptive networks', 'Zschaler, Gerd|Gross, Thilo', 'Max-Planck-Institut für Physik komplexer Systeme, 01187 Dresden, Germany. gerd@biond.org|Max-Planck-Institut für Physik komplexer Systeme, 01187 Dresden, Germany. gerd@biond.org', 'Germany|Germany', 0, 'Computer Simulation|Epidemiologic Studies|Software', 'Journal Article', '10.1093/bioinformatics/bts663', '23162057', 'The largenet2 C++ library provides an infrastructure for the simulation of large dynamic and adaptive networks with discrete node and link states.'),
(77332, 2013, 'bio', 'VirusSeq: software to identify viruses and their integration sites using next-generation sequencing of human cancer tissue', 'Chen, Yunxin|Yao, Hui|Thompson, Erika J|Tannir, Nizar M|Weinstein, John N|Su, Xiaoping', 'Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.|Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA.', 'United States|United States|United States|United States|United States|United States', 93, 'Algorithms|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Sequence Analysis, RNA|Software|Virus Integration|Viruses', 'Journal Article', '10.1093/bioinformatics/bts665', '23162058', 'We developed a new algorithmic method, VirusSeq, for detecting known viruses and their integration sites in the human genome using next-generation sequencing data. We evaluated VirusSeq on whole-transcriptome sequencing (RNA-Seq) data of 256 human cancer samples from The Cancer Genome Atlas. Using these data, we showed that VirusSeq accurately detects the known viruses and their integration sites with high sensitivity and specificity. VirusSeq can also perform this function using whole-genome sequencing data of human tissue.'),
(77333, 2013, 'bio', 'VAGUE: a graphical user interface for the Velvet assembler', 'Powell, David R|Seemann, Torsten', 'Victorian Bioinformatics Consortium, Monash University, Clayton 3800, Australia.|Victorian Bioinformatics Consortium, Monash University, Clayton 3800, Australia.', 'Australia|Australia', 9, 'Computer Graphics|Genomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts664', '23162059', 'Velvet is a popular open-source de novo genome assembly software tool, which is run from the Unix command line. Most of the problems experienced by new users of Velvet revolve around constructing syntactically and semantically correct command lines, getting input files into acceptable formats and assessing the output. Here, we present Velvet Assembler Graphical User Environment (VAGUE), a multi-platform graphical front-end for Velvet. VAGUE aims to make sequence assembly accessible to a wider audience and to facilitate better usage amongst existing users of Velvet.'),
(77334, 2013, 'bio', 'A system for exact and approximate genetic linkage analysis of SNP data in large pedigrees', 'Silberstein, Mark|Weissbrod, Omer|Otten, Lars|Tzemach, Anna|Anisenia, Andrei|Shtark, Oren|Tuberg, Dvir|Galfrin, Eddie|Gannon, Irena|Shalata, Adel|Borochowitz, Zvi U|Dechter, Rina|Thompson, Elizabeth|Geiger, Dan', 'Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.|Department of Computer Science, Technion-Israel Institute of Technology, Haifa, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Cluster Analysis|Genetic Linkage|Haplotypes|Humans|Markov Chains|Monte Carlo Method|Pedigree|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts658', '23162081', 'The use of dense single nucleotide polymorphism (SNP) data in genetic linkage analysis of large pedigrees is impeded by significant technical, methodological and computational challenges. Here we describe Superlink-Online SNP, a new powerful online system that streamlines the linkage analysis of SNP data. It features a fully integrated flexible processing workflow comprising both well-known and novel data analysis tools, including SNP clustering, erroneous data filtering, exact and approximate LOD calculations and maximum-likelihood haplotyping. The system draws its power from thousands of CPUs, performing data analysis tasks orders of magnitude faster than a single computer. By providing an intuitive interface to sophisticated state-of-the-art analysis tools coupled with high computing capacity, Superlink-Online SNP helps geneticists unleash the potential of SNP data for detecting disease genes.'),
(77335, 2013, 'bio', 'Stability analysis of phylogenetic trees', 'Sheikh, Saad I|Kahveci, Tamer|Ranka, Sanjay|Gordon Burleigh, J', 'Department of Computer and Information Science and Engineering, University of Florida, FL 32611, USA. sheikh@cise.ufl.edu|Department of Computer and Information Science and Engineering, University of Florida, FL 32611, USA. sheikh@cise.ufl.edu|Department of Computer and Information Science and Engineering, University of Florida, FL 32611, USA. sheikh@cise.ufl.edu|Department of Computer and Information Science and Engineering, University of Florida, FL 32611, USA. sheikh@cise.ufl.edu', 'United States|United States|United States|United States', 5, 'Algorithms|Animals|Mammals|Phylogeny|Plants|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts657', '23162082', 'Phylogenetics, or reconstructing the evolutionary relationships of organisms, is critical for understanding evolution. A large number of heuristic algorithms for phylogenetics have been developed, some of which enable estimates of trees with tens of thousands of taxa. Such trees may not be robust, as small changes in the input data can cause major differences in the optimal topology. Tools that can assess the quality and stability of phylogenetic tree estimates and identify the most reliable parts of the tree are needed.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77336, 2013, 'bio', 'PTID: an integrated web resource and computational tool for agrochemical discovery', 'Gong, Jiayu|Liu, Xiaofeng|Cao, Xianwen|Diao, Yanyan|Gao, Daqi|Li, Honglin|Qian, Xuhong', 'School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.|School of Information Science and Engineering, Shanghai Key Laboratory of Chemical Biology, Shanghai Key Laboratory of New Drug Design, Institute of Pharmaceuticals and Pesticides, School of Pharmacy, East China University of Science and Technology, Shanghai 200237, China.', 'China|China|China|China|China|China|China', 0, 'Agrochemicals|Data Mining|Databases, Chemical|Drug Discovery|Internet|Pesticides|Proteins|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts651', '23162083', 'Although in silico drug discovery approaches are crucial for the development of pharmaceuticals, their potential advantages in agrochemical industry have not been realized. The challenge for computer-aided methods in agrochemical arena is a lack of sufficient information for both pesticides and their targets. Therefore, it is important to establish such knowledge repertoire that contains comprehensive pesticides profiles, which include physicochemical properties, environmental fates, toxicities and mode of actions. Here, we present an integrated platform called Pesticide-Target interaction database (PTID), which comprises a total of 1347 pesticides with rich annotation of ecotoxicological and toxicological data as well as 13 738 interactions of pesticide-target and 4245 protein terms via text mining. Additionally, through the integration of ChemMapper, an in-house computational approach to polypharmacology, PTID can be used as a computational platform to identify pesticides targets and design novel agrochemical products.'),
(77337, 2013, 'bio', 'An application of a relational database system for high-throughput prediction of elemental compositions from accurate mass values', 'Sakurai, Nozomu|Ara, Takeshi|Kanaya, Shigehiko|Nakamura, Yukiko|Iijima, Yoko|Enomoto, Mitsuo|Motegi, Takeshi|Aoki, Koh|Suzuki, Hideyuki|Shibata, Daisuke', 'Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp|Department of Biotechnology Research, Kazusa DNA Research Institute, Kisarazu, Chiba 292-0818, Japan. sakurai@kazusa.or.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Databases, Chemical|Mass Spectrometry|Metabolomics', 'Journal Article', '10.1093/bioinformatics/bts660', '23162084', 'High-accuracy mass values detected by high-resolution mass spectrometry analysis enable prediction of elemental compositions, and thus are used for metabolite annotations in metabolomic studies. Here, we report an application of a relational database to significantly improve the rate of elemental composition predictions. By searching a database of pre-calculated elemental compositions with fixed kinds and numbers of atoms, the approach eliminates redundant evaluations of the same formula that occur in repeated calculations with other tools. When our approach is compared with HR2, which is one of the fastest tools available, our database search times were at least 109 times shorter than those of HR2. When a solid-state drive (SSD) was applied, the search time was 488 times shorter at 5 ppm mass tolerance and 1833 times at 0.1 ppm. Even if the search by HR2 was performed with 8 threads in a high-spec Windows 7 PC, the database search times were at least 26 and 115 times shorter without and with the SSD. These improvements were enhanced in a low spec Windows XP PC. We constructed a web service MFSearcher to query the database in a RESTful manner.'),
(77338, 2013, 'bio', 'Bridging the scales: semantic integration of quantitative SBML in graphical multi-cellular models and simulations with EPISIM and COPASI', 'Sütterlin, Thomas|Kolb, Christoph|Dickhaus, Hartmut|Jäger, Dirk|Grabe, Niels', 'Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, 69120 Heidelberg, Germany.|Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, 69120 Heidelberg, Germany.|Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, 69120 Heidelberg, Germany.|Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, 69120 Heidelberg, Germany.|Department of Medical Oncology, National Center for Tumor Diseases, University Hospital Heidelberg, 69120 Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 31, 'Cell Cycle|Cell Differentiation|Computer Graphics|Computer Simulation|Epidermal Cells|Humans|Models, Biological|Semantics|Software|Systems Biology|Workflow', 'Journal Article', '10.1093/bioinformatics/bts659', '23162085', 'Biological reality can in silico only be comprehensively represented in multi-scaled models. To this end, cell behavioural models addressing the multi-cellular level have to be semantically linked with mechanistic molecular models. These requirements have to be met by flexible software workflows solving the issues of different time scales, inter-model variable referencing and flexible sub-model embedding.'),
(77339, 2013, 'bio', 'Visualization and Phospholipid Identification (VaLID): online integrated search engine capable of identifying and visualizing glycerophospholipids with given mass', 'Blanchard, Alexandre P|McDowell, Graeme S V|Valenzuela, Nico|Xu, Hongbin|Gelbard, Sarah|Bertrand, Martin|Slater, Gary W|Figeys, Daniel|Fai, Stephen|Bennett, Steffany A L', 'Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.|Ottawa Institute of Systems Biology, CIHR Training Program in Neurodegenerative Lipidomics, Biochemistry, Microbiology, and Immunology, University of Ottawa, Ontario K1H 8M5, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Computer Graphics|Databases, Chemical|Glycerophospholipids|Internet|Mass Spectrometry|Proteomics|Search Engine', 'Journal Article', '10.1093/bioinformatics/bts662', '23162086', 'Establishing phospholipid identities in large lipidomic datasets is a labour-intensive process. Where genomics and proteomics capitalize on sequence-based signatures, glycerophospholipids lack easily definable molecular fingerprints. Carbon chain length, degree of unsaturation, linkage, and polar head group identity must be calculated from mass to charge (m/z) ratios under defined mass spectrometry (MS) conditions. Given increasing MS sensitivity, many m/z values are not represented in existing prediction engines. To address this need, Visualization and Phospholipid Identification is a web-based application that returns all theoretically possible phospholipids for any m/z value and MS condition. Visualization algorithms produce multiple chemical structure files for each species. Curated lipids detected by the Canadian Institutes of Health Research Training Program in Neurodegenerative Lipidomics are provided as high-resolution structures.'),
(77340, 2013, 'bio', 'Scaffolding low quality genomes using orthologous protein sequences', 'Li, Yang I|Copley, Richard R', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. yang.li@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK. yang.li@well.ox.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Animals|Ciona intestinalis|Contig Mapping|Drosophila melanogaster|Fishes|Genomics|High-Throughput Nucleotide Sequencing|Humans|Proteins|Sequence Analysis, DNA|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/bts661', '23162087', 'The ready availability of next-generation sequencing has led to a situation where it is easy to produce very fragmentary genome assemblies. We present a pipeline, SWiPS (Scaffolding With Protein Sequences), that uses orthologous proteins to improve low quality genome assemblies. The protein sequences are used as guides to scaffold existing contigs, while simultaneously allowing the gene structure to be predicted by homology.'),
(77341, 2013, 'bio', 'Intron-centric estimation of alternative splicing from RNA-seq data', 'Pervouchine, Dmitri D|Knowles, David G|Guigó, Roderic', 'Centre de Regulació Genòmica, 08003 Barcelona, Spain. dp@crg.eu|Centre de Regulació Genòmica, 08003 Barcelona, Spain. dp@crg.eu|Centre de Regulació Genòmica, 08003 Barcelona, Spain. dp@crg.eu', 'Spain|Spain|Spain', 33, 'Alternative Splicing|Exons|High-Throughput Nucleotide Sequencing|Humans|Introns|RNA Splice Sites|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts678', '23172860', 'Novel technologies brought in unprecedented amounts of high-throughput sequencing data along with great challenges in their analysis and interpretation. The percent-spliced-in (PSI, ) metric estimates the incidence of single-exon-skipping events and can be computed directly by counting reads that align to known or predicted splice junctions. However, the majority of human splicing events are more complex than single-exon skipping.'),
(77342, 2013, 'bio', 'DOOSS: a tool for visual analysis of data overlaid on secondary structures', 'Golden, Michael|Martin, Darren', 'Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town 4579, South Africa. michaelgolden0@gmail.com|Computational Biology Group, Institute of Infectious Diseases and Molecular Medicine, University of Cape Town, Cape Town 4579, South Africa. michaelgolden0@gmail.com', 'South Africa|South Africa', 0, 'Base Sequence|Computer Graphics|Genome, Viral|HIV-1|Humans|Nucleic Acid Conformation|Software', 'Journal Article', '10.1093/bioinformatics/bts667', '23172861', 'DOOSS (Data Overlaid On Secondary Structures) is a tool for visualizing annotated secondary structures of large single-stranded nucleotide sequences (such as full-length virus genomes). The purpose of this tool is to assist investigators in evaluating the biological relevance of secondary structures within particular sequences.'),
(77343, 2013, 'bio', 'Non-redundant compendium of human ncRNA genes in GeneCards', 'Belinky, Frida|Bahir, Iris|Stelzer, Gil|Zimmerman, Shahar|Rosen, Naomi|Nativ, Noam|Dalah, Irina|Iny Stein, Tsippi|Rappaport, Noa|Mituyama, Toutai|Safran, Marilyn|Lancet, Doron', 'Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il|Department of Molecular Genetics, The Weizmann Institute of Science, Rehovot 76100, Israel. Frida.Belinky@weizmann.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 35, 'Algorithms|Cluster Analysis|Databases, Genetic|Genes|Genome, Human|Genomics|Humans|Internet|Molecular Sequence Annotation|RNA, Untranslated', 'Journal Article', '10.1093/bioinformatics/bts676', '23172862', 'Non-coding RNA (ncRNA) genes are increasingly acknowledged for their importance in the human genome. However, there is no comprehensive non-redundant database for all such human genes.'),
(77344, 2013, 'bio', 'An empirical Bayes approach for analysis of diverse periodic trends in time-course gene expression data', 'Kocak, Mehmet|George, E Olusegun|Pyne, Saumyadipta|Pounds, Stanley', 'Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN 38105, USA. mkocak1@uthsc.edu|Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN 38105, USA. mkocak1@uthsc.edu|Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN 38105, USA. mkocak1@uthsc.edu|Department of Preventive Medicine, University of Tennessee Health Sciences Center, Memphis, TN 38105, USA. mkocak1@uthsc.edu', 'United States|United States|United States|United States', 3, 'Algorithms|Bayes Theorem|Cell Cycle|Gene Expression|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Periodicity|Schizosaccharomyces|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/bts672', '23172863', 'There is a substantial body of works in the biology literature that seeks to characterize the cyclic behavior of genes during cell division. Gene expression microarrays made it possible to measure the expression profiles of thousands of genes simultaneously in time-course experiments to assess changes in the expression levels of genes over time. In this context, the commonly used procedures for testing include the permutation test by de Lichtenberg et al. and the Fishers G-test, both of which are designed to evaluate periodicity against noise. However, it is possible that a gene of interest may have expression that is neither cyclic nor just noise. Thus, there is a need for a new test for periodicity that can identify cyclic patterns against not only noise but also other non-cyclic patterns such as linear, quadratic or higher order polynomial patterns.'),
(77345, 2013, 'bio', 'Scribl: an HTML5 Canvas-based graphics library for visualizing genomic data over the web', 'Miller, Chase A|Anthony, Jon|Meyer, Michelle M|Marth, Gabor', 'Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.', 'United States|United States|United States|United States', 19, 'Chromosomes, Human|Computer Graphics|Genomics|Humans|Internet|Software', 'Journal Article', '10.1093/bioinformatics/bts677', '23172864', 'High-throughput biological research requires simultaneous visualization as well as analysis of genomic data, e.g. read alignments, variant calls and genomic annotations. Traditionally, such integrative analysis required desktop applications operating on locally stored data. Many current terabyte-size datasets generated by large public consortia projects, however, are already only feasibly stored at specialist genome analysis centers. As even small laboratories can afford very large datasets, local storage and analysis are becoming increasingly limiting, and it is likely that most such datasets will soon be stored remotely, e.g. in the cloud. These developments will require web-based tools that enable users to access, analyze and view vast remotely stored data with a level of sophistication and interactivity that approximates desktop applications. As rapidly dropping cost enables researchers to collect data intended to answer questions in very specialized contexts, developers must also provide software libraries that empower users to implement customized data analyses and data views for their particular application. Such specialized, yet lightweight, applications would empower scientists to better answer specific biological questions than possible with general-purpose genome browsers currently available.'),
(77346, 2013, 'bio', 'High-throughput microbial population genomics using the Cortex variation assembler', 'Iqbal, Zamin|Turner, Isaac|McVean, Gil', 'Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford, OX3 7BN, UK. zam@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford, OX3 7BN, UK. zam@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, Roosevelt Drive, Oxford, OX3 7BN, UK. zam@well.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 25, 'Genetic Variation|Genomics|Genotype|INDEL Mutation|Metagenomics|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts673', '23172865', 'We have developed a software package, Cortex, designed for the analysis of genetic variation by de novo assembly of multiple samples. This allows direct comparison of samples without using a reference genome as intermediate and incorporates discovery and genotyping of single-nucleotide polymorphisms, indels and larger events in a single framework. We introduce pipelines which simplify the analysis of microbial samples and increase discovery power, these also enable the construction of a graph of known sequence and variation in a species, against which new samples can be compared rapidly. We demonstrate the ease-of-use and power by reproducing the results of studies using both long and short reads.'),
(77347, 2013, 'bio', 'A beta-mixture quantile normalization method for correcting probe design bias in Illumina Infinium 450 k DNA methylation data', 'Teschendorff, Andrew E|Marabita, Francesco|Lechner, Matthias|Bartlett, Thomas|Tegner, Jesper|Gomez-Cabrero, David|Beck, Stephan', 'Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk|Statistical Genomics Group, UCL Cancer Institute, University College London, London WC1E 6BT, UK. a.teschendorff@ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 611, 'Algorithms|DNA Methylation|Neoplasms|Normal Distribution|Nucleic Acid Probes|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/bts680', '23175756', 'The Illumina Infinium 450 k DNA Methylation Beadchip is a prime candidate technology for Epigenome-Wide Association Studies (EWAS). However, a difficulty associated with these beadarrays is that probes come in two different designs, characterized by widely different DNA methylation distributions and dynamic range, which may bias downstream analyses. A key statistical issue is therefore how best to adjust for the two different probe designs.'),
(77348, 2013, 'bio', 'An effective framework for reconstructing gene regulatory networks from genetical genomics data', 'Flassig, R J|Heise, S|Sundmacher, K|Klamt, S', 'Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany.|Max Planck Institute for Dynamics of Complex Technical Systems, Sandtorstr. 1, 39106 Magdeburg, Germany.', 'Germany|Germany|Germany|Germany', 10, 'Gene Expression|Gene Regulatory Networks|Genomics|Genotype|Phenotype|Quantitative Trait Loci|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/bts679', '23175757', 'Systems Genetics approaches, in particular those relying on genetical genomics data, put forward a new paradigm of large-scale genome and network analysis. These methods use naturally occurring multi-factorial perturbations (e.g. polymorphisms) in properly controlled and screened genetic crosses to elucidate causal relationships in biological networks. However, although genetical genomics data contain rich information, a clear dissection of causes and effects as required for reconstructing gene regulatory networks is not easily possible.'),
(77349, 2013, 'bio', 'A Lasso multi-marker mixed model for association mapping with population structure correction', 'Rakitsch, Barbara|Lippert, Christoph|Stegle, Oliver|Borgwardt, Karsten', 'Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. rakitsch@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. rakitsch@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. rakitsch@tuebingen.mpg.de|Machine Learning and Computational Biology Research Group, Max Planck Institute for Intelligent Systems and Max Planck Institute for Developmental Biology, 72076 Tübingen, Germany. rakitsch@tuebingen.mpg.de', 'Germany|Germany|Germany|Germany', 67, 'Animals|Chromosome Mapping|Genetic Loci|Genome|Genome-Wide Association Study|Genotype|Humans|Linear Models|Mice|Phenotype|Polymorphism, Single Nucleotide|Population Groups', 'Journal Article', '10.1093/bioinformatics/bts669', '23175758', 'Exploring the genetic basis of heritable traits remains one of the central challenges in biomedical research. In traits with simple Mendelian architectures, single polymorphic loci explain a significant fraction of the phenotypic variability. However, many traits of interest seem to be subject to multifactorial control by groups of genetic loci. Accurate detection of such multivariate associations is non-trivial and often compromised by limited statistical power. At the same time, confounding influences, such as population structure, cause spurious association signals that result in false-positive findings.'),
(77350, 2013, 'bio', 'Efficient statistical significance approximation for local similarity analysis of high-throughput time series data', 'Xia, Li C|Ai, Dongmei|Cram, Jacob|Fuhrman, Jed A|Sun, Fengzhu', 'Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA.|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA.|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA.|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA.|Molecular and Computational Biology Program, Department of Biological Sciences, University of Southern California, Los Angeles, CA 90089-2910, USA.', 'United States|United States|United States|United States|United States', 67, 'Female|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Male|Markov Chains|Metagenome|Models, Statistical|Software', 'Journal Article', '10.1093/bioinformatics/bts668', '23178636', 'Local similarity analysis of biological time series data helps elucidate the varying dynamics of biological systems. However, its applications to large scale high-throughput data are limited by slow permutation procedures for statistical significance evaluation.'),
(77351, 2013, 'bio', 'Bioclipse-R: integrating management and visualization of life science data with statistical analysis', 'Spjuth, Ola|Georgiev, Valentin|Carlsson, Lars|Alvarsson, Jonathan|Berg, Arvid|Willighagen, Egon|Wikberg, Jarl E S|Eklund, Martin', 'Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.|Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 6, 'Antineoplastic Agents|Biological Science Disciplines|Computer Graphics|Data Interpretation, Statistical|Mutagenesis|Programming Languages|Quantitative Structure-Activity Relationship|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bts681', '23178637', 'Bioclipse, a graphical workbench for the life sciences, provides functionality for managing and visualizing life science data. We introduce Bioclipse-R, which integrates Bioclipse and the statistical programming language R. The synergy between Bioclipse and R is demonstrated by the construction of a decision support system for anticancer drug screening and mutagenicity prediction, which shows how Bioclipse-R can be used to perform complex tasks from within a single software system.'),
(77352, 2013, 'bio', 'Concerning the accuracy of Fido and parameter choice', 'Serang, Oliver', 'Department of Pharmaceutical Biosciences, Uppsala University, SE-751 24 Uppsala, Sweden.', 'Sweden', 4, 'Algorithms|Humans|Programming, Linear|Proteins|Proteomics', 'Letter', '10.1093/bioinformatics/bts687', '23193221', '-'),
(77353, 2013, 'bio', 'READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation', 'Naeem, Raeece|Rashid, Mamoon|Pain, Arnab', 'Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal-23955-6900, Kingdom of Saudi Arabia. raeece.naeem@gmail.com|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal-23955-6900, Kingdom of Saudi Arabia. raeece.naeem@gmail.com|Pathogen Genomics Laboratory, Computational Bioscience Research Center, King Abdullah University of Science and Technology (KAUST), Thuwal-23955-6900, Kingdom of Saudi Arabia. raeece.naeem@gmail.com', 'Saudi Arabia|Saudi Arabia|Saudi Arabia', 36, 'Algorithms|Carcinoma|Colorectal Neoplasms|Fusobacterium nucleatum|Genome, Viral|High-Throughput Nucleotide Sequencing|Human papillomavirus 18|Humans|Male|Prostatic Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/bts684', '23193222', 'READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material).'),
(77354, 2013, 'bio', 'Defining and predicting structurally conserved regions in protein superfamilies', 'Huang, Ivan K|Pei, Jimin|Grishin, Nick V', 'Department of Mathematics, Rice University, Houston, TX 77005, USA. 91huangi@gmail.com|Department of Mathematics, Rice University, Houston, TX 77005, USA. 91huangi@gmail.com|Department of Mathematics, Rice University, Houston, TX 77005, USA. 91huangi@gmail.com', 'United States|United States|United States', 9, 'Amino Acid Motifs|Databases, Protein|Neural Networks (Computer)|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts682', '23193223', 'The structures of homologous proteins are generally better conserved than their sequences. This phenomenon is demonstrated by the prevalence of structurally conserved regions (SCRs) even in highly divergent protein families. Defining SCRs requires the comparison of two or more homologous structures and is affected by their availability and divergence, and our ability to deduce structurally equivalent positions among them. In the absence of multiple homologous structures, it is necessary to predict SCRs of a protein using information from only a set of homologous sequences and (if available) a single structure. Accurate SCR predictions can benefit homology modelling and sequence alignment.'),
(77355, 2013, 'bio', 'NURBS: a database of experimental and predicted nuclear receptor binding sites of mouse', 'Fang, Yaping|Liu, Hui-Xin|Zhang, Ning|Guo, Grace L|Wan, Yu-Jui Yvonne|Fang, Jianwen', 'Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu|Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu|Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu|Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu|Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu|Applied Bioinformatics Laboratory, University of Kansas, Lawrence, KS 66047, USA. jwfang@ku.edu', 'United States|United States|United States|United States|United States|United States', 6, 'Animals|Binding Sites|Cell Nucleus|Chromatin Immunoprecipitation|Databases, Genetic|Genome|High-Throughput Nucleotide Sequencing|Markov Chains|Mice|Receptors, Cytoplasmic and Nuclear|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts693', '23196988', 'Nuclear receptors (NRs) are a class of transcription factors playing important roles in various biological processes. An NR often impacts numerous genes and different NRs share overlapped target networks. To fulfil the need for a database incorporating binding sites of different NRs at various conditions for easy comparison and visualization to improve our understanding of NR binding mechanisms, we have developed NURBS, a database for experimental and predicted nuclear receptor binding sites of mouse (NURBS). NURBS currently contains binding sites across the whole-mouse genome of 8 NRs identified in 40 chromatin immunoprecipitation with massively parallel DNA sequencing experiments. All datasets are processed using a widely used procedure and same statistical criteria to ensure the binding sites derived from different datasets are comparable. NURBS also provides predicted binding sites using NR-HMM, a Hidden Markov Model (HMM) model.'),
(77356, 2013, 'bio', 'PAIR: paired allelic log-intensity-ratio-based normalization method for SNP-CGH arrays', 'Yang, Shengping|Pounds, Stanley|Zhang, Kun|Fang, Zhide', 'Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA. zfang@lsuhsc.edu|Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA. zfang@lsuhsc.edu|Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA. zfang@lsuhsc.edu|Biostatistics Program, School of Public Health, LSU Health Sciences Center, New Orleans, LA, USA. zfang@lsuhsc.edu', 'United States|United States|United States|United States', 6, 'Algorithms|Alleles|Comparative Genomic Hybridization|DNA Copy Number Variations|Genome|Loss of Heterozygosity|Markov Chains|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1093/bioinformatics/bts683', '23196989', 'Normalization is critical in DNA copy number analysis. We propose a new method to correctly identify two-copy probes from the genome to obtain representative references for normalization in single nucleotide polymorphism arrays. The method is based on a two-state Hidden Markov Model. Unlike most currently available methods in the literature, the proposed method does not need to assume that the percentage of two-copy state probes is dominant in the genome, as long as there do exist two-copy probes.'),
(77357, 2013, 'bio', 'PLI: a web-based tool for the comparison of protein-ligand interactions observed on PDB structures', 'Gallina, Anna Maria|Bisignano, Paola|Bergamino, Maurizio|Bordo, Domenico', 'IRCCS Azienda Ospedaliera Universitaria San Martino-IST-Istituto Nazionale Ricerca sul Cancro, 16132 Genova, Italy.|IRCCS Azienda Ospedaliera Universitaria San Martino-IST-Istituto Nazionale Ricerca sul Cancro, 16132 Genova, Italy.|IRCCS Azienda Ospedaliera Universitaria San Martino-IST-Istituto Nazionale Ricerca sul Cancro, 16132 Genova, Italy.|IRCCS Azienda Ospedaliera Universitaria San Martino-IST-Istituto Nazionale Ricerca sul Cancro, 16132 Genova, Italy.', 'Italy|Italy|Italy|Italy', 11, 'Binding Sites|Databases, Protein|Drug Design|Internet|Ligands|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts691', '23196990', 'A large fraction of the entries contained in the Protein Data Bank describe proteins in complex with low molecular weight molecules such as physiological compounds or synthetic drugs. In many cases, the same molecule is found in distinct protein-ligand complexes. There is an increasing interest in Medicinal Chemistry in comparing protein binding sites to get insight on interactions that modulate the binding specificity, as this structural information can be correlated with other experimental data of biochemical or physiological nature and may help in rational drug design.'),
(77358, 2013, 'bio', 'Multistructural hot spot characterization with FTProd', 'Votapka, Lane|Amaro, Rommie E', 'Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA.|Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA.', 'United States|United States', 9, 'Binding Sites|Molecular Dynamics Simulation|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts689', '23202744', 'Computational solvent fragment mapping is typically performed on a single structure of a protein to identify and characterize binding sites. However, the simultaneous analysis of several mutant structures or frames of a molecular dynamics simulation may provide more realistic detail about the behavior of the sites. Here we present a plug-in for Visual Molecular Dynamics that streamlines the comparison of the binding configurations of several FTMAP-generated structures.'),
(77359, 2013, 'bio', 'BlueSNP: R package for highly scalable genome-wide association studies using Hadoop clusters', 'Huang, Hailiang|Tata, Sandeep|Prill, Robert J', 'Healthcare Informatics, IBM Almaden Research Center, San Jose, CA 95120, USA.|Healthcare Informatics, IBM Almaden Research Center, San Jose, CA 95120, USA.|Healthcare Informatics, IBM Almaden Research Center, San Jose, CA 95120, USA.', 'United States|United States|United States', 29, 'Genome-Wide Association Study|Humans|Phenotype|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/bts647', '23202745', 'Computational workloads for genome-wide association studies (GWAS) are growing in scale and complexity outpacing the capabilities of single-threaded software designed for personal computers. The BlueSNP R package implements GWAS statistical tests in the R programming language and executes the calculations across computer clusters configured with Apache Hadoop, a de facto standard framework for distributed data processing using the MapReduce formalism. BlueSNP makes computationally intensive analyses, such as estimating empirical p-values via data permutation, and searching for expression quantitative trait loci over thousands of genes, feasible for large genotype-phenotype datasets.'),
(77360, 2013, 'bio', 'Musket: a multistage k-mer spectrum-based error corrector for Illumina sequence data', 'Liu, Yongchao|Schröder, Jan|Schmidt, Bertil', 'Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de|Institut für Informatik, Johannes Gutenberg Universität Mainz, Mainz 55099, Germany. liuy@uni-mainz.de', 'Germany|Germany|Germany', 137, 'Algorithms|Chromosomes, Human|Escherichia coli|Genome, Bacterial|Humans|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts690', '23202746', 'The imperfect sequence data produced by next-generation sequencing technologies have motivated the development of a number of short-read error correctors in recent years. The majority of methods focus on the correction of substitution errors, which are the dominant error source in data produced by Illumina sequencing technology. Existing tools either score high in terms of recall or precision but not consistently high in terms of both measures.'),
(77361, 2013, 'bio', 'ToxPi GUI: an interactive visualization tool for transparent integration of data from diverse sources of evidence', 'Reif, David M|Sypa, Myroslav|Lock, Eric F|Wright, Fred A|Wilson, Ander|Cathey, Tommy|Judson, Richard R|Rusyn, Ivan', 'National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com|National Center for Computational Toxicology, U.S. Environmental Protection Agency, Durham, NC, USA. reif.david@gmail.com', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Computer Graphics|Software|Toxicity Tests|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts686', '23202747', 'Scientists and regulators are often faced with complex decisions, where use of scarce resources must be prioritized using collections of diverse information. The Toxicological Prioritization Index (ToxPi™) was developed to enable integration of multiple sources of evidence on exposure and/or safety, transformed into transparent visual rankings to facilitate decision making. The rankings and associated graphical profiles can be used to prioritize resources in various decision contexts, such as testing chemical toxicity or assessing similarity of predicted compound bioactivity profiles. The amount and types of information available to decision makers are increasing exponentially, while the complex decisions must rely on specialized domain knowledge across multiple criteria of varying importance. Thus, the ToxPi bridges a gap, combining rigorous aggregation of evidence with ease of communication to stakeholders.'),
(77362, 2013, 'bio', 'Non-local residue-residue contacts in proteins are more conserved than local ones', 'Noivirt-Brik, Orly|Hazan, Gershon|Unger, Ron|Ofran, Yanay', 'Department of Structural Biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Structural Biology, Weizmann Institute of Science, Rehovot 76100, Israel.', 'Israel|Israel|Israel|Israel', 5, 'Evolution, Molecular|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structural Homology, Protein', 'Journal Article', '10.1093/bioinformatics/bts694', '23202807', 'Non-covalent residue-residue contacts drive the folding of proteins and stabilize them. They may be local-i.e. involve residues that are close in sequence, or non-local. It has been suggested that, in most proteins, local contacts drive protein folding by providing crucial constraints of the conformational space, thus allowing proteins to fold. We compared residues that are involved in local contacts to residues that are involved in non-local contacts and found that, in most proteins, residues in non-local contacts are significantly more conserved evolutionarily than residues in local contacts. Moreover, non-local contacts are more structurally conserved: a contact between positions that are distant in sequence is more likely to exist in many structural homologues compared with a contact between positions that are close in sequence. These results provide new insights into the mechanisms of protein folding and may allow for better prediction of critical intra-chain contacts.'),
(77363, 2013, 'bio', 'ECOH: an enzyme commission number predictor using mutual information and a support vector machine', 'Matsuta, Yoshihiko|Ito, Masahiro|Tohsato, Yukako', 'Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, Shiga, Kusatsu 525-8577, Japan.|Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, Shiga, Kusatsu 525-8577, Japan.|Department of Bioinformatics, College of Life Sciences, Ritsumeikan University, Shiga, Kusatsu 525-8577, Japan.', 'Japan|Japan|Japan', 14, 'Algorithms|Enzymes|Support Vector Machine|Terminology as Topic', 'Journal Article', '10.1093/bioinformatics/bts700', '23220570', 'The enzyme nomenclature system, commonly known as the enzyme commission (EC) number, plays a key role in classifying and predicting enzymatic reactions. However, numerous reactions have been described in various pathways that do not have an official EC number, and the reactions are not expected to have an EC number assigned because of a lack of articles published on enzyme assays. To predict the EC number of a non-classified enzymatic reaction, we focus on the structural similarity of its substrate and product to the substrate and product of reactions that have been classified.'),
(77364, 2013, 'bio', 'SM2miR: a database of the experimentally validated small molecules effects on microRNA expression', 'Liu, Xinyi|Wang, Shuyuan|Meng, Fanlin|Wang, Jizhe|Zhang, Yan|Dai, Enyu|Yu, Xuexin|Li, Xia|Jiang, Wei', 'College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.|College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.', 'China|China|China|China|China|China|China|China|China', 0, 'Databases, Nucleic Acid|Gene Expression|Humans|Internet|MicroRNAs|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bts698', '23220571', 'The inappropriate expression of microRNAs (miRNAs) is closely related with disease diagnosis, prognosis and therapy response. Recently, many studies have demonstrated that bioactive small molecules (or drugs) can regulate miRNA expression, which indicates that targeting miRNAs with small molecules is a new therapy for human diseases. In this study, we established the SM2miR database, which recorded 2925 relationships between 151 small molecules and 747 miRNAs in 17 species after manual curation from nearly 2000 articles. Each entry contains the detailed information about small molecules, miRNAs and evidences of their relationships, such as species, miRBase Accession number, DrugBank Accession number, PubChem Compound Identifier (CID), expression pattern of miRNA, experimental method, tissues or conditions for detection. SM2miR database has a user-friendly interface to retrieve by miRNA or small molecule. In addition, we offered a submission page. Thus, SM2miR provides a fairly comprehensive repository about the influences of small molecules on miRNA expression, which will promote the development of miRNA therapeutics.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77365, 2013, 'bio', 'A knowledge-based orientation potential for transcription factor-DNA docking', 'Takeda, Takako|Corona, Rosario I|Guo, Jun-Tao', 'Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.|Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.|Department of Bioinformatics and Genomics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA.', 'United States|United States|United States', 11, 'DNA|Knowledge Bases|Molecular Docking Simulation|Protein Binding|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts699', '23220572', 'Computational modeling of protein-DNA complexes remains a challenging problem in structural bioinformatics. One of the key factors for a successful protein-DNA docking is a potential function that can accurately discriminate the near-native structures from decoy complexes and at the same time make conformational sampling more efficient. Here, we developed a novel orientation-dependent, knowledge-based, residue-level potential for improving transcription factor (TF)-DNA docking.'),
(77366, 2013, 'bio', 'ADAPT-NMR Enhancer: complete package for reduced dimensionality in protein NMR spectroscopy', 'Lee, Woonghee|Bahrami, Arash|Markley, John L', 'National Magnetics Resonance Facility at Madison, University of Wisconsin-Madison, Madison, WI 53706, USA. whlee@nmrfam.wisc.edu|National Magnetics Resonance Facility at Madison, University of Wisconsin-Madison, Madison, WI 53706, USA. whlee@nmrfam.wisc.edu|National Magnetics Resonance Facility at Madison, University of Wisconsin-Madison, Madison, WI 53706, USA. whlee@nmrfam.wisc.edu', 'United States|United States|United States', 7, 'Algorithms|Carrier Proteins|Nuclear Magnetic Resonance, Biomolecular|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts692', '23220573', 'ADAPT-nuclear magnetic resonance (ADAPT-NMR) offers an automated approach to the concurrent acquisition and processing of protein NMR data with the goal of complete backbone and side chain assignments. What the approach lacks is a useful graphical interface for reviewing results and for searching for missing peaks that may have prevented assignments or led to incorrect assignments. Because most of the data ADAPT-NMR collects are 2D tilted planes used to find peaks in 3D spectra, it would be helpful to have a tool that reconstructs the 3D spectra. The software package reported here, ADAPT-NMR Enhancer, supports the visualization of both 2D tilted planes and reconstructed 3D peaks on each tilted plane. ADAPT-NMR Enhancer can be used interactively with ADAPT-NMR to automatically assign selected peaks, or it can be used to produce PINE-SPARKY-like graphical dialogs that support atom-by-atom and peak-by-peak assignment strategies. Results can be exported in various formats, including XEASY proton file (.prot), PINE pre-assignment file (.str), PINE probabilistic output file, SPARKY peak list file (.list) and TALOS+ input file (.tab). As an example, we show how ADAPT-NMR Enhancer was used to extend the automated data collection and assignment results for the protein Aedes aegypti sterol carrier protein 2.'),
(77367, 2013, 'bio', 'Nestly--a framework for running software with nested parameter choices and aggregating results', 'McCoy, Connor O|Gallagher, Aaron|Hoffman, Noah G|Matsen, Frederick A', 'Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. cmccoy@fhcrc.org|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. cmccoy@fhcrc.org|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. cmccoy@fhcrc.org|Program in Computational Biology, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA. cmccoy@fhcrc.org', 'United States|United States|United States|United States', 7, 'Algorithms|Computational Biology|Humans|Software', 'Journal Article', '10.1093/bioinformatics/bts696', '23220574', 'The execution of a software application or pipeline using various combinations of parameters and inputs is a common task in bioinformatics. In the absence of a specialized tool to organize, streamline and formalize this process, scientists must write frequently complex scripts to perform these tasks. We present nestly, a Python package to facilitate running tools with nested combinations of parameters and inputs. nestly provides three components. First, a module to build nested directory structures corresponding to choices of parameters. Second, the nestrun script to run a given command using each set of parameter choices. Third, the nestagg script to aggregate results of the individual runs into a CSV file, as well as support for more complex aggregation. We also include a module for easily specifying nested dependencies for the SCons build tool, enabling incremental builds.'),
(77368, 2013, 'bio', 'ChromoZoom: a flexible, fluid, web-based genome browser', 'Pak, Theodore R|Roth, Frederick P', 'Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada.|Donnelly Centre, University of Toronto, Toronto, ON M5S3E1, Canada.', 'Canada|Canada', 11, 'Genome, Human|Genomics|Humans|Internet|Software|Yeasts', 'Journal Article', '10.1093/bioinformatics/bts695', '23220575', 'Current web-based genome browsers require repetitious user input to scroll over long distances, alter the drawing density of elements or zoom through multiple orders of magnitude. Generally, either the server or the client is responsible for the majority of data processing, resulting in either servers having to receive and handle data relevant only to one user, or clients redundantly processing widely viewed data. ChromoZoom pre-renders and caches general-use tracks into tiled images on the server and serves them in an interactive web interface with inertial scrolling and precise, fluent zooming via the mouse wheel or trackpad. Custom tracks in several formats can be rendered by client-side code alongside the pre-rendered tracks, minimizing server load because of user-specific rendering and eliminating the need to transmit private data. ChromoZoom thereby enables rapid and simultaneous exploration of curated, experimental and personal genomic datasets.'),
(77369, 2013, 'bio', 'Glycosylation Network Analysis Toolbox: a MATLAB-based environment for systems glycobiology', 'Liu, Gang|Puri, Apurv|Neelamegham, Sriram', 'Department of Chemical and Biological Engineering and The NY State Center for Excellence in Bioinformatics and Life Sciences, State University of New York, Buffalo, NY 14260, USA. gangliu@buffalo.edu|Department of Chemical and Biological Engineering and The NY State Center for Excellence in Bioinformatics and Life Sciences, State University of New York, Buffalo, NY 14260, USA. gangliu@buffalo.edu|Department of Chemical and Biological Engineering and The NY State Center for Excellence in Bioinformatics and Life Sciences, State University of New York, Buffalo, NY 14260, USA. gangliu@buffalo.edu', 'United States|United States|United States', 13, 'Databases, Chemical|Glycomics|Glycosylation|Polysaccharides|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/bts703', '23230149', 'Systems glycobiology studies the interaction of various pathways that regulate glycan biosynthesis and function. Software tools for the construction and analysis of such pathways are not yet available. We present GNAT, a platform-independent, user-extensible MATLAB-based toolbox that provides an integrated computational environment to construct, manipulate and simulate glycans and their networks. It enables integration of XML-based glycan structure data into SBML (Systems Biology Markup Language) files that describe glycosylation reaction networks. Curation and manipulation of networks is facilitated using class definitions and glycomics database query tools. High quality visualization of networks and their steady-state and dynamic simulation are also supported.'),
(77370, 2013, 'bio', 'Characterization of disordered proteins with ENSEMBLE', 'Krzeminski, Mickaxc3xabl|Marsh, Joseph A|Neale, Chris|Choy, Wing-Yiu|Forman-Kay, Julie D', 'Molecular Structure & Function Program, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.|Molecular Structure & Function Program, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.|Molecular Structure & Function Program, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.|Molecular Structure & Function Program, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.|Molecular Structure & Function Program, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada.', 'Canada|Canada|Canada|Canada|Canada', 88, 'Algorithms|Protein Conformation|Protein Folding|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts701', '23233655', 'ENSEMBLE is a computational approach for determining a set of conformations that represents the structural ensemble of a disordered protein based on input experimental data. The disordered protein can be an unfolded or intrinsically disordered state. Here, we introduce the latest version of the program, which has been enhanced to facilitate its general release and includes an intuitive user interface, as well as new approaches to treat data and analyse results.'),
(77371, 2013, 'bio', 'RetroSeq: transposable element discovery from next-generation sequencing data', 'Keane, Thomas M|Wong, Kim|Adams, David J', 'Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. tk2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. tk2@sanger.ac.uk|Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK. tk2@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 88, 'Genomics|High-Throughput Nucleotide Sequencing|Humans|Interspersed Repetitive Sequences|Software', 'Journal Article', '10.1093/bioinformatics/bts697', '23233656', 'A significant proportion of eukaryote genomes consist of transposable element (TE)-derived sequence. These elements are known to have the capacity to modulate gene function and genome evolution. We have developed RetroSeq for detecting non-reference TE insertions from Illumina paired-end whole-genome sequencing data. We evaluate RetroSeq on a human trio from the 1000 Genomes Project, showing that it produces highly accurate TE calls.'),
(77372, 2013, 'bio', 'A novel link prediction algorithm for reconstructing protein-protein interaction networks by topological similarity', 'Lei, Chengwei|Ruan, Jianhua', 'Department of Computer Science, The University of Texas at San Antonio, San Antonio, TX 78249, USA.|Department of Computer Science, The University of Texas at San Antonio, San Antonio, TX 78249, USA.', 'United States|United States', 88, 'Algorithms|Cluster Analysis|Humans|Multiprotein Complexes|Protein Interaction Mapping|Protein Interaction Maps|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/bts688', '23235927', 'Recent advances in technology have dramatically increased the availability of protein-protein interaction (PPI) data and stimulated the development of many methods for improving the systems level understanding the cell. However, those efforts have been significantly hindered by the high level of noise, sparseness and highly skewed degree distribution of PPI networks. Here, we present a novel algorithm to reduce the noise present in PPI networks. The key idea of our algorithm is that two proteins sharing some higher-order topological similarities, measured by a novel random walk-based procedure, are likely interacting with each other and may belong to the same protein complex.'),
(77373, 2013, 'bio', 'Computational modelling of LY303511 and TRAIL-induced apoptosis suggests dynamic regulation of cFLIP', 'Shi, Yuan|Mellier, Gregory|Huang, Sinong|White, Jacob|Pervaiz, Shazib|Tucker-Kellogg, Lisa', 'Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.|Singapore-MIT Alliance, E4-04-10, 4 Engineering Drive 3, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 6, 'Apoptosis|CASP8 and FADD-Like Apoptosis Regulating Protein|Caspase 8|Chromones|Computer Simulation|Drug Synergism|HeLa Cells|Humans|Piperazines|Reactive Oxygen Species|TNF-Related Apoptosis-Inducing Ligand', 'Journal Article', '10.1093/bioinformatics/bts702', '23239672', 'TRAIL has been widely studied for the ability to kill cancer cells selectively, but its clinical usefulness has been hindered by the development of resistance. Multiple compounds have been identified that sensitize cancer cells to TRAIL-induced apoptosis. The drug LY303511 (LY30), combined with TRAIL, caused synergistic (greater than additive) killing of multiple cancer cell lines. We used mathematical modelling and ordinary differential equations to represent how LY30 and TRAIL individually affect HeLa cells, and to predict how the combined treatment achieves synergy.'),
(77374, 2013, 'bio', 'SwiftLink: parallel MCMC linkage analysis using multicore CPU and GPU', 'Medlar, Alan|Gxc5x82owacka, Dorota|Stanescu, Horia|Bryson, Kevin|Kleta, Robert', 'Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi|Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi|Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi|Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi|Division of Medicine, University College London, London WC1E 6BT, UK, Institute of Biotechnology, University of Helsinki, Helsinki 00014, Finland. alan.j.medlar@helsinki.fi', 'Finland|Finland|Finland|Finland|Finland', 9, 'Algorithms|Genetic Linkage|Genomics|Hearing Loss, Sensorineural|Humans|Intellectual Disability|Markov Chains|Monte Carlo Method|Pedigree|Polymorphism, Single Nucleotide|Seizures|Software', 'Journal Article', '10.1093/bioinformatics/bts704', '23239673', 'Linkage analysis remains an important tool in elucidating the genetic component of disease and has become even more important with the advent of whole exome sequencing, enabling the user to focus on only those genomic regions co-segregating with Mendelian traits. Unfortunately, methods to perform multipoint linkage analysis scale poorly with either the number of markers or with the size of the pedigree. Large pedigrees with many markers can only be evaluated with Markov chain Monte Carlo (MCMC) methods that are slow to converge and, as no attempts have been made to exploit parallelism, massively underuse available processing power. Here, we describe SWIFTLINK, a novel application that performs MCMC linkage analysis by spreading the computational burden between multiple processor cores and a graphics processing unit (GPU) simultaneously. SWIFTLINK was designed around the concept of explicitly matching the characteristics of an algorithm with the underlying computer architecture to maximize performance.'),
(77375, 2013, 'bio', 'Minerva and minepy: a C engine for the MINE suite and its R, Python and MATLAB wrappers', 'Albanese, Davide|Filosi, Michele|Visintainer, Roberto|Riccadonna, Samantha|Jurman, Giuseppe|Furlanello, Cesare', 'Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.|Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.|Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.|Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.|Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.|Fondazione Bruno Kessler, via Sommarive 18, I-38123 Povo (Trento), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 69, 'Algorithms|Computational Biology|Data Mining|Gene Expression Profiling|Metagenome|Software', 'Journal Article', '10.1093/bioinformatics/bts707', '23242262', 'We introduce a novel implementation in ANSI C of the MINE family of algorithms for computing maximal information-based measures of dependence between two variables in large datasets, with the aim of a low memory footprint and ease of integration within bioinformatics pipelines. We provide the libraries minerva (with the R interface) and minepy for Python, MATLAB, Octave and C++. The C solution reduces the large memory requirement of the original Java implementation, has good upscaling properties and offers a native parallelization for the R interface. Low memory requirements are demonstrated on the MINE benchmarks as well as on large ( = 1340) microarray and Illumina GAII RNA-seq transcriptomics datasets.'),
(77376, 2013, 'bio', 'Fast and robust optical flow for time-lapse microscopy using super-voxels', 'Amat, Fernando|Myers, Eugene W|Keller, Philipp J', 'Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, VA 20147, USA. amatf@janelia.hhmi.org|Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, VA 20147, USA. amatf@janelia.hhmi.org|Howard Hughes Medical Institute, Janelia Farm Research Campus, Ashburn, VA 20147, USA. amatf@janelia.hhmi.org', 'United States|United States|United States', 37, 'Animals|Drosophila|Imaging, Three-Dimensional|Microscopy|Time-Lapse Imaging|Zebrafish', 'Journal Article', '10.1093/bioinformatics/bts706', '23242263', 'Optical flow is a key method used for quantitative motion estimation of biological structures in light microscopy. It has also been used as a key module in segmentation and tracking systems and is considered a mature technology in the field of computer vision. However, most of the research focused on 2D natural images, which are small in size and rich in edges and texture information. In contrast, 3D time-lapse recordings of biological specimens comprise up to several terabytes of image data and often exhibit complex object dynamics as well as blurring due to the point-spread-function of the microscope. Thus, new approaches to optical flow are required to improve performance for such data.'),
(77377, 2013, 'bio', 'RS-WebPredictor: a server for predicting CYP-mediated sites of metabolism on drug-like molecules', 'Zaretzki, Jed|Bergeron, Charles|Huang, Tao-wei|Rydberg, Patrik|Swamidass, S Joshua|Breneman, Curt M', 'Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.|Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO 63130, USA.', 'United States|United States|United States|United States|United States|United States', 25, 'Algorithms|Cinnarizine|Cytochrome P-450 Enzyme System|Isoenzymes|Software', 'Journal Article', '10.1093/bioinformatics/bts705', '23242264', 'Regioselectivity-WebPredictor (RS-WebPredictor) is a server that predicts isozyme-specific cytochrome P450 (CYP)-mediated sites of metabolism (SOMs) on drug-like molecules. Predictions may be made for the promiscuous 2C9, 2D6 and 3A4 CYP isozymes, as well as CYPs 1A2, 2A6, 2B6, 2C8, 2C19 and 2E1. RS-WebPredictor is the first freely accessible server that predicts the regioselectivity of the last six isozymes. Server execution time is fast, taking on average 2s to encode a submitted molecule and 1s to apply a given model, allowing for high-throughput use in lead optimization projects.'),
(77378, 2013, 'bio', 'ChEMBLSpace--a graphical explorer of the chemogenomic space covered by the ChEMBL database', 'Fechner, Nikolas|Papadatos, George|Evans, David|Morphy, John Richard|Brewerton, Suzanne Clare|Thorner, David|Bodkin, Michael', 'Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.|Department of Medicinal Chemistry, Lilly Research Laboratories, Eli Lilly and Company, Erl Wood Manor, Surrey GU20 6PH, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 8, 'Computer Graphics|Databases, Chemical|Humans|Ligands|Polypharmacy|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/bts711', '23257198', 'The ChEMBLSpace graphical explorer enables the identification of compounds from the ChEMBL database, which exhibit a desirable polypharmacology profile. This profile can be predefined or created iteratively, and the tool can be extended to other data sources.'),
(77379, 2013, 'bio', 'InCroMAP: integrated analysis of cross-platform microarray and pathway data', 'Wrzodek, Clemens|Eichner, Johannes|Büchel, Finja|Zell, Andreas', 'Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de|Center for Bioinformatics Tuebingen (ZBIT), University of Tuebingen, 72076 Tübingen, Germany. clemens.wrzodek@uni-tuebingen.de', 'Germany|Germany|Germany|Germany', 27, 'DNA Methylation|Gene Expression|Gene Expression Profiling|MicroRNAs|Oligonucleotide Array Sequence Analysis|Protein Array Analysis|Proteins|RNA, Messenger|Software', 'Journal Article', '10.1093/bioinformatics/bts709', '23257199', 'Microarrays are commonly used to detect changes in gene expression between different biological samples. For this purpose, many analysis tools have been developed that offer visualization, statistical analysis and more sophisticated analysis methods. Most of these tools are designed specifically for messenger RNA microarrays. However, today, more and more different microarray platforms are available. Changes in DNA methylation, microRNA expression or even protein phosphorylation states can be detected with specialized arrays. For these microarray technologies, the number of available tools is small compared with mRNA analysis tools. Especially, a joint analysis of different microarray platforms that have been used on the same set of biological samples is hardly supported by most microarray analysis tools. Here, we present InCroMAP, a tool for the analysis and visualization of high-level microarray data from individual or multiple different platforms. Currently, InCroMAP supports mRNA, microRNA, DNA methylation and protein modification datasets. Several methods are offered that allow for an integrated analysis of data from those platforms. The available features of InCroMAP range from visualization of DNA methylation data over annotation of microRNA targets and integrated gene set enrichment analysis to a joint visualization of data from all platforms in the context of metabolic or signalling pathways.'),
(77380, 2013, 'bio', 'SRmapper: a fast and sensitive genome-hashing alignment tool', 'Gontarz, Paul M|Berger, Jennifer|Wong, Chung F', 'Department of Chemistry and Biochemistry, Center for Nanoscience, University of Missouri-Saint Louis, One University Boulevard, St. Louis, MO 63121, USA.|Department of Chemistry and Biochemistry, Center for Nanoscience, University of Missouri-Saint Louis, One University Boulevard, St. Louis, MO 63121, USA.|Department of Chemistry and Biochemistry, Center for Nanoscience, University of Missouri-Saint Louis, One University Boulevard, St. Louis, MO 63121, USA.', 'United States|United States|United States', 8, 'Genome, Human|Genomics|Humans|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bts712', '23267171', 'Modern sequencing instruments have the capability to produce millions of short reads every day. The large number of reads produced in conjunction with variations between reads and reference genomic sequences caused both by legitimate differences, such as single-nucleotide polymorphisms and insertions/deletions (indels), and by sequencer errors make alignment a difficult and computationally expensive task, and many reads cannot be aligned. Here, we introduce a new alignment tool, SRmapper, which in tests using real data can align 10s of billions of base pairs from short reads to the human genome per computer processor day. SRmapper tolerates a higher number of mismatches than current programs based on Burrows-Wheeler transform and finds about the same number of alignments in 2-8xc3x97 less time depending on read length (with higher performance gain for longer read length). The current version of SRmapper aligns both single and pair-end reads in base space fastq format and outputs alignments in Sequence Alignment/Map format. SRmapper uses a probabilistic approach to set a default number of mismatches allowed and determines alignment quality. SRmappers memory footprint (xe2x88xbc2.5 GB) is small enough that it can be run on a computer with 4 GB of random access memory for a genome the size of a human. Finally, SRmapper is designed so that its function can be extended to finding small indels as well as long deletions and chromosomal translocations in future versions.'),
(77381, 2013, 'bio', 'Disease-gene discovery by integration of 3D gene expression and transcription factor binding affinities', 'Piro, Rosario M|Molineris, Ivan|Di Cunto, Ferdinando|Eils, Roland|König, Rainer', 'Department of Theoretical Bioinformatics, German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), University of Heidelberg, Im 69120 Heidelberg, Germany. r.piro@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), University of Heidelberg, Im 69120 Heidelberg, Germany. r.piro@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), University of Heidelberg, Im 69120 Heidelberg, Germany. r.piro@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), University of Heidelberg, Im 69120 Heidelberg, Germany. r.piro@dkfz.de|Department of Theoretical Bioinformatics, German Cancer Research Center (Deutsches Krebsforschungszentrum, DKFZ), University of Heidelberg, Im 69120 Heidelberg, Germany. r.piro@dkfz.de', 'Germany|Germany|Germany|Germany|Germany', 3, 'Animals|Brain|Gene Expression Profiling|Genes|Genetic Diseases, Inborn|Humans|Intellectual Disability|Mice|Promoter Regions, Genetic|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bts720', '23267172', 'The computational evaluation of candidate genes for hereditary disorders is a non-trivial task. Several excellent methods for disease-gene prediction have been developed in the past 2 decades, exploiting widely differing data sources to infer disease-relevant functional relationships between candidate genes and disorders. We have shown recently that spatially mapped, i.e. 3D, gene expression data from the mouse brain can be successfully used to prioritize candidate genes for human Mendelian disorders of the central nervous system.'),
(77382, 2013, 'bio', 'In silico identification of oncogenic potential of fyn-related kinase in hepatocellular carcinoma', 'Chen, Jia-Shing|Hung, Wei-Shiang|Chan, Hsiang-Han|Tsai, Shaw-Jenq|Sun, H Sunny', 'Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan, Republic of China.|Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan, Republic of China.|Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan, Republic of China.|Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan, Republic of China.|Institute of Molecular Medicine, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan, Republic of China.', 'China|China|China|China|China', 0, 'Carcinoma, Hepatocellular|Cell Line, Tumor|Cell Movement|Cell Transformation, Neoplastic|Computational Biology|Computer Simulation|Genes, Tumor Suppressor|Hep G2 Cells|Humans|Liver Neoplasms|Neoplasm Proteins|Oncogenes|Protein-Tyrosine Kinases|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bts715', '23267173', 'Cancer development is a complex and heterogeneous process. It is estimated that 5-10% of human genes probably contribute to oncogenesis, whereas current experimentally validated cancer genes only cover 1% of the human genome. Thus hundreds of cancer genes may still remain to be identified. To search for new genes that play roles in carcinogenesis and facilitate cancer research, we developed a systematic workflow to use information saved in a previously established tumor-associated gene (TAG) database.'),
(77383, 2013, 'bio', 'Data exploration, quality control and testing in single-cell qPCR-based gene expression experiments', 'McDavid, Andrew|Finak, Greg|Chattopadyay, Pratip K|Dominguez, Maria|Lamoreaux, Laurie|Ma, Steven S|Roederer, Mario|Gottardo, Raphael', 'Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.|Department of Statistics, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 142, 'Gene Expression Profiling|Humans|Microfluidic Analytical Techniques|Models, Statistical|Quality Control|Reverse Transcriptase Polymerase Chain Reaction|Single-Cell Analysis', 'Journal Article', '10.1093/bioinformatics/bts714', '23267174', 'Cell populations are never truly homogeneous, individual cells exist in biochemical states that define functional differences between them. New technology based on microfluidic arrays combined with multiplexed quantitative polymerase chain reactions now enables high-throughput single-cell gene expression measurement, allowing assessment of cellular heterogeneity. However, few analytic tools have been developed specifically for the statistical and analytical challenges of single-cell quantitative polymerase chain reactions data.'),
(77384, 2013, 'bio', 'Ultranet: efficient solver for the sparse inverse covariance selection problem in gene network modeling', 'Järvstråt, Linnea|Johansson, Mikael|Gullberg, Urban|Nilsson, Björn', 'Department of Hematology and Transfusion Medicine, Lund University Hospital, SE-221 85 Lund, Sweden.|Department of Hematology and Transfusion Medicine, Lund University Hospital, SE-221 85 Lund, Sweden.|Department of Hematology and Transfusion Medicine, Lund University Hospital, SE-221 85 Lund, Sweden.|Department of Hematology and Transfusion Medicine, Lund University Hospital, SE-221 85 Lund, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 6, 'Gene Regulatory Networks|Genomics|Humans|Models, Genetic|Normal Distribution|Software|Transcriptome', 'Journal Article', '10.1093/bioinformatics/bts717', '23267175', 'Graphical Gaussian models (GGMs) are a promising approach to identify gene regulatory networks. Such models can be robustly inferred by solving the sparse inverse covariance selection (SICS) problem. With the high dimensionality of genomics data, fast methods capable of solving large instances of SICS are needed. We developed a novel network modeling tool, Ultranet, that solves the SICS problem with significantly improved efficiency. Ultranet combines a range of mathematical and programmatical techniques, exploits the structure of the SICS problem and enables computation of genome-scale GGMs without compromising analytic accuracy.'),
(77385, 2013, 'bio', 'OntoMaton: a bioportal powered ontology widget for Google Spreadsheets', 'Maguire, Eamonn|González-Beltrán, Alejandra|Whetzel, Patricia L|Sansone, Susanna-Assunta|Rocca-Serra, Philippe', 'Oxford e-Research Centre, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, UK. isatools@googlegroups.com|Oxford e-Research Centre, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, UK. isatools@googlegroups.com|Oxford e-Research Centre, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, UK. isatools@googlegroups.com|Oxford e-Research Centre, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, UK. isatools@googlegroups.com|Oxford e-Research Centre, University of Oxford, 7 Keble Road, OX1 3QG, Oxford, UK. isatools@googlegroups.com', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 22, 'Internet|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts718', '23267176', 'Data collection in spreadsheets is ubiquitous, but current solutions lack support for collaborative semantic annotation that would promote shared and interdisciplinary annotation practices, supporting geographically distributed players.'),
(77386, 2013, 'bio', 'Inference of gene regulatory networks from genome-wide knockout fitness data', 'Wang, Liming|Wang, Xiaodong|Arkin, Adam P|Samoilov, Michael S', 'Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA.|Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA.|Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA.|Department of Electrical and Computer Engineering, Duke University, Durham, NC 27708, USA.', 'United States|United States|United States|United States', 12, 'Algorithms|Gene Regulatory Networks|Genome|Models, Genetic|Saccharomyces cerevisiae|Shewanella', 'Journal Article', '10.1093/bioinformatics/bts634', '23271269', 'Genome-wide fitness is an emerging type of high-throughput biological data generated for individual organisms by creating libraries of knockouts, subjecting them to broad ranges of environmental conditions, and measuring the resulting clone-specific fitnesses. Since fitness is an organism-scale measure of gene regulatory network behaviour, it may offer certain advantages when insights into such phenotypical and functional features are of primary interest over individual gene expression. Previous works have shown that genome-wide fitness data can be used to uncover novel gene regulatory interactions, when compared with results of more conventional gene expression analysis. Yet, to date, few algorithms have been proposed for systematically using genome-wide mutant fitness data for gene regulatory network inference.'),
(77387, 2013, 'bio', 'rBiopaxParser--an R package to parse, modify and visualize BioPAX data', 'Kramer, Frank|Bayerlová, Michaela|Klemm, Florian|Bleckmann, Annalen|Beissbarth, Tim', 'Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, Humboldtallee 32, Germany. frank.kramer@med.uni-goettingen.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computational Biology|Computer Graphics|Databases, Factual|Genomics|Models, Biological|Signal Transduction|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts710', '23274212', 'Biological pathway data, stored in structured databases, is a useful source of knowledge for a wide range of bioinformatics algorithms and tools. The Biological Pathway Exchange (BioPAX) language has been established as a standard to store and annotate pathway information. However, use of these data within statistical analyses can be tedious. On the other hand, the statistical computing environment R has become the standard for bioinformatics analysis of large-scale genomics data. With this package, we hope to enable R users to work with BioPAX data and make use of the always increasing amount of biological pathway knowledge within data analysis methods.'),
(77388, 2013, 'bio', 'SCARPA: scaffolding reads with practical algorithms', 'Donmez, Nilgun|Brudno, Michael', 'Department of Computer Science, University of Toronto, Toronto, ON, Canada M5S 3E1. nild@cs.toronto.edu|Department of Computer Science, University of Toronto, Toronto, ON, Canada M5S 3E1. nild@cs.toronto.edu', 'Canada|Canada', 49, 'Algorithms|Ascomycota|Contig Mapping|Escherichia coli|Genomics|High-Throughput Nucleotide Sequencing|Programming, Linear|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts716', '23274213', 'Scaffolding is the process of ordering and orienting contigs produced during genome assembly. Accurate scaffolding is essential for finishing draft assemblies, as it facilitates the costly and laborious procedures needed to fill in the gaps between contigs. Conventional formulations of the scaffolding problem are intractable, and most scaffolding programs rely on heuristic or approximate solutions, with potentially exponential running time.'),
(77389, 2013, 'bio', 'A comprehensive SNP and indel imputability database', 'Duan, Qing|Liu, Eric Yi|Croteau-Chonka, Damien C|Mohlke, Karen L|Li, Yun', 'Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.|Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.', 'United States|United States|United States|United States|United States', 10, 'Asian Continental Ancestry Group|Databases, Nucleic Acid|Gene Frequency|Genome|Genome-Wide Association Study|Genotype|Humans|INDEL Mutation|Philippines|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bts724', '23292738', 'Genotype imputation has become an indispensible step in genome-wide association studies (GWAS). Imputation accuracy, directly influencing downstream analysis, has shown to be improved using re-sequencing-based reference panels, however, this comes at the cost of high computational burden due to the huge number of potentially imputable markers (tens of millions) discovered through sequencing a large number of individuals. Therefore, there is an increasing need for access to imputation quality information without actually conducting imputation. To facilitate this process, we have established a publicly available SNP and indel imputability database, aiming to provide direct access to imputation accuracy information for markers identified by the 1000 Genomes Project across four major populations and covering multiple GWAS genotyping platforms.'),
(77390, 2013, 'bio', 'KEGGParser: parsing and editing KEGG pathway maps in Matlab', 'Arakelyan, Arsen|Nersisyan, Lilit', 'Group of Bioinformatics, Institute of Molecular Biology, National Academy of Sciences of the Republic of Armenia, Yerevan 0014, Armenia. aarakelyan@sci.am|Group of Bioinformatics, Institute of Molecular Biology, National Academy of Sciences of the Republic of Armenia, Yerevan 0014, Armenia. aarakelyan@sci.am', 'Armenia|Armenia', 0, 'Computer Graphics|Databases, Factual|Metabolic Networks and Pathways|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/bts730', '23292739', 'KEGG pathway database is a collection of manually drawn pathway maps accompanied with KGML format files intended for use in automatic analysis. KGML files, however, do not contain the required information for complete reproduction of all the events indicated in the static image of a pathway map. Several parsers and editors of KEGG pathways exist for processing KGML files. We introduce KEGGParser-a MATLAB based tool for KEGG pathway parsing, semiautomatic fixing, editing, visualization and analysis in MATLAB environment. It also works with Scilab.'),
(77391, 2013, 'bio', 'GESTODIFFERENT: a Cytoscape plugin for the generation and the identification of gene regulatory networks describing a stochastic cell differentiation process', 'Antoniotti, Marco|Bader, Gary D|Caravagna, Giulio|Crippa, Silvia|Graudenzi, Alex|Mauri, Giancarlo', 'Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it|Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it|Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it|Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it|Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it|Department of Informatics, Systems and Communication, University of Milan Bicocca, Viale Sarca 336, 20126, Milano, Italy. marco.antoniotti@unimib.it', 'Italy|Italy|Italy|Italy|Italy|Italy', 4, 'Cell Differentiation|Cell Lineage|Gene Regulatory Networks|Models, Genetic|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bts726', '23292740', 'The characterization of the complex phenomenon of cell differentiation is a key goal of both systems and computational biology. GeStoDifferent is a Cytoscape plugin aimed at the generation and the identification of gene regulatory networks (GRNs) describing an arbitrary stochastic cell differentiation process. The (dynamical) model adopted to describe general GRNs is that of noisy random Boolean networks (NRBNs), with a specific focus on their emergent dynamical behavior. GeStoDifferent explores the space of GRNs by filtering the NRBN instances inconsistent with a stochastic lineage differentiation tree representing the cell lineages that can be obtained by following the fate of a stem cell descendant. Matched networks can then be analyzed by Cytoscape network analysis algorithms or, for instance, used to define (multiscale) models of cellular dynamics.'),
(77392, 2013, 'bio', 'RamiGO: an R/Bioconductor package providing an AmiGO visualize interface', 'Schröder, Markus S|Gusenleitner, Daniel|Quackenbush, John|Culhane, Aedín C|Haibe-Kains, Benjamin', 'School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. markus.schroeder@ucdconnect.ie|School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. markus.schroeder@ucdconnect.ie|School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. markus.schroeder@ucdconnect.ie|School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. markus.schroeder@ucdconnect.ie|School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Belfield, Dublin 4, Ireland. markus.schroeder@ucdconnect.ie', 'Ireland|Ireland|Ireland|Ireland|Ireland', 23, 'Breast Neoplasms|Computer Graphics|Female|Genes|Humans|Internet|Software|Transcriptome|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts708', '23297033', 'The R/Bioconductor package RamiGO is an R interface to AmiGO that enables visualization of Gene Ontology (GO) trees. Given a list of GO terms, RamiGO uses the AmiGO visualize API to import Graphviz-DOT format files into R, and export these either as images (SVG, PNG) or into Cytoscape for extended network analyses. RamiGO provides easy customization of annotation, highlighting of specific GO terms, colouring of terms by P-value or export of a simplified summary GO tree. We illustrate RamiGO functionalities in a genome-wide gene set analysis of prognostic genes in breast cancer.'),
(77393, 2013, 'bio', 'Detecting and understanding genetic and structural features in HIV-1 B subtype V3 underlying HIV-1 co-receptor usage', 'Chen, Mengjie|Svicher, Valentina|Artese, Anna|Costa, Giosuè|Alteri, Claudia|Ortuso, Francesco|Parrotta, Lucia|Liu, Yang|Liu, Chang|Perno, Carlo Federico|Alcaro, Stefano|Zhang, Jing', 'Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.|Program of Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 13, 'Genotype|HIV Envelope Protein gp120|HIV Infections|HIV-1|Humans|Models, Statistical|Molecular Docking Simulation|Mutation|Receptors, CCR5|Receptors, CXCR4', 'Journal Article', '10.1093/bioinformatics/btt002', '23297034', 'To define V3 genetic elements and structural features underlying different HIV-1 co-receptor usage in vivo.'),
(77394, 2013, 'bio', 'Assessing identity, redundancy and confounds in Gene Ontology annotations over time', 'Gillis, Jesse|Pavlidis, Paul', 'Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, 192B Genome Research Center, 500 Sunnyside Boulevard, Woodbury, NY 11797, USA.|Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, 192B Genome Research Center, 500 Sunnyside Boulevard, Woodbury, NY 11797, USA.', 'United States|United States', 33, 'Databases, Protein|Genes|Humans|Molecular Sequence Annotation|Protein Interaction Mapping|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bts727', '23297035', 'The Gene Ontology (GO) is heavily used in systems biology, but the potential for redundancy, confounds with other data sources and problems with stability over time have been little explored.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(77395, 2013, 'bio', 'NucleoFinder: a statistical approach for the detection of nucleosome positions', 'Becker, Jeremie|Yau, Christopher|Hancock, John M|Holmes, Christopher C', 'Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.|Department of Statistics, University of Oxford, Oxford OX1 3TG, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Cell Line|Genome, Human|High-Throughput Nucleotide Sequencing|Humans|Models, Statistical|Nucleosomes|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bts719', '23297036', 'The identification of nucleosomes along the chromatin is key to understanding their role in the regulation of gene expression and other DNA-related processes. However, current experimental methods (MNase-ChIP, MNase-Seq) sample nucleosome positions from a cell population and contain biases, making thus the precise identification of individual nucleosomes not straightforward. Recent works have only focused on the first point, where noise reduction approaches have been developed to identify nucleosome positions.'),
(77396, 2013, 'bio', 'BETAWARE: a machine-learning tool to detect and predict transmembrane beta-barrel proteins in prokaryotes', 'Savojardo, Castrense|Fariselli, Piero|Casadio, Rita', 'Biocomputing Group, CIRI-Health Science and Technology/Department of Biology, University of Bologna, 40126 Bologna, Italy.|Biocomputing Group, CIRI-Health Science and Technology/Department of Biology, University of Bologna, 40126 Bologna, Italy.|Biocomputing Group, CIRI-Health Science and Technology/Department of Biology, University of Bologna, 40126 Bologna, Italy.', 'Italy|Italy|Italy', 28, 'Artificial Intelligence|Bacterial Outer Membrane Proteins|Bacterial Proteins|Membrane Proteins|Protein Structure, Secondary|Software', 'Journal Article', '10.1093/bioinformatics/bts728', '23297037', 'The annotation of membrane proteins in proteomes is an important problem of Computational Biology, especially after the development of high-throughput techniques that allow fast and efficient genome sequencing. Among membrane proteins, transmembrane xcexb2-barrels (TMBBs) are poorly represented in the database of protein structures (PDB) and difficult to identify with experimental approaches. They are, however, extremely important, playing key roles in several cell functions and bacterial pathogenicity. TMBBs are included in the lipid bilayer with a xcexb2-barrel structure and are presently found in the outer membranes of Gram-negative bacteria, mitochondria and chloroplasts. Recently, we developed two top-performing methods based on machine-learning approaches to tackle both the detection of TMBBs in sets of proteins and the prediction of their topology. Here, we present our BETAWARE program that includes both approaches and can run as a standalone program on a linux-based computer to easily address in-home massive protein annotation or filtering.'),
(77397, 2013, 'bio', 'BroadPeak: a novel algorithm for identifying broad peaks in diffuse ChIP-seq datasets', 'Wang, Jianrong|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.', 'Georgia|Georgia|Georgia', 25, 'Algorithms|Chromatin Immunoprecipitation|Genome|High-Throughput Nucleotide Sequencing|Histones|Humans|Software', 'Evaluation Studies', '10.1093/bioinformatics/bts722', '23300134', 'Although some histone modification chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) signals show abrupt peaks across narrow and specific genomic locations, others have diffuse distributions along chromosomes, and their large contiguous enrichment landscapes are better modeled as broad peaks. Here, we present BroadPeak, an algorithm for the identification of such broad peaks from diffuse ChIP-seq datasets. We show that BroadPeak is a linear time algorithm that requires only two parameters, and we validate its performance on real and simulated histone modification ChIP-seq datasets. BroadPeak calls peaks that are highly coincident with both the underlying ChIP-seq tag count distributions and relevant biological features, such as the gene bodies of actively transcribed genes, and it shows superior overall recall and precision of known broad peaks from simulated datasets.'),
(77398, 2013, 'bio', 'MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data', 'Ramachandran, Parameswaran|Palidwor, Gareth A|Porter, Christopher J|Perkins, Theodore J', 'Regenerative Medicine Program, Ottawa Hospital Research Institute, K1H 8L6, Ottawa, Canada.|Regenerative Medicine Program, Ottawa Hospital Research Institute, K1H 8L6, Ottawa, Canada.|Regenerative Medicine Program, Ottawa Hospital Research Institute, K1H 8L6, Ottawa, Canada.|Regenerative Medicine Program, Ottawa Hospital Research Institute, K1H 8L6, Ottawa, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Chromosome Mapping|Data Interpretation, Statistical|Genomics|High-Throughput Nucleotide Sequencing|Humans|Reproducibility of Results', 'Evaluation Studies', '10.1093/bioinformatics/btt001', '23300135', 'Reliable estimation of the mean fragment length for next-generation short-read sequencing data is an important step in next-generation sequencing analysis pipelines, most notably because of its impact on the accuracy of the enriched regions identified by peak-calling algorithms. Although many peak-calling algorithms include a fragment-length estimation subroutine, the problem has not been adequately solved, as demonstrated by the variability of the estimates returned by different algorithms.'),
(77399, 2013, 'bio', 'SIBER: systematic identification of bimodally expressed genes using RNAseq data', 'Tong, Pan|Chen, Yong|Su, Xiao|Coombes, Kevin R', 'Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA.', 'United States|United States|United States|United States', 15, 'Algorithms|Breast Neoplasms|Cluster Analysis|Female|Gene Expression Profiling|High-Throughput Nucleotide Sequencing|Humans|Oligonucleotide Array Sequence Analysis|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bts713', '23303507', 'Identification of bimodally expressed genes is an important task, as genes with bimodal expression play important roles in cell differentiation, signalling and disease progression. Several useful algorithms have been developed to identify bimodal genes from microarray data. Currently, no method can deal with data from next-generation sequencing, which is emerging as a replacement technology for microarrays.'),
(77400, 2013, 'bio', 'Decombinator: a tool for fast, efficient gene assignment in T-cell receptor sequences using a finite state machine', 'Thomas, Niclas|Heather, James|Ndifon, Wilfred|Shawe-Taylor, John|Chain, Benjamin', 'CoMPLEX Department, UCL, Gower Street, London, WC1E 6BT, UK.|CoMPLEX Department, UCL, Gower Street, London, WC1E 6BT, UK.|CoMPLEX Department, UCL, Gower Street, London, WC1E 6BT, UK.|CoMPLEX Department, UCL, Gower Street, London, WC1E 6BT, UK.|CoMPLEX Department, UCL, Gower Street, London, WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 56, 'Algorithms|High-Throughput Nucleotide Sequencing|Humans|Receptors, Antigen, T-Cell, alpha-beta|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt004', '23303508', 'High-throughput sequencing provides an opportunity to analyse the repertoire of antigen-specific receptors with an unprecedented breadth and depth. However, the quantity of raw data produced by this technology requires efficient ways to categorize and store the output for subsequent analysis. To this end, we have defined a simple five-item identifier that uniquely and unambiguously defines each TcR sequence. We then describe a novel application of finite-state automaton to map Illumina short-read sequence data for individual TcRs to their respective identifier. An extension of the standard algorithm is also described, which allows for the presence of single-base pair mismatches arising from sequencing error. The software package, named Decombinator, is tested first on a set of artificial in silico sequences and then on a set of published human TcR-xcexb2 sequences. Decombinator assigned sequences at a rate more than two orders of magnitude faster than that achieved by classical pairwise alignment algorithms, and with a high degree of accuracy (>88%), even after introducing up to 1% error rates in the in silico sequences. Analysis of the published sequence dataset highlighted the strong V and J usage bias observed in the human peripheral blood repertoire, which seems to be unconnected to antigen exposure. The analysis also highlighted the enormous size of the available repertoire and the challenge of obtaining a comprehensive description for it. The Decombinator package will be a valuable tool for further in-depth analysis of the T-cell repertoire.'),
(77401, 2013, 'bio', 'ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies', 'Clark, Scott C|Egan, Rob|Frazier, Peter I|Wang, Zhong', 'Center for Applied Mathematics, Cornell University, Ithaca, NY 14853, USA.|Center for Applied Mathematics, Cornell University, Ithaca, NY 14853, USA.|Center for Applied Mathematics, Cornell University, Ithaca, NY 14853, USA.|Center for Applied Mathematics, Cornell University, Ithaca, NY 14853, USA.', 'United States|United States|United States|United States', 90, 'Bayes Theorem|Escherichia coli|Genetic Variation|Genomics|High-Throughput Nucleotide Sequencing|Humans|Metagenomics|Models, Statistical|Probability|Software', 'Journal Article', '10.1093/bioinformatics/bts723', '23303509', 'Researchers need general purpose methods for objectively evaluating the accuracy of single and metagenome assemblies and for automatically detecting any errors they may contain. Current methods do not fully meet this need because they require a reference, only consider one of the many aspects of assembly quality or lack statistical justification, and none are designed to evaluate metagenome assemblies.'),
(77402, 2013, 'bio', 'HitWalker: variant prioritization for personalized functional cancer genomics', 'Bottomly, Daniel|Wilmot, Beth|Tyner, Jeffrey W|Eide, Christopher A|Loriaux, Marc M|Druker, Brian J|McWeeney, Shannon K', 'Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu|Knight Cancer Institute, Oregon Health and Science University, Portland, OR 97239, USA. bottomly@ohsu.edu', 'United States|United States|United States|United States|United States|United States|United States', 7, 'Algorithms|Genetic Variation|Genome, Human|Genomics|Humans|Leukemia, Myeloid, Acute|Neoplasms|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt003', '23303510', 'Determining the functional relevance of identified sequence variants in cancer is a prerequisite to ultimately matching specific therapies with individual patients. This level of mechanistic understanding requires integration of genomic information with complementary functional analyses to identify oncogenic targets and relies on the development of computational frameworks to aid in the prioritization and visualization of these diverse data types. In response to this, we have developed HitWalker, which prioritizes patient variants relative to their weighted proximity to functional assay results in a protein-protein interaction network. It is highly extensible, allowing incorporation of diverse data types to refine prioritization. In addition to a ranked list of variants, we have also devised a simple shortest path-based approach of visualizing the results in an intuitive manner to provide biological interpretation.'),
(77403, 2013, 'bio', 'Fragment recruitment on metabolic pathways: comparative metabolic profiling of metagenomes and metatranscriptomes', 'Desai, Dhwani K|Schunck, Harald|Löser, Johannes W|Laroche, Julie', 'Helmholtz Centre for Ocean Research Kiel (GEOMAR), Düsternbrooker Weg 20, Kiel 24105, Germany. Dhwani.Desai@Dal.Ca|Helmholtz Centre for Ocean Research Kiel (GEOMAR), Düsternbrooker Weg 20, Kiel 24105, Germany. Dhwani.Desai@Dal.Ca|Helmholtz Centre for Ocean Research Kiel (GEOMAR), Düsternbrooker Weg 20, Kiel 24105, Germany. Dhwani.Desai@Dal.Ca|Helmholtz Centre for Ocean Research Kiel (GEOMAR), Düsternbrooker Weg 20, Kiel 24105, Germany. Dhwani.Desai@Dal.Ca', 'Germany|Germany|Germany|Germany', 3, 'Gene Expression Profiling|Metabolic Networks and Pathways|Metabolome|Metagenome|Metagenomics|Software', 'Journal Article', '10.1093/bioinformatics/bts721', '23303511', 'The sheer scale of the metagenomic and metatranscriptomic datasets that are now available warrants the development of automated protocols for organizing, annotating and comparing the samples in terms of their metabolic profiles. We describe a user-friendly java program FROMP (Fragment Recruitment on Metabolic Pathways) for mapping and visualizing enzyme annotations onto the Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathways or custom-made pathways and comparing the samples in terms of their Pathway Completeness Scores, their relative Activity Scores or enzyme enrichment odds ratios. This program along with our fully configurable PERL-based annotation organization pipeline Meta2Pro (METAbolic PROfiling of META-omic data) offers a quick and accurate standalone solution for metabolic profiling of environmental samples or cultures from different treatments. Apart from pictorial comparisons, FROMP can also generate score matrices for multiple meta-omics samples, which can be used directly by other statistical programs.'),
(77404, 2013, 'bio', 'CePa: an R package for finding significant pathways weighted by multiple network centralities', 'Gu, Zuguang|Wang, Jin', 'The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Science, Department of Physics, Nanjing University, Nanjing 210093, China.|The State Key Laboratory of Pharmaceutical Biotechnology and Jiangsu Engineering Research Center for MicroRNA Biology and Biotechnology, School of Life Science, Department of Physics, Nanjing University, Nanjing 210093, China.', 'China|China', 26, 'Gene Expression Profiling|Gene Regulatory Networks|Software', 'Journal Article', '10.1093/bioinformatics/btt008', '23314125', 'CePa is an R package aiming to find significant pathways through network topology information. The package has several advantages compared with current pathway enrichment tools. First, pathway node instead of single gene is taken as the basic unit when analysing networks to meet the fact that genes must be constructed into complexes to hold normal functions. Second, multiple network centralities are applied simultaneously to measure importance of nodes from different aspects to make a full view on the biological system. CePa extends standard pathway enrichment methods, which include both over-representation analysis procedure and gene-set analysis procedure. CePa has been evaluated with high performance on real-world data, and it can provide more information directly related to current biological problems.'),
(77405, 2013, 'bio', 'Predicting protein xcexb2-sheet contacts using a maximum entropy-based correlated mutation measure', 'Burkoff, Nikolas S|Vxc3xa1rnai, Csilla|Wild, David L', 'Systems Biology Centre, Senate House, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, Senate House, University of Warwick, Coventry, CV4 7AL, UK.|Systems Biology Centre, Senate House, University of Warwick, Coventry, CV4 7AL, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Artificial Intelligence|Entropy|Models, Molecular|Models, Statistical|Mutation|Neural Networks (Computer)|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btt005', '23314126', 'The problem of ab initio protein folding is one of the most difficult in modern computational biology. The prediction of residue contacts within a protein provides a more tractable immediate step. Recently introduced maximum entropy-based correlated mutation measures (CMMs), such as direct information, have been successful in predicting residue contacts. However, most correlated mutation studies focus on proteins that have large good-quality multiple sequence alignments (MSA) because the power of correlated mutation analysis falls as the size of the MSA decreases. However, even with small autogenerated MSAs, maximum entropy-based CMMs contain information. To make use of this information, in this article, we focus not on general residue contacts but contacts between residues in xcexb2-sheets. The strong constraints and prior knowledge associated with xcexb2-contacts are ideally suited for prediction using a method that incorporates an often noisy CMM.'),
(77406, 2013, 'bio', 'gKaKs: the pipeline for genome-level Ka/Ks calculation', 'Zhang, Chengjun|Wang, Jun|Long, Manyuan|Fan, Chuanzhu', 'Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.|Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.|Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.|Department of Ecology and Evolution, University of Chicago, Chicago, IL 60637, USA.', 'United States|United States|United States|United States', 24, 'Animals|Codon|Codon, Terminator|Frameshift Mutation|Genomics|Humans|Mice|Rats|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btt009', '23314322', 'gKaKs is a codon-based genome-level Ka/Ks computation pipeline developed and based on programs from four widely used packages: BLAT, BLASTALL (including bl2seq, formatdb and fastacmd), PAML (including codeml and yn00) and KaKs_Calculator (including 10 substitution rate estimation methods). gKaKs can automatically detect and eliminate frameshift mutations and premature stop codons to compute the substitution rates (Ka, Ks and Ka/Ks) between a well-annotated genome and a non-annotated genome or even a poorly assembled scaffold dataset. It is especially useful for newly sequenced genomes that have not been well annotated. We applied gKaKs to estimate the genome-wide substitution rates in five pairs of closely related species. The average Ka and Ks computed by gKaKs were consistent with previous studies. We also compared the Ka, Ks and Ka/Ks of mouse and rat orthologous protein-coding genes estimated by gKaKs and based on the alignments generated by PAL2NAL. Results from two methods are compatible.'),
(77407, 2013, 'bio', 'ViralFusionSeq: accurately discover viral integration events and reconstruct fusion transcripts at single-base resolution', 'Li, Jing-Woei|Wan, Raymond|Yu, Chi-Shing|Co, Ngai Na|Wong, Nathalie|Chan, Ting-Fung', 'School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.|School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 50, 'Cell Line, Tumor|Gene Fusion|High-Throughput Nucleotide Sequencing|Humans|RNA|Sequence Analysis, DNA|Sequence Analysis, RNA|Software|Virus Integration', 'Journal Article', '10.1093/bioinformatics/btt011', '23314323', 'Insertional mutagenesis from virus infection is an important pathogenic risk for the development of cancer. Despite the advent of high-throughput sequencing, discovery of viral integration sites and expressed viral fusion events are still limited. Here, we present ViralFusionSeq (VFS), which combines soft-clipping information, read-pair analysis and targeted de novo assembly to discover and annotate viral-human fusions. VFS was used in an RNA-Seq experiment, simulated DNA-Seq experiment and re-analysis of published DNA-Seq datasets. Our experiments demonstrated that VFS is both sensitive and highly accurate.'),
(77408, 2013, 'bio', 'NGSUtils: a software suite for analyzing and manipulating next-generation sequencing datasets', 'Breese, Marcus R|Liu, Yunlong', 'Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.|Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA.', 'India|India', 0, 'Genomics|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1093/bioinformatics/bts731', '23314324', 'NGSUtils is a suite of software tools for manipulating data common to next-generation sequencing experiments, such as FASTQ, BED and BAM format files. These tools provide a stable and modular platform for data management and analysis.'),
(77409, 2013, 'bio', 'Fast alignment and comparison of RNA structures', 'Wiegels, Tim|Bienert, Stefan|Torda, Andrew E', 'Centre for Bioinformatics, University of Hamburg, Bundesstr. 43, D-20146 Hamburg, Germany. tim.wiegels@gmail.com|Centre for Bioinformatics, University of Hamburg, Bundesstr. 43, D-20146 Hamburg, Germany. tim.wiegels@gmail.com|Centre for Bioinformatics, University of Hamburg, Bundesstr. 43, D-20146 Hamburg, Germany. tim.wiegels@gmail.com', 'Germany|Germany|Germany', 0, 'Algorithms|Databases, Protein|Models, Molecular|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btt006', '23314325', 'To recognize remote relationships between RNA molecules, one must be able to align structures without regard to sequence similarity. We have implemented a method, which is swift [O(n(2))], sensitive and tolerant of large gaps and insertions. Molecules are broken into overlapping fragments, which are characterized by their memberships in a probabilistic classification based on local geometry and H-bonding descriptors. This leads to a probabilistic similarity measure that is used in a conventional dynamic programming method.'),
(77410, 2013, 'bio', 'Reconciling differential gene expression data with molecular interaction networks', 'Poirel, Christopher L|Rahman, Ahsanur|Rodrigues, Richard R|Krishnan, Arjun|Addesa, Jacqueline R|Murali, T M', 'Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.|Department of Computer Science, Virginia Tech, Blacksburg, VA, USA.', 'United States|United States|United States|United States|United States|United States', 8, 'Algorithms|Alzheimer Disease|Biological Transport|Brain|Gene Expression Profiling|Gene Regulatory Networks|Glucose|Humans|Huntington Disease|Insulin|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btt007', '23314326', 'Many techniques have been developed to compute the response network of a cell. A recent trend in this area is to compute response networks of small size, with the rationale that only part of a pathway is often changed by disease and that interpreting small subnetworks is easier than interpreting larger ones. However, these methods may not uncover the spectrum of pathways perturbed in a particular experiment or disease.'),
(77411, 2013, 'bio', 'Scotty: a web tool for designing RNA-Seq experiments to measure differential gene expression', 'Busby, Michele A|Stewart, Chip|Miller, Chase A|Grzeda, Krzysztof R|Marth, Gabor T', 'Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.', 'United States|United States|United States|United States|United States', 0, 'Gene Expression|Gene Expression Profiling|Humans|Internet|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt015', '23314327', 'A common question arises at the beginning of every experiment where RNA-Seq is used to detect differential gene expression between two conditions: How many reads should we sequence?'),
(77412, 2013, 'bio', 'DSK: k-mer counting with very low memory usage', 'Rizk, Guillaume|Lavenier, Dominique|Chikhi, Rayan', 'Algorizk, 75013 Paris, France.|Algorizk, 75013 Paris, France.|Algorizk, 75013 Paris, France.', 'France|France|France', 136, 'Algorithms|Genome, Human|Humans|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt020', '23325618', 'Counting all the k-mers (substrings of length k) in DNA/RNA sequencing reads is the preliminary step of many bioinformatics applications. However, state of the art k-mer counting methods require that a large data structure resides in memory. Such structure typically grows with the number of distinct k-mers to count. We present a new streaming algorithm for k-mer counting, called DSK (disk streaming of k-mers), which only requires a fixed user-defined amount of memory and disk space. This approach realizes a memory, time and disk trade-off. The multi-set of all k-mers present in the reads is partitioned, and partitions are saved to disk. Then, each partition is separately loaded in memory in a temporary hash table. The k-mer counts are returned by traversing each hash table. Low-abundance k-mers are optionally filtered. DSK is the first approach that is able to count all the 27-mers of a human genome dataset using only 4.0 GB of memory and moderate disk space (160 GB), in 17.9 h. DSK can replace a popular k-mer counting software (Jellyfish) on small-memory servers.'),
(77413, 2013, 'bio', 'miRCancer: a microRNA-cancer association database constructed by text mining on literature', 'Xie, Boya|Ding, Qin|Han, Hongjin|Wu, Di', 'Department of Computer Science, East Carolina University, Greenville, NC 27858 and Department of Physiology, Brody School of Medicine, East Carolina University, Greenville, NC 27834, USA.|Department of Computer Science, East Carolina University, Greenville, NC 27858 and Department of Physiology, Brody School of Medicine, East Carolina University, Greenville, NC 27834, USA.|Department of Computer Science, East Carolina University, Greenville, NC 27858 and Department of Physiology, Brody School of Medicine, East Carolina University, Greenville, NC 27834, USA.|Department of Computer Science, East Carolina University, Greenville, NC 27858 and Department of Physiology, Brody School of Medicine, East Carolina University, Greenville, NC 27834, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Data Mining|Databases, Nucleic Acid|Humans|Internet|MicroRNAs|Neoplasms|PubMed', 'Journal Article', '10.1093/bioinformatics/btt014', '23325619', 'Research interests in microRNAs have increased rapidly in the past decade. Many studies have showed that microRNAs have close relationships with various human cancers, and they potentially could be used as cancer indicators in diagnosis or as a suppressor for treatment purposes. There are several databases that contain microRNA-cancer associations predicted by computational methods but few from empirical results. Despite the fact that abundant experiments investigating microRNA expressions in cancer cells have been carried out, the results have remain scattered in the literature. We propose to extract microRNA-cancer associations by text mining and store them in a database called miRCancer.'),
(77414, 2013, 'bio', 'Sparsely correlated hidden Markov models with application to genome-wide location studies', 'Choi, Hyungwon|Fermin, Damian|Nesvizhskii, Alexey I|Ghosh, Debashis|Qin, Zhaohui S', 'National University of Singapore and National University Health System, Singapore 117597, Singapore.|National University of Singapore and National University Health System, Singapore 117597, Singapore.|National University of Singapore and National University Health System, Singapore 117597, Singapore.|National University of Singapore and National University Health System, Singapore 117597, Singapore.|National University of Singapore and National University Health System, Singapore 117597, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 0, 'Algorithms|CD4-Positive T-Lymphocytes|Chromatin Immunoprecipitation|Genome|Genomics|High-Throughput Nucleotide Sequencing|Histones|Humans|Markov Chains|Models, Statistical|Transcription, Genetic', 'Journal Article', '10.1093/bioinformatics/btt012', '23325620', 'Multiply correlated datasets have become increasingly common in genome-wide location analysis of regulatory proteins and epigenetic modifications. Their correlation can be directly incorporated into a statistical model to capture underlying biological interactions, but such modeling quickly becomes computationally intractable.'),
(77415, 2013, 'bio', 'CRAVAT: cancer-related analysis of variants toolkit', 'Douville, Christopher|Carter, Hannah|Kim, Rick|Niknafs, Noushin|Diekhans, Mark|Stenson, Peter D|Cooper, David N|Ryan, Michael|Karchin, Rachel', 'Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.|Department of Biomedical Engineering, Institute for Computational Medicine, Johns Hopkins University, Baltimore, MD 21218, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 73, 'Genomics|Humans|Internet|Mutation|Neoplasms|Software', 'Journal Article', '10.1093/bioinformatics/btt017', '23325621', 'Advances in sequencing technology have greatly reduced the costs incurred in collecting raw sequencing data. Academic laboratories and researchers therefore now have access to very large datasets of genomic alterations but limited time and computational resources to analyse their potential biological importance. Here, we provide a web-based application, Cancer-Related Analysis of Variants Toolkit, designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis. Cancer-Related Analysis of Variants Toolkit provides predictive scores for germline variants, somatic mutations and relative gene importance, as well as annotations from published literature and databases. Results are emailed to users as MS Excel spreadsheets and/or tab-separated text files.'),
(77416, 2013, 'bio', 'CluePedia Cytoscape plugin: pathway insights using integrated experimental and in silico data', 'Bindea, Gabriela|Galon, Jérôme|Mlecnik, Bernhard', 'INSERM, Laboratory of Integrative Cancer Immunology, 75006 Paris, France.|INSERM, Laboratory of Integrative Cancer Immunology, 75006 Paris, France.|INSERM, Laboratory of Integrative Cancer Immunology, 75006 Paris, France.', 'France|France|France', 0, 'Animals|Computer Simulation|Gene Regulatory Networks|Humans|Mice|MicroRNAs|Proteins|Software', 'Journal Article', '10.1093/bioinformatics/btt019', '23325622', 'The CluePedia Cytoscape plugin is a search tool for new markers potentially associated to pathways. CluePedia calculates linear and non-linear statistical dependencies from experimental data. Genes, proteins and miRNAs can be connected based on in silico and/or experimental information and integrated into a ClueGO network of terms/pathways. Interrelations within each pathway can be investigated, and new potential associations may be revealed through gene/protein/miRNA enrichments. A pathway-like visualization can be created using the Cerebral plugin layout. Combining all these features is essential for data interpretation and the generation of new hypotheses. The CluePedia Cytoscape plugin is user-friendly and has an expressive and intuitive visualization.'),
(77417, 2013, 'bio', 'The product of C9orf72, a gene strongly implicated in neurodegeneration, is structurally related to DENN Rab-GEFs', 'Levine, Timothy P|Daniels, Rachel D|Gatta, Alberto T|Wong, Louise H|Hayes, Matthew J', 'Department of Cell Biology, UCL Institute of Ophthalmology, Bath St, London EC1V 9EL, UK. tim.levine@ucl.ac.uk|Department of Cell Biology, UCL Institute of Ophthalmology, Bath St, London EC1V 9EL, UK. tim.levine@ucl.ac.uk|Department of Cell Biology, UCL Institute of Ophthalmology, Bath St, London EC1V 9EL, UK. tim.levine@ucl.ac.uk|Department of Cell Biology, UCL Institute of Ophthalmology, Bath St, London EC1V 9EL, UK. tim.levine@ucl.ac.uk|Department of Cell Biology, UCL Institute of Ophthalmology, Bath St, London EC1V 9EL, UK. tim.levine@ucl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 217, 'Amyotrophic Lateral Sclerosis|C9orf72 Protein|Frontotemporal Dementia|Guanine Nucleotide Exchange Factors|Humans|Protein Structure, Tertiary|Proteins|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/bts725', '23329412', 'Fronto-temporal dementia (FTD) and amyotrophic lateral sclerosis (ALS, also called motor neuron disease, MND) are severe neurodegenerative diseases that show considerable overlap at the clinical and cellular level. The most common single mutation in families with FTD or ALS has recently been mapped to a non-coding repeat expansion in the uncharacterized gene C9ORF72. Although a plausible mechanism for disease is that aberrant C9ORF72 mRNA poisons splicing, it is important to determine the cellular function of C9ORF72, about which nothing is known.'),
(77418, 2013, 'bio', 'Grape RNA-Seq analysis pipeline environment', 'Knowles, David G|Röder, Maik|Merkel, Angelika|Guigó, Roderic', 'Bioinformatics and Genomics Group, Centre for Genomic Regulation (CRG) and Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain. david.gonzalez@crg.eu|Bioinformatics and Genomics Group, Centre for Genomic Regulation (CRG) and Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain. david.gonzalez@crg.eu|Bioinformatics and Genomics Group, Centre for Genomic Regulation (CRG) and Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain. david.gonzalez@crg.eu|Bioinformatics and Genomics Group, Centre for Genomic Regulation (CRG) and Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003 Barcelona, Spain. david.gonzalez@crg.eu', 'Spain|Spain|Spain|Spain', 19, 'Chromosome Mapping|Computational Biology|Exons|Gene Expression Profiling|Genome|High-Throughput Nucleotide Sequencing|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btt016', '23329413', 'The avalanche of data arriving since the development of NGS technologies have prompted the need for developing fast, accurate and easily automated bioinformatic tools capable of dealing with massive datasets. Among the most productive applications of NGS technologies is the sequencing of cellular RNA, known as RNA-Seq. Although RNA-Seq provides similar or superior dynamic range than microarrays at similar or lower cost, the lack of standard and user-friendly pipelines is a bottleneck preventing RNA-Seq from becoming the standard for transcriptome analysis.'),
(77419, 2013, 'bio', 'Searching for virus phylotypes', 'Chevenet, François|Jung, Matthieu|Peeters, Martine|de Oliveira, Tulio|Gascuel, Olivier', 'Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr|Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr|Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr|Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr|Institut de Biologie Computationnelle, LIRMM, UMR 5506 CNRS - Université Montpellier 2, Montpellier, France. francois.chevenet@ird.fr', 'France|France|France|France|France', 18, 'Algorithms|HIV Infections|HIV-1|Humans|Internet|Phylogeny|Software|Viruses', 'Journal Article', '10.1093/bioinformatics/btt010', '23329414', 'Large phylogenies are being built today to study virus evolution, trace the origin of epidemics, establish the mode of transmission and survey the appearance of drug resistance. However, no tool is available to quickly inspect these phylogenies and combine them with extrinsic traits (e.g. geographic location, risk group, presence of a given resistance mutation), seeking to extract strain groups of specific interest or requiring surveillance.'),
(77420, 2013, 'bio', 'SBSI: an extensible distributed software infrastructure for parameter estimation in systems biology', 'Adams, Richard|Clark, Allan|Yamaguchi, Azusa|Hanlon, Neil|Tsorman, Nikos|Ali, Shakir|Lebedeva, Galina|Goltsov, Alexey|Sorokin, Anatoly|Akman, Ozgur E|Troein, Carl|Millar, Andrew J|Goryanin, Igor|Gilmore, Stephen', 'SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, UK.|SynthSys Edinburgh, Kings Buildings, University of Edinburgh, Edinburgh, 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', 12, 'Algorithms|Software|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btt023', '23329415', 'Complex computational experiments in Systems Biology, such as fitting model parameters to experimental data, can be challenging to perform. Not only do they frequently require a high level of computational power, but the software needed to run the experiment needs to be usable by scientists with varying levels of computational expertise, and modellers need to be able to obtain up-to-date experimental data resources easily. We have developed a software suite, the Systems Biology Software Infrastructure (SBSI), to facilitate the parameter-fitting process. SBSI is a modular software suite composed of three major components: SBSINumerics, a high-performance library containing parallelized algorithms for performing parameter fitting, SBSIDispatcher, a middleware application to track experiments and submit jobs to back-end servers, and SBSIVisual, an extensible client application used to configure optimization experiments and view results. Furthermore, we have created a plugin infrastructure to enable project-specific modules to be easily installed. Plugin developers can take advantage of the existing user-interface and application framework to customize SBSI for their own uses, facilitated by SBSIs use of standard data formats.'),
(77421, 2013, 'bio', 'PreDNA: accurate prediction of DNA-binding sites in proteins by integrating sequence and geometric structure information', 'Li, Tao|Li, Qian-Zhong|Liu, Shuai|Fan, Guo-Liang|Zuo, Yong-Chun|Peng, Yong', 'Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.|Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.|Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.|Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.|Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.|Laboratory of Theoretical Biophysics, School of Physical Sciences and Technology, College of Computer Science and The National Research Center for Animal Transgenic Biotechnology, Inner Mongolia University, Hohhot, 010021, China.', 'China|China|China|China|China|China', 28, 'Algorithms|Binding Sites|DNA|DNA-Binding Proteins|Protein Structure, Secondary|ROC Curve|Sequence Analysis, Protein|Support Vector Machine', 'Journal Article', '10.1093/bioinformatics/btt029', '23335013', 'Protein-DNA interactions often take part in various crucial processes, which are essential for cellular function. The identification of DNA-binding sites in proteins is important for understanding the molecular mechanisms of protein-DNA interaction. Thus, we have developed an improved method to predict DNA-binding sites by integrating structural alignment algorithm and support vector machine-based methods.'),
(77422, 2013, 'bio', 'StatAlign 20: combining statistical alignment with RNA secondary structure prediction', 'Arunapuram, Preeti|Edvardsson, Ingolfur|Golden, Michael|Anderson, James W J|Novák, Adám|Sükösd, Zsuzsanna|Hein, Jotun', 'Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.|Department of Computer Science, University of North Carolina at Chapel Hill, NC 27599, USA.', 'United States|United States|United States|United States|United States|United States|United States', 8, 'Algorithms|Base Pairing|Bayes Theorem|Markov Chains|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software|Thermodynamics', 'Journal Article', '10.1093/bioinformatics/btt025', '23335014', 'Comparative modeling of RNA is known to be important for making accurate secondary structure predictions. RNA structure prediction tools such as PPfold or RNAalifold use an aligned set of sequences in predictions. Obtaining a multiple alignment from a set of sequences is quite a challenging problem itself, and the quality of the alignment can affect the quality of a prediction. By implementing RNA secondary structure prediction in a statistical alignment framework, and predicting structures from multiple alignment samples instead of a single fixed alignment, it may be possible to improve predictions.'),
(77423, 2013, 'bio', 'Systematic inference of highways of horizontal gene transfer in prokaryotes', 'Bansal, Mukul S|Banay, Guy|Harlow, Timothy J|Gogarten, J Peter|Shamir, Ron', 'The Blavatnik School of Computer Science, Tel-Aviv University, Ramat Aviv, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Ramat Aviv, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Ramat Aviv, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Ramat Aviv, Tel Aviv 69978, Israel.|The Blavatnik School of Computer Science, Tel-Aviv University, Ramat Aviv, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel', 12, 'Algorithms|Bacteria|Evolution, Molecular|Gene Transfer, Horizontal|Genes, Bacterial|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btt021', '23335015', 'Horizontal gene transfer (HGT) plays a crucial role in the evolution of prokaryotic species. Typically, no more than a few genes are horizontally transferred between any two species. However, several studies identified pairs of species (or linages) between which many different genes were horizontally transferred. Such a pair is said to be linked by a highway of gene sharing. Inferring such highways is crucial to understanding the evolution of prokaryotes and for inferring past symbiotic and ecological associations among different species.'),
(77424, 2013, 'bio', 'A coherent feedforward loop design principle to sustain robustness of biological networks', 'Le, Duc-Hau|Kwon, Yung-Keun', 'School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Republic of Korea.|School of Electrical Engineering, University of Ulsan, 93 Daehak-ro, Nam-gu, Ulsan 680-749, Republic of Korea.', '-|-', 23, 'Feedback, Physiological|Gene Regulatory Networks|Humans|Models, Biological|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btt026', '23335016', 'Many studies have investigated the relationship between structural properties and dynamic behaviors in biological networks. In particular, feedback loop (FBL) and feedforward loop (FFL) structures have received a great deal of attention. One interesting and common property of FBL and FFL structures is their coherency of coupling. However, the role of coherent FFLs in relation to network robustness is not fully known, whereas that of coherent FBLs has been well established.');
