INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94235, 2011, 'bmc', 'A theoretical entropy score as a single value to express inhibitor selectivity', 'Uitdehaag, Joost C M|Zaman, Guido J R', 'Merck Research Laboratories, Department of Molecular Pharmacology, Oss, The Netherlands. joost.uitdehaag@merck.com|Merck Research Laboratories, Department of Molecular Pharmacology, Oss, The Netherlands. joost.uitdehaag@merck.com', 'Netherlands|Netherlands', 28, 'Drug Discovery|Entropy|High-Throughput Screening Assays|Humans|Ligands|Protein Kinase Inhibitors|Receptors, Cytoplasmic and Nuclear|Software Design', 'Journal Article', '10.1186/1471-2105-12-94', '21486481', 'Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.'),
(94236, 2011, 'bmc', 'Assessing the benefits of using mate-pairs to resolve repeats in de novo short-read prokaryotic assemblies', 'Wetzel, Joshua|Kingsford, Carl|Pop, Mihai', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD, USA.', 'United States|United States|United States', 36, 'Bacteria|Genome, Bacterial|High-Throughput Nucleotide Sequencing|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-95', '21486487', 'Next-generation sequencing technologies allow genomes to be sequenced more quickly and less expensively than ever before. However, as sequencing technology has improved, the difficulty of de novo genome assembly has increased, due in large part to the shorter reads generated by the new technologies. The use of mated sequences (referred to as mate-pairs) is a standard means of disambiguating assemblies to obtain a more complete picture of the genome without resorting to manual finishing. Here, we examine the effectiveness of mate-pair information in resolving repeated sequences in the DNA (a paramount issue to overcome). While it has been empirically accepted that mate-pairs improve assemblies, and a variety of assemblers use mate-pairs in the context of repeat resolution, the effectiveness of mate-pairs in this context has not been systematically evaluated in previous literature.'),
(94237, 2011, 'bmc', 'A linguistic rule-based approach to extract drug-drug interactions from pharmacological documents', 'Segura-Bedmar, Isabel|Martínez, Paloma|de Pablo-Sánchez, César', 'Computer Science Department, University Carlos III of Madrid, Leganés, 28911, Spain. isegura@inf.uc3m.es|Computer Science Department, University Carlos III of Madrid, Leganés, 28911, Spain. isegura@inf.uc3m.es|Computer Science Department, University Carlos III of Madrid, Leganés, 28911, Spain. isegura@inf.uc3m.es', 'Spain|Spain|Spain', 0, 'Algorithms|Artificial Intelligence|Drug Interactions|Information Storage and Retrieval|Linguistics|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-12-S2-S1', '21489220', 'A drug-drug interaction (DDI) occurs when one drug influences the level or activity of another drug. The increasing volume of the scientific literature overwhelms health care professionals trying to be kept up-to-date with all published studies on DDI.'),
(94238, 2011, 'bmc', 'Building the process-drug-side effect network to discover the relationship between biological processes and side effects', 'Lee, Sejoon|Lee, Kwang H|Song, Min|Lee, Doheon', 'Bio and Brain Engineering Department, KAIST, Daejeon 305-701, South Korea.|Bio and Brain Engineering Department, KAIST, Daejeon 305-701, South Korea.|Bio and Brain Engineering Department, KAIST, Daejeon 305-701, South Korea.|Bio and Brain Engineering Department, KAIST, Daejeon 305-701, South Korea.', '-|-|-|-', 0, 'Adverse Drug Reaction Reporting Systems|Computational Biology|Data Mining|Databases as Topic|Drug-Related Side Effects and Adverse Reactions|Humans|Phenotype', 'Journal Article', '10.1186/1471-2105-12-S2-S2', '21489221', 'Side effects are unwanted responses to drug treatment and are important resources for human phenotype information. The recent development of a database on side effects, the side effect resource (SIDER), is a first step in documenting the relationship between drugs and their side effects. It is, however, insufficient to simply find the association of drugs with biological processes, that relationship is crucial because drugs that influence biological processes can have an impact on phenotype. Therefore, knowing which processes respond to drugs that influence the phenotype will enable more effective and systematic study of the effect of drugs on phenotype. To the best of our knowledge, the relationship between biological processes and side effects of drugs has not yet been systematically researched.'),
(94239, 2011, 'bmc', 'Context-specific gene regulatory networks subdivide intrinsic subtypes of breast cancer', 'Nasser, Sara|Cunliffe, Heather E|Black, Michael A|Kim, Seungchan', 'Computational Biology Division, Translational Genomics Research Institute, 445 N, Fifth Street, Phoenix, AZ, USA.|Computational Biology Division, Translational Genomics Research Institute, 445 N, Fifth Street, Phoenix, AZ, USA.|Computational Biology Division, Translational Genomics Research Institute, 445 N, Fifth Street, Phoenix, AZ, USA.|Computational Biology Division, Translational Genomics Research Institute, 445 N, Fifth Street, Phoenix, AZ, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Breast Neoplasms|Cluster Analysis|Computational Biology|Data Mining|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Humans|Survival Analysis', 'Journal Article', '10.1186/1471-2105-12-S2-S3', '21489222', 'Breast cancer is a highly heterogeneous disease with respect to molecular alterations and cellular composition making therapeutic and clinical outcome unpredictable. This diversity creates a significant challenge in developing tumor classifications that are clinically reliable with respect to prognosis prediction.'),
(94240, 2011, 'bmc', 'Word sense disambiguation for event trigger word detection in biomedicine', 'Martinez, David|Baldwin, Timothy', 'NICTA VRL, The University of Melbourne, VIC 3010, Australia. david.martinez@nicta.com.au|NICTA VRL, The University of Melbourne, VIC 3010, Australia. david.martinez@nicta.com.au', 'Australia|Australia', 0, 'Algorithms|Computational Biology|Natural Language Processing|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-12-S2-S4', '21489223', 'This paper describes a method for detecting event trigger words in biomedical text based on a word sense disambiguation (WSD) approach. We first investigate the applicability of existing WSD techniques to trigger word disambiguation in the BioNLP 2009 shared task data, and find that we are able to outperform a traditional CRF-based approach for certain word types. On the basis of this finding, we combine the WSD approach with the CRF, and obtain significant improvements over the standalone CRF, gaining particularly in recall.'),
(94241, 2011, 'bmc', 'Automatic classification of sentences to support Evidence Based Medicine', 'Kim, Su Nam|Martinez, David|Cavedon, Lawrence|Yencken, Lars', 'NICTA VRL, The University of Melbourne, 3010, Australia.|NICTA VRL, The University of Melbourne, 3010, Australia.|NICTA VRL, The University of Melbourne, 3010, Australia.|NICTA VRL, The University of Melbourne, 3010, Australia.', 'Australia|Australia|Australia|Australia', 0, 'Abstracting and Indexing as Topic|Electronic Data Processing|Evidence-Based Medicine|Information Storage and Retrieval|Natural Language Processing|Semantics', 'Journal Article', '10.1186/1471-2105-12-S2-S5', '21489224', 'Given a set of pre-defined medical categories used in Evidence Based Medicine, we aim to automatically annotate sentences in medical abstracts with these labels.'),
(94242, 2011, 'bmc', 'Processing SPARQL queries with regular expressions in RDF databases', 'Lee, Jinsoo|Pham, Minh-Duc|Lee, Jihwan|Han, Wook-Shin|Cho, Hune|Yu, Hwanjo|Lee, Jeong-Hoon', 'Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.|Department of Computer Engineering, Kyungpook National University, Daegu, Korea.', '-|-|-|-|-|-|-', 0, 'Algorithms|Computational Biology|Databases, Factual|Information Storage and Retrieval|Internet|Knowledge Bases|Programming Languages|Semantics|Software', 'Journal Article', '10.1186/1471-2105-12-S2-S6', '21489225', 'As the Resource Description Framework (RDF) data model is widely used for modeling and sharing a lot of online bioinformatics resources such as Uniprot (dev.isb-sib.ch/projects/uniprot-rdf) or Bio2RDF (bio2rdf.org), SPARQL - a W3C recommendation query for RDF databases - has become an important query language for querying the bioinformatics knowledge bases. Moreover, due to the diversity of users requests for extracting information from the RDF data as well as the lack of users knowledge about the exact value of each fact in the RDF databases, it is desirable to use the SPARQL query with regular expression patterns for querying the RDF data. To the best of our knowledge, there is currently no work that efficiently supports regular expression processing in SPARQL over RDF databases. Most of the existing techniques for processing regular expressions are designed for querying a text corpus, or only for supporting the matching over the paths in an RDF graph.'),
(94243, 2011, 'bmc', 'Classification of viral zoonosis through receptor pattern analysis', 'Bae, Se-Eun|Son, Hyeon Seok', 'Laboratory of Computational Biology & Bioinformatics, Institute of Health and Environment, Graduate School of Public Health, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea.|Laboratory of Computational Biology & Bioinformatics, Institute of Health and Environment, Graduate School of Public Health, Seoul National University, 599 Gwanak-ro, Gwanak-gu, Seoul 151-742, Korea.', '-|-', 5, 'Amino Acid Sequence|Animals|Computational Biology|Humans|Hydrophobic and Hydrophilic Interactions|Receptors, Virus|Virus Diseases|Viruses|Zoonoses', 'Journal Article', '10.1186/1471-2105-12-96', '21489240', 'Viral zoonosis, the transmission of a virus from its primary vertebrate reservoir species to humans, requires ubiquitous cellular proteins known as receptor proteins. Zoonosis can occur not only through direct transmission from vertebrates to humans, but also through intermediate reservoirs or other environmental factors. Viruses can be categorized according to genotype (ssDNA, dsDNA, ssRNA and dsRNA viruses). Among them, the RNA viruses exhibit particularly high mutation rates and are especially problematic for this reason. Most zoonotic viruses are RNA viruses that change their envelope proteins to facilitate binding to various receptors of host species. In this study, we sought to predict zoonotic propensity through the analysis of receptor characteristics. We hypothesized that the major barrier to interspecies virus transmission is that receptor sequences vary among species--in other words, that the specific amino acid sequence of the receptor determines the ability of the viral envelope protein to attach to the cell.'),
(94244, 2010, 'bmc', 'UT-ORNL-KBRIN Bioinformatics Summit 2010 Cadiz, KY, USA 19-21 March 2010 Abstracts', '-', '-', '-', 5, 'Computational Biology', 'Congress', '10.1186/1471-2105-12-96', '21495228', '-'),
(94245, 2010, 'bmc', 'Sixth International Society for Computational Biology (ISCB) Student Council Symposium Boston, MA, USA 9 July 2010 Abstracts', '-', '-', '-', 5, 'Computational Biology', 'Congress', '10.1186/1471-2105-12-96', '21495240', '-'),
(94246, 2011, 'bmc', 'Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms', 'Milnthorpe, Andrew T|Soloviev, Mikhail', 'School of Biological Sciences, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK. A.T.Milnthorpe@rhul.ac.uk|School of Biological Sciences, Royal Holloway, University of London, Egham, Surrey, TW20 0EX, UK. A.T.Milnthorpe@rhul.ac.uk', 'United Kingdom|United Kingdom', 2, 'Algorithms|DNA, Complementary|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Library|Genome|Humans|Neoplasms', 'Journal Article', '10.1186/1471-2105-12-97', '21496233', 'The Cancer Genome Anatomy Project (CGAP) xProfiler and cDNA Digital Gene Expression Displayer (DGED) have been made available to the scientific community over a decade ago and since then were used widely to find genes which are differentially expressed between cancer and normal tissues. The tissue types are usually chosen according to the ontology hierarchy developed by NCBI. The xProfiler uses an internally available flat file database to determine the presence or absence of genes in the chosen libraries, while cDNA DGED uses the publicly available UniGene Expression and Gene relational databases to count the sequences found for each gene in the presented libraries.'),
(94247, 2011, 'bmc', 'CDAO-store: ontology-driven data integration for phylogenetic analysis', 'Chisham, Brandon|Wright, Ben|Le, Trung|Son, Tran Cao|Pontelli, Enrico', 'Department of Computer Science, New Mexico State University, Las Cruces, USA.|Department of Computer Science, New Mexico State University, Las Cruces, USA.|Department of Computer Science, New Mexico State University, Las Cruces, USA.|Department of Computer Science, New Mexico State University, Las Cruces, USA.|Department of Computer Science, New Mexico State University, Las Cruces, USA.', 'Mexico|Mexico|Mexico|Mexico|Mexico', 15, 'Algorithms|Biological Evolution|Classification|Information Storage and Retrieval|Internet|Phylogeny|Semantics|Software', 'Journal Article', '10.1186/1471-2105-12-98', '21496247', 'The Comparative Data Analysis Ontology (CDAO) is an ontology developed, as part of the EvoInfo and EvoIO groups supported by the National Evolutionary Synthesis Center, to provide semantic descriptions of data and transformations commonly found in the domain of phylogenetic analysis. The core concepts of the ontology enable the description of phylogenetic trees and associated character data matrices.'),
(94248, 2011, 'bmc', 'SNP-based pathway enrichment analysis for genome-wide association studies', 'Weng, Lingjie|Macciardi, Fabio|Subramanian, Aravind|Guffanti, Guia|Potkin, Steven G|Yu, Zhaoxia|Xie, Xiaohui', 'Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.|Department of Computer Science, University of California, Irvine, USA.', 'United States|United States|United States|United States|United States|United States|United States', 89, 'Genetic Variation|Genome-Wide Association Study|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Research Design|Schizophrenia|Software', 'Journal Article', '10.1186/1471-2105-12-99', '21496265', 'Recently we have witnessed a surge of interest in using genome-wide association studies (GWAS) to discover the genetic basis of complex diseases. Many genetic variations, mostly in the form of single nucleotide polymorphisms (SNPs), have been identified in a wide spectrum of diseases, including diabetes, cancer, and psychiatric diseases. A common theme arising from these studies is that the genetic variations discovered by GWAS can only explain a small fraction of the genetic risks associated with the complex diseases. New strategies and statistical approaches are needed to address this lack of explanation. One such approach is the pathway analysis, which considers the genetic variations underlying a biological pathway, rather than separately as in the traditional GWAS studies. A critical challenge in the pathway analysis is how to combine evidences of association over multiple SNPs within a gene and multiple genes within a pathway. Most current methods choose the most significant SNP from each gene as a representative, ignoring the joint action of multiple SNPs within a gene. This approach leads to preferential identification of genes with a greater number of SNPs.'),
(94249, 2011, 'bmc', 'SAQC: SNP array quality control', 'Yang, Hsin-Chou|Lin, Hsin-Chi|Kang, Meijyh|Chen, Chun-Houh|Lin, Chien-Wei|Li, Ling-Hui|Wu, Jer-Yuarn|Chen, Yuan-Tsong|Pan, Wen-Harn', 'Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw|Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. hsinchou@stat.sinica.edu.tw', '-|-|-|-|-|-|-|-|-', 4, 'DNA|Gene Frequency|Genome, Human|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Quality Control', 'Journal Article', '10.1186/1471-2105-12-100', '21501472', 'Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed.'),
(94250, 2011, 'bmc', 'Implementation of force distribution analysis for molecular dynamics simulations', 'Stacklies, Wolfram|Seifert, Christian|Graeter, Frauke', 'CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China.|CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China.|CAS-MPG Partner Institute and Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, China.', 'China|China|China', 40, 'Biomechanical Phenomena|Humans|Models, Molecular|Molecular Dynamics Simulation|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-101', '21501475', 'The way mechanical stress is distributed inside and propagated by proteins and other biopolymers largely defines their function. Yet, determining the network of interactions propagating internal strain remains a challenge for both, experiment and theory. Based on molecular dynamics simulations, we developed force distribution analysis (FDA), a method that allows visualizing strain propagation in macromolecules.'),
(94251, 2011, 'bmc', 'Screening synteny blocks in pairwise genome comparisons through integer programming', 'Tang, Haibao|Lyons, Eric|Pedersen, Brent|Schnable, James C|Paterson, Andrew H|Freeling, Michael', 'Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com|Department of Plant and Microbial Biology, University of California, Berkeley, CA 94720, USA. tanghaibao@gmail.com', 'United States|United States|United States|United States|United States|United States', 68, 'Algorithms|Computer Simulation|Genome, Plant|Genomics|Plants|Programming, Linear|Software|Synteny', 'Journal Article', '10.1186/1471-2105-12-102', '21501495', 'It is difficult to accurately interpret chromosomal correspondences such as true orthology and paralogy due to significant divergence of genomes from a common ancestor. Analyses are particularly problematic among lineages that have repeatedly experienced whole genome duplication (WGD) events. To compare multiple subgenomes derived from genome duplications, we need to relax the traditional requirements of one-to-one syntenic matchings of genomic regions in order to reflect one-to-many or more generally many-to-many matchings. However this relaxation may result in the identification of synteny blocks that are derived from ancient shared WGDs that are not of interest. For many downstream analyses, we need to eliminate weak, low scoring alignments from pairwise genome comparisons. Our goal is to objectively select subset of synteny blocks whose total scores are maximized while respecting the duplication history of the genomes in comparison. We call this quota-based screening of synteny blocks in order to appropriately fill a quota of syntenic relationships within one genome or between two genomes having WGD events.'),
(94252, 2011, 'bmc', 'Multithreaded comparative RNA secondary structure prediction using stochastic context-free grammars', 'Sükösd, Zsuzsanna|Knudsen, Bjarne|Vaerum, Morten|Kjems, Jørgen|Andersen, Ebbe S', 'Interdisciplinary Nanoscience Center, Aarhus University, Denmark. zs@mb.au.dk|Interdisciplinary Nanoscience Center, Aarhus University, Denmark. zs@mb.au.dk|Interdisciplinary Nanoscience Center, Aarhus University, Denmark. zs@mb.au.dk|Interdisciplinary Nanoscience Center, Aarhus University, Denmark. zs@mb.au.dk|Interdisciplinary Nanoscience Center, Aarhus University, Denmark. zs@mb.au.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark', 21, 'Algorithms|Computational Biology|Genome, Viral|HIV-1|Nucleic Acid Conformation|Phylogeny|RNA|Sequence Alignment|Sequence Analysis, RNA|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-12-103', '21501497', 'The prediction of the structure of large RNAs remains a particular challenge in bioinformatics, due to the computational complexity and low levels of accuracy of state-of-the-art algorithms. The pfold model couples a stochastic context-free grammar to phylogenetic analysis for a high accuracy in predictions, but the time complexity of the algorithm and underflow errors have prevented its use for long alignments. Here we present PPfold, a multithreaded version of pfold, which is capable of predicting the structure of large RNA alignments accurately on practical timescales.'),
(94253, 2011, 'bmc', 'PhyloSim - Monte Carlo simulation of sequence evolution in the R statistical computing environment', 'Sipos, Botond|Massingham, Tim|Jordan, Gregory E|Goldman, Nick', 'EMBL-European Bioinformatics Institute, Hinxton, UK. sbotond@ebi.ac.uk|EMBL-European Bioinformatics Institute, Hinxton, UK. sbotond@ebi.ac.uk|EMBL-European Bioinformatics Institute, Hinxton, UK. sbotond@ebi.ac.uk|EMBL-European Bioinformatics Institute, Hinxton, UK. sbotond@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 28, 'Algorithms|Animals|Base Sequence|Computer Simulation|Evolution, Molecular|Humans|Mathematical Computing|Models, Genetic|Monte Carlo Method|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-12-104', '21504561', 'The Monte Carlo simulation of sequence evolution is routinely used to assess the performance of phylogenetic inference methods and sequence alignment algorithms. Progress in the field of molecular evolution fuels the need for more realistic and hence more complex simulations, adapted to particular situations, yet current software makes unreasonable assumptions such as homogeneous substitution dynamics or a uniform distribution of indels across the simulated sequences. This calls for an extensible simulation framework written in a high-level functional language, offering new functionality and making it easy to incorporate further complexity.'),
(94254, 2011, 'bmc', 'ENGINES: exploring single nucleotide variation in entire human genomes', 'Amigo, Jorge|Salas, Antonio|Phillips, Christopher', 'Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain. jorge.amigo@usc.es|Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain. jorge.amigo@usc.es|Grupo de Medicina Xenómica, CIBERER, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain. jorge.amigo@usc.es', 'Spain|Spain|Spain', 29, 'Databases, Genetic|Genetics, Population|Genome, Human|Human Genome Project|Humans|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-105', '21504571', 'Next generation ultra-sequencing technologies are starting to produce extensive quantities of data from entire human genome or exome sequences, and therefore new software is needed to present and analyse this vast amount of information. The 1000 Genomes project has recently released raw data for 629 complete genomes representing several human populations through their Phase I interim analysis and, although there are certain public tools available that allow exploration of these genomes, to date there is no tool that permits comprehensive population analysis of the variation catalogued by such data.'),
(94255, 2011, 'bmc', 'Swiftly computing center strings', 'Hufsky, Franziska|Kuchenbecker, Léon|Jahn, Katharina|Stoye, Jens|Böcker, Sebastian', 'Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, Jena, Germany. franziska.hufsky@uni-jena.de.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, Jena, Germany. franziska.hufsky@uni-jena.de.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, Jena, Germany. franziska.hufsky@uni-jena.de.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, Jena, Germany. franziska.hufsky@uni-jena.de.|Lehrstuhl für Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, Jena, Germany. franziska.hufsky@uni-jena.de.', 'Germany|Germany|Germany|Germany|Germany', 4, 'Algorithms|Bacteria|Cluster Analysis|Computational Biology|Genome, Bacterial|Genomics|Models, Genetic', 'Journal Article', '10.1186/1471-2105-12-106', '21504573', 'The center string (or closest string) problem is a classic computer science problem with important applications in computational biology. Given k input strings and a distance threshold d, we search for a string within Hamming distance at most d to each input string. This problem is NP complete.'),
(94256, 2011, 'bmc', 'MiRPara: a SVM-based software tool for prediction of most probable microRNA coding regions in genome scale sequences', 'Wu, Yonggan|Wei, Bo|Liu, Haizhou|Li, Tianxian|Rayner, Simon', 'Bioinformatics Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Science, PR of China.|Bioinformatics Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Science, PR of China.|Bioinformatics Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Science, PR of China.|Bioinformatics Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Science, PR of China.|Bioinformatics Group, State Key Laboratory of Virology, Wuhan Institute of Virology, Chinese Academy of Science, PR of China.', 'China|China|China|China|China', 0, 'Animals|Base Sequence|Computational Biology|Genome|Humans|MicroRNAs|Nucleic Acid Conformation|Open Reading Frames|Software|Species Specificity', 'Journal Article', '10.1186/1471-2105-12-107', '21504621', 'MicroRNAs are a family of ~22 nt small RNAs that can regulate gene expression at the post-transcriptional level. Identification of these molecules and their targets can aid understanding of regulatory processes. Recently, HTS has become a common identification method but there are two major limitations associated with the technique. Firstly, the method has low efficiency, with typically less than 1 in 10,000 sequences representing miRNA reads and secondly the method preferentially targets highly expressed miRNAs. If sequences are available, computational methods can provide a screening step to investigate the value of an HTS study and aid interpretation of results. However, current methods can only predict miRNAs for short fragments and have usually been trained against small datasets which dont always reflect the diversity of these molecules.'),
(94257, 2011, 'bmc', 'TurboFold: iterative probabilistic estimation of secondary structures for multiple RNA sequences', 'Harmanci, Arif O|Sharma, Gaurav|Mathews, David H', 'Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.|Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.|Department of Electrical and Computer Engineering, University of Rochester, Rochester, NY, USA.', 'United States|United States|United States', 60, 'Algorithms|Base Pairing|Base Sequence|Nucleic Acid Conformation|Probability|RNA|RNA, Untranslated|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-108', '21507242', 'The prediction of secondary structure, i.e. the set of canonical base pairs between nucleotides, is a first step in developing an understanding of the function of an RNA sequence. The most accurate computational methods predict conserved structures for a set of homologous RNA sequences. These methods usually suffer from high computational complexity. In this paper, TurboFold, a novel and efficient method for secondary structure prediction for multiple RNA sequences, is presented.'),
(94258, 2011, 'bmc', 'PheMaDB: a solution for storage, retrieval, and analysis of high throughput phenotype data', 'Chang, Wenling E|Sarver, Keri|Higgs, Brandon W|Read, Timothy D|Nolan, Nichole Me|Chapman, Carol E|Bishop-Lilly, Kimberly A|Sozhamannan, Shanmuga', 'Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org', 'United States|United States|United States|United States|United States|United States|United States|United States', 7, 'Bacillus anthracis|Databases, Factual|Information Storage and Retrieval|Internet|Microarray Analysis|Phenotype|Software', 'Journal Article', '10.1186/1471-2105-12-109', '21507258', 'OmniLog™ phenotype microarrays (PMs) have the capability to measure and compare the growth responses of biological samples upon exposure to hundreds of growth conditions such as different metabolites and antibiotics over a time course of hours to days. In order to manage the large amount of data produced from the OmniLog™ instrument, PheMaDB (Phenotype Microarray DataBase), a web-based relational database, was designed. PheMaDB enables efficient storage, retrieval and rapid analysis of the OmniLog™ PM data.'),
(94259, 2011, 'bmc', 'Was the Scanner Calibration Slide used for its intended purpose?', 'Zhang, Shannon|Zong, Yaping', 'Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org|Biotechnology, The MITRE Corporation, McLean, VA, USA. wchang@mitre.org', 'United States|United States', 0, 'Calibration|Fluorescence|Microarray Analysis|Sensitivity and Specificity', 'Letter', '10.1186/1471-2105-12-110', '21510874', 'In the article, Scanner calibration revisited, BMC Bioinformatics 2010, 11:361, Dr. Pozhitkov used the Scanner Calibration Slide, a key product of Full Moon BioSystems to generate data in his study of microarray scanner PMT response and proposed a mathematic model for PMT response 1. In the end, the author concluded that Full Moon BioSystems calibration slides are inadequate for performing calibration, and recommended against using these slides. We found these conclusions are seriously flawed and misleading, and his recommendation against using the Scanner Calibration Slide was not properly supported.'),
(94260, 2011, 'bmc', 'BICEPP: an example-based statistical text mining method for predicting the binary characteristics of drugs', 'Lin, Frank P Y|Anthony, Stephen|Polasek, Thomas M|Tsafnat, Guy|Doogue, Matthew P', 'Centre for Health Informatics, The University of New South Wales, Sydney, Australia. f.lin@unsw.edu.au|Centre for Health Informatics, The University of New South Wales, Sydney, Australia. f.lin@unsw.edu.au|Centre for Health Informatics, The University of New South Wales, Sydney, Australia. f.lin@unsw.edu.au|Centre for Health Informatics, The University of New South Wales, Sydney, Australia. f.lin@unsw.edu.au|Centre for Health Informatics, The University of New South Wales, Sydney, Australia. f.lin@unsw.edu.au', 'Australia|Australia|Australia|Australia|Australia', 0, 'Data Mining|Databases, Factual|Drug Interactions|Drug-Related Side Effects and Adverse Reactions|Humans|Pharmaceutical Preparations|Pharmacokinetics|Therapeutic Uses', 'Journal Article', '10.1186/1471-2105-12-112', '21510898', 'The identification of drug characteristics is a clinically important task, but it requires much expert knowledge and consumes substantial resources. We have developed a statistical text-mining approach (BInary Characteristics Extractor and biomedical Properties Predictor: BICEPP) to help experts screen drugs that may have important clinical characteristics of interest.'),
(94261, 2011, 'bmc', 'A fully automatic gridding method for cDNA microarray images', 'Rueda, Luis|Rezaeian, Iman', 'School of Computer Science, University of Windsor, Ontario, Canada. lrueda@uwindsor.ca|School of Computer Science, University of Windsor, Ontario, Canada. lrueda@uwindsor.ca', 'Canada|Canada', 36, 'Algorithms|Cluster Analysis|Image Processing, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results', 'Journal Article', '10.1186/1471-2105-12-113', '21510903', 'Processing cDNA microarray images is a crucial step in gene expression analysis, since any errors in early stages affect subsequent steps, leading to possibly erroneous biological conclusions. When processing the underlying images, accurately separating the sub-grids and spots is extremely important for subsequent steps that include segmentation, quantification, normalization and clustering.'),
(94262, 2011, 'bmc', 'Detection of recurrent rearrangement breakpoints from copy number data', 'Ritz, Anna|Paris, Pamela L|Ittmann, Michael M|Collins, Colin|Raphael, Benjamin J', 'Department of Computer Science, Brown University, Providence, RI, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. aritz@cs.brown.edu|Department of Computer Science, Brown University, Providence, RI, USA. aritz@cs.brown.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Chromosome Breakpoints|Comparative Genomic Hybridization|DNA Copy Number Variations|Gene Dosage|Glioblastoma|Humans|Male|Neoplasms|Prostatic Neoplasms|Protein Tyrosine Phosphatase, Non-Receptor Type 12|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-114', '21510904', 'Copy number variants (CNVs), including deletions, amplifications, and other rearrangements, are common in human and cancer genomes. Copy number data from array comparative genome hybridization (aCGH) and next-generation DNA sequencing is widely used to measure copy number variants. Comparison of copy number data from multiple individuals reveals recurrent variants. Typically, the interior of a recurrent CNV is examined for genes or other loci associated with a phenotype. However, in some cases, such as gene truncations and fusion genes, the target of variant lies at the boundary of the variant.'),
(94263, 2011, 'bmc', 'The proteogenomic mapping tool', 'Sanders, William S|Wang, Nan|Bridges, Susan M|Malone, Brandon M|Dandass, Yoginder S|McCarthy, Fiona M|Nanduri, Bindu|Lawrence, Mark L|Burgess, Shane C', 'Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.|Department of Computer Science & Engineering, Mississippi State University, MS, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Codon|Genomics|Mass Spectrometry|Molecular Sequence Annotation|Peptides|Protein Biosynthesis|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-12-115', '21513508', 'High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generation and to aid in structural genome annotation, experimentally observed peptides need to be mapped back to their source genome location quickly and exactly. Previously, the tools to do this have been limited to custom scripts designed by individual research groups to analyze their own data, are generally not widely available, and do not scale well with large eukaryotic genomes.'),
(94264, 2011, 'bmc', 'Ultra-fast sequence clustering from similarity networks with SiLiX', 'Miele, Vincent|Penel, Simon|Duret, Laurent', 'Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRIA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRIA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr|Laboratoire Biométrie et Biologie Evolutive, Université de Lyon, Université Lyon 1, CNRS, INRIA, UMR5558, Villeurbanne, France. vincent.miele@univ-lyon1.fr', 'France|France|France', 123, 'Algorithms|Animals|Base Sequence|Cluster Analysis|Databases, Genetic|Genes, Mitochondrial|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1186/1471-2105-12-116', '21513511', 'The number of gene sequences that are available for comparative genomics approaches is increasing extremely quickly. A current challenge is to be able to handle this huge amount of sequences in order to build families of homologous sequences in a reasonable time.'),
(94265, 2011, 'bmc', 'MI-GWAS: a SAS platform for the analysis of inherited and maternal genetic effects in genome-wide association studies using log-linear models', 'Agopian, A J|Mitchell, Laura E', 'Human Genetics Center, Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, 77030, USA.|Human Genetics Center, Division of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas School of Public Health, Houston, 77030, USA.', 'United States|United States', 8, 'Disease|Female|Genome-Wide Association Study|Humans|Linear Models|Male|Maternal-Fetal Exchange|Pregnancy|Risk Assessment|Software', 'Journal Article', '10.1186/1471-2105-12-117', '21513519', 'Several platforms for the analysis of genome-wide association data are available. However, these platforms focus on the evaluation of the genotype inherited by affected (i.e. case) individuals, whereas for some conditions (e.g. birth defects) the genotype of the mothers of affected individuals may also contribute to risk. For such conditions, it is critical to evaluate associations with both the maternal and the inherited (i.e. case) genotype. When genotype data are available for case-parent triads, a likelihood-based approach using log-linear modeling can be used to assess both the maternal and inherited genotypes. However, available software packages for log-linear analyses are not well suited to the analysis of typical genome-wide association data (e.g. including missing data).'),
(94266, 2011, 'bmc', 'Variance adjusted weighted UniFrac: a powerful beta diversity measure for comparing communities based on phylogeny', 'Chang, Qin|Luan, Yihui|Sun, Fengzhu', 'School of Mathematics, Shandong University, Jinan, Shandong, PR China.|School of Mathematics, Shandong University, Jinan, Shandong, PR China.|School of Mathematics, Shandong University, Jinan, Shandong, PR China.', 'China|China|China', 0, 'Animals|Bacteria|Ecology|Gastrointestinal Tract|Humans|Metagenome|Mice|Phylogeny|RNA, Bacterial|RNA, Ribosomal, 16S|Skin|Soil Microbiology', 'Journal Article', '10.1186/1471-2105-12-118', '21518444', 'Beta diversity, which involves the assessment of differences between communities, is an important problem in ecological studies. Many statistical methods have been developed to quantify beta diversity, and among them, UniFrac and weighted-UniFrac (W-UniFrac) are widely used. The W-UniFrac is a weighted sum of branch lengths in a phylogenetic tree of the sequences from the communities. However, W-UniFrac does not consider the variation of the weights under random sampling resulting in less power detecting the differences between communities.'),
(94267, 2011, 'bmc', 'ShoRAH: estimating the genetic diversity of a mixed sample from next-generation sequencing data', 'Zagordi, Osvaldo|Bhattacharya, Arnab|Eriksson, Nicholas|Beerenwinkel, Niko', 'Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch', 'Switzerland|Switzerland|Switzerland|Switzerland', 157, 'Genetic Variation|HIV|HIV Infections|High-Throughput Nucleotide Sequencing|Humans|Neoplasms|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-119', '21521499', 'With next-generation sequencing technologies, experiments that were considered prohibitive only a few years ago are now possible. However, while these technologies have the ability to produce enormous volumes of data, the sequence reads are prone to error. This poses fundamental hurdles when genetic diversity is investigated.'),
(94268, 2011, 'bmc', 'Cancer computational biology', 'Yakhini, Zohar|Jurisica, Igor', 'Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch|Department of Biosystems Science and Engineering, ETH Zurich, Mattenstrasse 26, 4058 Basel, Switzerland. osvaldo.zagordi@bsse.ethz.ch', 'Switzerland|Switzerland', 7, 'Computational Biology|Humans|Neoplasms|Proteins|Systems Biology', 'Congress', '10.1186/1471-2105-12-120', '21521513', '-'),
(94269, 2011, 'bmc', 'Stochastic sequence-level model of coupled transcription and translation in prokaryotes', 'Mäkelä, Jarno|Lloyd-Price, Jason|Yli-Harja, Olli|Ribeiro, Andre S', 'Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.|Computational Systems Biology Research Group, Department of Signal Processing, Tampere University of Technology, FI-33101 Tampere, Finland.', 'Finland|Finland|Finland|Finland', 0, 'Codon|DNA-Directed RNA Polymerases|Escherichia coli|Gene Expression Regulation, Bacterial|Models, Genetic|Protein Biosynthesis|Regulatory Sequences, Nucleic Acid|Ribosomes|Stochastic Processes|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-12-121', '21521517', 'In prokaryotes, transcription and translation are dynamically coupled, as the latter starts before the former is complete. Also, from one transcript, several translation events occur in parallel. To study how events in transcription elongation affect translation elongation and fluctuations in protein levels, we propose a delayed stochastic model of prokaryotic transcription and translation at the nucleotide and codon level that includes the promoter open complex formation and alternative pathways to elongation, namely pausing, arrests, editing, pyrophosphorolysis, RNA polymerase traffic, and premature termination. Stepwise translation can start after the ribosome binding site is formed and accounts for variable codon translation rates, ribosome traffic, back-translocation, drop-off, and trans-translation.'),
(94270, 2011, 'bmc', 'Mutagenesis Objective Search and Selection Tool (MOSST): an algorithm to predict structure-function related mutations in proteins', 'Olivera-Nappa, Alvaro|Andrews, Barbara A|Asenjo, Juan A', 'Centre for Biochemical Engineering and Biotechnology, Institute for Cell Dynamics and Biotechnology: a Centre for Systems Biology, University of Chile, Santiago, Chile. aolivera@ing.uchile.cl|Centre for Biochemical Engineering and Biotechnology, Institute for Cell Dynamics and Biotechnology: a Centre for Systems Biology, University of Chile, Santiago, Chile. aolivera@ing.uchile.cl|Centre for Biochemical Engineering and Biotechnology, Institute for Cell Dynamics and Biotechnology: a Centre for Systems Biology, University of Chile, Santiago, Chile. aolivera@ing.uchile.cl', 'Chile|Chile|Chile', 6, 'Algorithms|Amino Acid Sequence|Computational Biology|Glycoside Hydrolases|Mutagenesis, Site-Directed|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-122', '21524307', 'Functionally relevant artificial or natural mutations are difficult to assess or predict if no structure-function information is available for a protein. This is especially important to correctly identify functionally significant non-synonymous single nucleotide polymorphisms (nsSNPs) or to design a site-directed mutagenesis strategy for a target protein. A new and powerful methodology is proposed to guide these two decision strategies, based only on conservation rules of physicochemical properties of amino acids extracted from a multiple alignment of a protein family where the target protein belongs, with no need of explicit structure-function relationships.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94271, 2011, 'bmc', 'Discovering time-lagged rules from microarray data using gene profile classifiers', 'Gallo, Cristian A|Carballido, Jessica A|Ponzoni, Ignacio', 'Laboratorio de Investigación y Desarrollo en Computación Científica (LIDeCC), Departamento de Ciencias e Ingeniería de la Computación, Universidad Nacional del Sur, Av, Alem 1253, 8000, Bahía Blanca, Argentina.|Laboratorio de Investigación y Desarrollo en Computación Científica (LIDeCC), Departamento de Ciencias e Ingeniería de la Computación, Universidad Nacional del Sur, Av, Alem 1253, 8000, Bahía Blanca, Argentina.|Laboratorio de Investigación y Desarrollo en Computación Científica (LIDeCC), Departamento de Ciencias e Ingeniería de la Computación, Universidad Nacional del Sur, Av, Alem 1253, 8000, Bahía Blanca, Argentina.', 'Argentina|Argentina|Argentina', 0, 'Algorithms|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Gene Regulatory Networks|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-123', '21524308', 'Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes.'),
(94272, 2011, 'bmc', 'Proteinortho: detection of (co-)orthologs in large-scale analysis', 'Lechner, Marcus|Findeiss, Sven|Steiner, Lydia|Marz, Manja|Stadler, Peter F|Prohaska, Sonja J', 'RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de|RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de|RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de|RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de|RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de|RNA Bioinformatics Group, Department of Pharmaceutical Chemistry, Philipps-University Marburg, Germany. lechner@staff.uni-marburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 512, 'Base Sequence|Databases, Genetic|Genomics|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-12-124', '21526987', 'Orthology analysis is an important part of data analysis in many areas of bioinformatics such as comparative genomics and molecular phylogenetics. The ever-increasing flood of sequence data, and hence the rapidly increasing number of genomes that can be compared simultaneously, calls for efficient software tools as brute-force approaches with quadratic memory requirements become infeasible in practise. The rapid pace at which new data become available, furthermore, makes it desirable to compute genome-wide orthology relations for a given dataset rather than relying on relations listed in databases.'),
(94273, 2011, 'bmc', 'Identification of models of heterogeneous cell populations from population snapshot data', 'Hasenauer, Jan|Waldherr, Steffen|Doszczak, Malgorzata|Radde, Nicole|Scheurich, Peter|Allgöwer, Frank', 'Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de|Institute for Systems Theory and Automatic Control, University of Stuttgart, Germany. Jan.Hasenauer@ist.uni-stuttgart.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Bayes Theorem|Cytological Techniques|Models, Biological|Regression Analysis|Signal Transduction|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1186/1471-2105-12-125', '21527025', 'Most of the modeling performed in the area of systems biology aims at achieving a quantitative description of the intracellular pathways within a typical cell. However, in many biologically important situations even clonal cell populations can show a heterogeneous response. These situations require study of cell-to-cell variability and the development of models for heterogeneous cell populations.'),
(94274, 2011, 'bmc', 'STSE: Spatio-Temporal Simulation Environment Dedicated to Biology', 'Stoma, Szymon|Fröhlich, Martina|Gerber, Susanne|Klipp, Edda', 'Humboldt-Universität zu Berlin, Department of Theoretical Biophysics, Berlin, Germany. szymon.stoma@gmail.com|Humboldt-Universität zu Berlin, Department of Theoretical Biophysics, Berlin, Germany. szymon.stoma@gmail.com|Humboldt-Universität zu Berlin, Department of Theoretical Biophysics, Berlin, Germany. szymon.stoma@gmail.com|Humboldt-Universität zu Berlin, Department of Theoretical Biophysics, Berlin, Germany. szymon.stoma@gmail.com', 'Germany|Germany|Germany|Germany', 5, 'Fluorescent Dyes|Image Processing, Computer-Assisted|Microscopy|Mitogen-Activated Protein Kinases|Models, Biological|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-126', '21527030', 'Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers.'),
(94275, 2011, 'bmc', 'Sequential interim analyses of survival data in DNA microarray experiments', 'Leha, Andreas|Beissbarth, Tim|Jung, Klaus', 'Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany.|Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany.|Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany.', 'Germany|Germany|Germany', 0, 'Breast Neoplasms|Computer Simulation|Humans|Oligonucleotide Array Sequence Analysis|Research Design|Sample Size|Survival Analysis|Time Factors', 'Journal Article', '10.1186/1471-2105-12-127', '21527044', 'Discovery of biomarkers that are correlated with therapy response and thus with survival is an important goal of medical research on severe diseases, e.g. cancer. Frequently, microarray studies are performed to identify genes of which the expression levels in pretherapeutic tissue samples are correlated to survival times of patients. Typically, such a study can take several years until the full planned sample size is available.Therefore, interim analyses are desirable, offering the possibility of stopping the study earlier, or of performing additional laboratory experiments to validate the role of the detected genes. While many methods correcting the multiple testing bias introduced by interim analyses have been proposed for studies of one single feature, there are still open questions about interim analyses of multiple features, particularly of high-dimensional microarray data, where the number of features clearly exceeds the number of samples. Therefore, we examine false discovery rates and power rates in microarray experiments performed during interim analyses of survival studies. In addition, the early stopping based on interim results of such studies is evaluated. As stop criterion we employ the achieved average power rate, i.e. the proportion of detected true positives, for which a new estimator is derived and compared to existing estimators.'),
(94276, 2011, 'bmc', 'Phenotype recognition with combined features and random subspace classifier ensemble', 'Zhang, Bailing|Pham, Tuan D', 'Department of Computer Science and Software Engineering, Xian Jiaotong-Liverpool University, Suzhou, 215123, PR China. bailing.zhang@xjtlu.edu.cn|Department of Computer Science and Software Engineering, Xian Jiaotong-Liverpool University, Suzhou, 215123, PR China. bailing.zhang@xjtlu.edu.cn', 'China|China', 30, 'Algorithms|Animals|Artificial Intelligence|CHO Cells|Cricetinae|Cricetulus|Drosophila melanogaster|HeLa Cells|Humans|Image Processing, Computer-Assisted|Microscopy, Fluorescence|Neural Networks (Computer)|Pattern Recognition, Automated|Wavelet Analysis', 'Journal Article', '10.1186/1471-2105-12-128', '21529372', 'Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.'),
(94277, 2011, 'bmc', 'SNPPicker: high quality tag SNP selection across multiple populations', 'Sicotte, Hugues|Rider, David N|Poland, Gregory A|Dhiman, Neelam|Kocher, Jean-Pierre A', 'Department of Biomedical Statistics and Informatics, Mayo Clinic, 200 1st street SW, Rochester, MN 55905, USA.|Department of Biomedical Statistics and Informatics, Mayo Clinic, 200 1st street SW, Rochester, MN 55905, USA.|Department of Biomedical Statistics and Informatics, Mayo Clinic, 200 1st street SW, Rochester, MN 55905, USA.|Department of Biomedical Statistics and Informatics, Mayo Clinic, 200 1st street SW, Rochester, MN 55905, USA.|Department of Biomedical Statistics and Informatics, Mayo Clinic, 200 1st street SW, Rochester, MN 55905, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Genetics, Population|Genotype|Humans|Linkage Disequilibrium|Models, Statistical|Polymorphism, Single Nucleotide|Viruses', 'Journal Article', '10.1186/1471-2105-12-129', '21535878', 'Linkage Disequilibrium (LD) bin-tagging algorithms identify a reduced set of tag SNPs that can capture the genetic variation in a population without genotyping every single SNP. However, existing tag SNP selection algorithms for designing custom genotyping panels do not take into account all platform dependent factors affecting the likelihood of a tag SNP to be successfully genotyped and many of the constraints that can be imposed by the user.'),
(94278, 2011, 'bmc', 'An automated homology-based approach for identifying transposable elements', 'Kennedy, Ryan C|Unger, Maria F|Christley, Scott|Collins, Frank H|Madey, Gregory R', 'Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN, USA. Ryan.C.Kennedy@alumni.nd.edu', 'United States|United States|United States|United States|United States', 16, 'Animals|Base Sequence|Conserved Sequence|DNA Transposable Elements|Eukaryota|Gene Library|Genome|Humans|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-12-130', '21535899', 'Transposable elements (TEs) are mobile sequences found in nearly all eukaryotic genomes. They have the ability to move and replicate within a genome, often influencing genome evolution and gene expression. The identification of TEs is an important part of every genome project. The number of sequenced genomes is rapidly rising, and the need to identify TEs within them is also growing. The ability to do this automatically and effectively in a manner similar to the methods used for genes is of increasing importance. There exist many difficulties in identifying TEs, including their tendency to degrade over time and that many do not adhere to a conserved structure. In this work, we describe a homology-based approach for the automatic identification of high-quality consensus TEs, aimed for use in the analysis of newly sequenced genomes.'),
(94279, 2011, 'bmc', 'GC/MS based metabolomics: development of a data mining system for metabolite identification by using soft independent modeling of class analogy (SIMCA)', 'Tsugawa, Hiroshi|Tsujimoto, Yuki|Arita, Masanori|Bamba, Takeshi|Fukusaki, Eiichiro', 'Department of Bioengineering, Graduate School of Engineering, Osaka University, Suita, Japan.|Department of Bioengineering, Graduate School of Engineering, Osaka University, Suita, Japan.|Department of Bioengineering, Graduate School of Engineering, Osaka University, Suita, Japan.|Department of Bioengineering, Graduate School of Engineering, Osaka University, Suita, Japan.|Department of Bioengineering, Graduate School of Engineering, Osaka University, Suita, Japan.', 'Japan|Japan|Japan|Japan|Japan', 129, 'Data Mining|Databases, Genetic|Food Technology|Gas Chromatography-Mass Spectrometry|Information Systems|Metabolomics|Models, Biological|Tea', 'Journal Article', '10.1186/1471-2105-12-131', '21542920', 'The goal of metabolomics analyses is a comprehensive and systematic understanding of all metabolites in biological samples. Many useful platforms have been developed to achieve this goal. Gas chromatography coupled to mass spectrometry (GC/MS) is a well-established analytical method in metabolomics study, and 200 to 500 peaks are routinely observed with one biological sample. However, only ~100 metabolites can be identified, and the remaining peaks are left as unknowns.'),
(94280, 2011, 'bmc', 'Properties of metabolic graphs: biological organization or representation artifacts?', 'Zhou, Wanding|Nakhleh, Luay', 'Department of Bioengineering, Rice University, Houston, Texas, USA. wz4@rice.edu|Department of Bioengineering, Rice University, Houston, Texas, USA. wz4@rice.edu', 'United States|United States', 19, 'Artifacts|Cluster Analysis|Escherichia coli|Metabolic Networks and Pathways|Models, Biological|Proteome|Systems Biology', 'Journal Article', '10.1186/1471-2105-12-132', '21542923', 'Standard graphs, where each edge links two nodes, have been extensively used to represent the connectivity of metabolic networks. It is based on this representation that properties of metabolic networks, such as hierarchical and small-world structures, have been elucidated and null models have been proposed to derive biological organization hypotheses. However, these graphs provide a simplistic model of a metabolic networks connectivity map, since metabolic reactions often involve more than two reactants. In other words, this map is better represented as a hypergraph. Consequently, a question that naturally arises in this context is whether these properties truly reflect biological organization or are merely an artifact of the representation.'),
(94281, 2011, 'bmc', 'The PathOlogist: an automated tool for pathway-centric analysis', 'Greenblum, Sharon I|Efroni, Sol|Schaefer, Carl F|Buetow, Ken H', 'Department of Genome Sciences, University of Washington, Seattle WA, USA. sharongreenblum@gmail.com|Department of Genome Sciences, University of Washington, Seattle WA, USA. sharongreenblum@gmail.com|Department of Genome Sciences, University of Washington, Seattle WA, USA. sharongreenblum@gmail.com|Department of Genome Sciences, University of Washington, Seattle WA, USA. sharongreenblum@gmail.com', 'United States|United States|United States|United States', 0, 'Algorithms|Cell Line, Tumor|Cluster Analysis|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Glioblastoma|Humans|Metabolic Networks and Pathways|Neoplasms', 'Journal Article', '10.1186/1471-2105-12-133', '21542931', 'The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions.'),
(94282, 2011, 'bmc', 'SNiPlay: a web-based tool for detection, management and analysis of SNPs Application to grapevine diversity projects', 'Dereeper, Alexis|Nicolas, Stéphane|Le Cunff, Loïc|Bacilieri, Roberto|Doligez, Agnès|Peros, Jean-Pierre|Ruiz, Manuel|This, Patrice', 'Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr|Diversity, Genetics and Genomics of grapevine, UMR DIAPC, INRA, Montpellier, France. alexis.dereeper@ird.fr', 'France|France|France|France|France|France|France|France', 46, 'Base Sequence|Chromosome Mapping|Computational Biology|INDEL Mutation|Internet|Phylogeny|Polymorphism, Single Nucleotide|Sequence Alignment|Software|Vitis', 'Journal Article', '10.1186/1471-2105-12-134', '21545712', 'High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.'),
(94283, 2011, 'bmc', 'Hydrophobic pulses predict transmembrane helix irregularities and channel transmembrane units', 'Paulet, Damien|Claustres, Mireille|Béroud, Christophe', 'Université Montpellier, France. damien.paulet@inserm.fr|Université Montpellier, France. damien.paulet@inserm.fr|Université Montpellier, France. damien.paulet@inserm.fr', 'France|France|France', 0, 'Amino Acid Sequence|Animals|Cell Membrane|Computational Biology|Escherichia coli|Hydrophobic and Hydrophilic Interactions|Membrane Proteins|Membrane Transport Proteins|Models, Molecular|Potassium Channels, Voltage-Gated|Protein Structure, Secondary', 'Journal Article', '10.1186/1471-2105-12-135', '21545751', 'Few high-resolution structures of integral membranes proteins are available, as crystallization of such proteins needs yet to overcome too many technical limitations. Nevertheless, prediction of their transmembrane (TM) structure by bioinformatics tools provides interesting insights on the topology of these proteins.'),
(94284, 2011, 'bmc', 'ArrayInitiative - a tool that simplifies creating custom Affymetrix CDFs', 'Overall, Christopher C|Carr, D Andrew|Tabari, Ehsan S|Thompson, Kevin J|Weller, Jennifer W', 'Department of Bioinformatics and Genomics, University of North Carolina - Charlotte, Charlotte, NC 28223-0001, USA.|Department of Bioinformatics and Genomics, University of North Carolina - Charlotte, Charlotte, NC 28223-0001, USA.|Department of Bioinformatics and Genomics, University of North Carolina - Charlotte, Charlotte, NC 28223-0001, USA.|Department of Bioinformatics and Genomics, University of North Carolina - Charlotte, Charlotte, NC 28223-0001, USA.|Department of Bioinformatics and Genomics, University of North Carolina - Charlotte, Charlotte, NC 28223-0001, USA.', 'United States|United States|United States|United States|United States', 0, 'Adenocarcinoma|Algorithms|Humans|Lung Neoplasms|Microarray Analysis|Oligonucleotide Probes|Software', 'Journal Article', '10.1186/1471-2105-12-136', '21548938', 'Probes on a microarray represent a frozen view of a genome and are quickly outdated when new sequencing studies extend our knowledge, resulting in significant measurement error when analyzing any microarray experiment. There are several bioinformatics approaches to improve probe assignments, but without in-house programming expertise, standardizing these custom array specifications as a usable file (e.g. as Affymetrix CDFs) is difficult, owing mostly to the complexity of the specification file format. However, without correctly standardized files there is a significant barrier for testing competing analysis approaches since this file is one of the required inputs for many commonly used algorithms. The need to test combinations of probe assignments and analysis algorithms led us to develop ArrayInitiative, a tool for creating and managing custom array specifications.'),
(94285, 2011, 'bmc', 'Assessing affymetrix GeneChip microarray quality', 'McCall, Matthew N|Murakami, Peter N|Lukk, Margus|Huber, Wolfgang|Irizarry, Rafael A', 'Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Baltimore, MD, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Baltimore, MD, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Baltimore, MD, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Baltimore, MD, USA.|Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, 615 N, Wolfe St,, Baltimore, MD, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Quality Control|RNA|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-12-137', '21548974', 'Microarray technology has become a widely used tool in the biological sciences. Over the past decade, the number of users has grown exponentially, and with the number of applications and secondary data analyses rapidly increasing, we expect this rate to continue. Various initiatives such as the External RNA Control Consortium (ERCC) and the MicroArray Quality Control (MAQC) project have explored ways to provide standards for the technology. For microarrays to become generally accepted as a reliable technology, statistical methods for assessing quality will be an indispensable component, however, there remains a lack of consensus in both defining and measuring microarray quality.'),
(94286, 2011, 'bmc', 'Elastic SCAD as a novel penalization method for SVM classification tasks in high-dimensional data', 'Becker, Natalia|Toedt, Grischa|Lichter, Peter|Benner, Axel', 'German Cancer Research Center, Division Molecular Genetics, INF 280, 69120 Heidelberg, Germany. natalia.becker@dkfz.de|German Cancer Research Center, Division Molecular Genetics, INF 280, 69120 Heidelberg, Germany. natalia.becker@dkfz.de|German Cancer Research Center, Division Molecular Genetics, INF 280, 69120 Heidelberg, Germany. natalia.becker@dkfz.de|German Cancer Research Center, Division Molecular Genetics, INF 280, 69120 Heidelberg, Germany. natalia.becker@dkfz.de', 'Germany|Germany|Germany|Germany', 37, 'Algorithms|Artificial Intelligence|Breast Neoplasms|Classification|Genetic Vectors|Humans|Lymph Nodes|Microarray Analysis|Neoplasm Metastasis', 'Journal Article', '10.1186/1471-2105-12-138', '21554689', 'Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and prediction methods with a wide range of scientific applications, the SVM does not include automatic feature selection and therefore a number of feature selection procedures have been developed. Regularisation approaches extend SVM to a feature selection method in a flexible way using penalty functions like LASSO, SCAD and Elastic Net.We propose a novel penalty function for SVM classification tasks, Elastic SCAD, a combination of SCAD and ridge penalties which overcomes the limitations of each penalty alone.Since SVM models are extremely sensitive to the choice of tuning parameters, we adopted an interval search algorithm, which in comparison to a fixed grid search finds rapidly and more precisely a global optimal solution.'),
(94287, 2011, 'bmc', 'PeakRanger: a cloud-enabled peak caller for ChIP-seq data', 'Feng, Xin|Grossman, Robert|Stein, Lincoln', 'Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA. drestion@gmail.com|Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA. drestion@gmail.com|Department of Biomedical Engineering, Stony Brook University, Stony Brook, NY 11794, USA. drestion@gmail.com', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromatin|Chromatin Assembly and Disassembly|Chromatin Immunoprecipitation|Histone Code|Protein Binding|Sensitivity and Specificity|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-139', '21554709', 'Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, most are tuned either to handle punctate sites, such as transcriptional factor binding sites, or broad regions, such as histone modification marks, few can do both. Other algorithms are limited in their configurability, performance on large data sets, and ability to distinguish closely-spaced peaks.'),
(94288, 2011, 'bmc', 'Biomarker discovery and redundancy reduction towards classification using a multi-factorial MALDI-TOF MS T2DM mouse model dataset', 'Bauer, Chris|Kleinjung, Frank|Smith, Celia J|Towers, Mark W|Tiss, Ali|Chadt, Alexandra|Dreja, Tanja|Beule, Dieter|Al-Hasani, Hadi|Reinert, Knut|Schuchhardt, Johannes|Cramer, Rainer', 'MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de|MicroDiscovery GmbH, Marienburger Str, 1, 10405 Berlin, Germany. chris.bauer@microdiscovery.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Albumins|Analysis of Variance|Animals|Biomarkers|Diabetes Mellitus, Type 2|Diet|Hemoglobins|Male|Mice|Mice, Inbred C57BL|Mice, Obese|Peptides|Proteomics|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1186/1471-2105-12-140', '21554713', 'Diabetes like many diseases and biological processes is not mono-causal. On the one hand multi-factorial studies with complex experimental design are required for its comprehensive analysis. On the other hand, the data from these studies often include a substantial amount of redundancy such as proteins that are typically represented by a multitude of peptides. Coping simultaneously with both complexities (experimental and technological) makes data analysis a challenge for Bioinformatics.'),
(94289, 2011, 'bmc', 'Inferring functional modules of protein families with probabilistic topic models', 'Konietzny, Sebastian Ga|Dietz, Laura|McHardy, Alice C', 'Max Planck Research Group for Computational Genomics and Epidemiology, Max Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany.|Max Planck Research Group for Computational Genomics and Epidemiology, Max Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany.|Max Planck Research Group for Computational Genomics and Epidemiology, Max Planck Institute for Informatics, University Campus E1 4, 66123 Saarbrücken, Germany.', 'Germany|Germany|Germany', 9, 'Bayes Theorem|Flagella|Genome|Models, Genetic|Models, Statistical|Prokaryotic Cells|Proteins', 'Journal Article', '10.1186/1471-2105-12-141', '21554720', 'Genome and metagenome studies have identified thousands of protein families whose functions are poorly understood and for which techniques for functional characterization provide only partial information. For such proteins, the genome context can give further information about their functional context.'),
(94290, 2011, 'bmc', 'FIND: a new software tool and development platform for enhanced multicolor flow analysis', 'Dabdoub, Shareef M|Ray, William C|Justice, Sheryl S', 'Biophysics Program, The Ohio State University, Columbus, Ohio, USA. dabdoub.2@osu.edu|Biophysics Program, The Ohio State University, Columbus, Ohio, USA. dabdoub.2@osu.edu|Biophysics Program, The Ohio State University, Columbus, Ohio, USA. dabdoub.2@osu.edu', 'United States|United States|United States', 7, 'Algorithms|Flow Cytometry|Hydrodynamics|Lasers|Programming Languages|Software', 'Journal Article', '10.1186/1471-2105-12-145', '21569257', 'Flow Cytometry is a process by which cells, and other microscopic particles, can be identified, counted, and sorted mechanically through the use of hydrodynamic pressure and laser-activated fluorescence labeling. As immunostained cells pass individually through the flow chamber of the instrument, laser pulses cause fluorescence emissions that are recorded digitally for later analysis as multidimensional vectors. Current, widely adopted analysis software limits users to manual separation of events based on viewing two or three simultaneous dimensions. While this may be adequate for experiments using four or fewer colors, advances have lead to laser flow cytometers capable of recording 20 different colors simultaneously. In addition, mass-spectrometry based machines capable of recording at least 100 separate channels are being developed. Analysis of such high-dimensional data by visual exploration alone can be error-prone and susceptible to unnecessary bias. Fortunately, the field of Data Mining provides many tools for automated group classification of multi-dimensional data, and many algorithms have been adapted or created for flow cytometry. However, the majority of this research has not been made available to users through analysis software packages and, as such, are not in wide use.'),
(94291, 2011, 'bmc', 'Extraction of consensus protein patterns in regions containing non-proline cis peptide bonds and their functional assessment', 'Exarchos, Konstantinos P|Exarchos, Themis P|Rigas, Georgios|Papaloukas, Costas|Fotiadis, Dimitrios I', 'Unit of Medical Technology and Intelligent Information Systems, Dept, of Materials Science and Engineering, University of Ioannina, GR 45110, Ioannina, Greece.|Unit of Medical Technology and Intelligent Information Systems, Dept, of Materials Science and Engineering, University of Ioannina, GR 45110, Ioannina, Greece.|Unit of Medical Technology and Intelligent Information Systems, Dept, of Materials Science and Engineering, University of Ioannina, GR 45110, Ioannina, Greece.|Unit of Medical Technology and Intelligent Information Systems, Dept, of Materials Science and Engineering, University of Ioannina, GR 45110, Ioannina, Greece.|Unit of Medical Technology and Intelligent Information Systems, Dept, of Materials Science and Engineering, University of Ioannina, GR 45110, Ioannina, Greece.', 'Greece|Greece|Greece|Greece|Greece', 0, 'Algorithms|Amides|Crystallography, X-Ray|Databases, Factual|Databases, Protein|Peptides|Proline|Protein Conformation|Protein Structure, Tertiary|Proteins|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-12-142', '21569261', 'In peptides and proteins, only a small percentile of peptide bonds adopts the cis configuration. Especially in the case of amide peptide bonds, the amount of cis conformations is quite limited thus hampering systematic studies, until recently. However, lately the emerging population of databases with more 3D structures of proteins has produced a considerable number of sequences containing non-proline cis formations (cis-nonPro).'),
(94292, 2011, 'bmc', 'Meta-alignment with crumble and prune: partitioning very large alignment problems for performance and parallelization', 'Roskin, Krishna M|Paten, Benedict|Haussler, David', 'Department of Computer Science, Univ. of California, Santa Cruz, USA. krish@soe.ucsc.edu|Department of Computer Science, Univ. of California, Santa Cruz, USA. krish@soe.ucsc.edu|Department of Computer Science, Univ. of California, Santa Cruz, USA. krish@soe.ucsc.edu', 'United States|United States|United States', 7, 'Algorithms|Animals|Base Sequence|Cluster Analysis|Genome|Humans|Sequence Alignment|Time Factors', 'Journal Article', '10.1186/1471-2105-12-144', '21569267', 'Continuing research into the global multiple sequence alignment problem has resulted in more sophisticated and principled alignment methods. Unfortunately these new algorithms often require large amounts of time and memory to run, making it nearly impossible to run these algorithms on large datasets. As a solution, we present two general methods, Crumble and Prune, for breaking a phylogenetic alignment problem into smaller, more tractable sub-problems. We call Crumble and Prune meta-alignment methods because they use existing alignment algorithms and can be used with many current alignment programs. Crumble breaks long alignment problems into shorter sub-problems. Prune divides the phylogenetic tree into a collection of smaller trees to reduce the number of sequences in each alignment problem. These methods are orthogonal: they can be applied together to provide better scaling in terms of sequence length and in sequence depth. Both methods partition the problem such that many of the sub-problems can be solved independently. The results are then combined to form a solution to the full alignment problem.'),
(94293, 2011, 'bmc', 'DAS writeback: a collaborative annotation system', 'Salazar, Gustavo A|Jimenez, Rafael C|Garcia, Alexander|Hermjakob, Henning|Mulder, Nicola|Blake, Edwin', 'Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za|Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za|Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za|Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za|Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za|Computer Sciences Department, University of Cape Town, South Africa. gsalazar@cs.uct.ac.za', 'South Africa|South Africa|South Africa|South Africa|South Africa|South Africa', 2, 'Computer Communication Networks|Databases, Genetic|Information Storage and Retrieval|Molecular Sequence Annotation|Software', 'Journal Article', '10.1186/1471-2105-12-143', '21569281', 'Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.'),
(94294, 2011, 'bmc', 'Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays', 'Hur, Youngmi|Lee, Hyunju', 'Dept. of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA.|Dept. of Applied Mathematics and Statistics, Johns Hopkins University, Baltimore, MD, USA.', 'United States|United States', 0, 'Chromosome Aberrations|DNA Copy Number Variations|Glioblastoma|Humans|Lung Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Wavelet Analysis', 'Journal Article', '10.1186/1471-2105-12-146', '21569311', 'Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs.'),
(94295, 2011, 'bmc', 'HTPheno: an image analysis pipeline for high-throughput plant phenotyping', 'Hartmann, Anja|Czauderna, Tobias|Hoffmann, Roberto|Stein, Nils|Schreiber, Falk', 'Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.|Leibniz Institute of Plant Genetics and Crop Plant Research, Corrensstrasse 3, 06466 Gatersleben, Germany.', 'Germany|Germany|Germany|Germany|Germany', 154, 'Algorithms|Hordeum|Image Processing, Computer-Assisted|Phenotype|Plants|Software', 'Journal Article', '10.1186/1471-2105-12-148', '21569390', 'In the last few years high-throughput analysis methods have become state-of-the-art in the life sciences. One of the latest developments is automated greenhouse systems for high-throughput plant phenotyping. Such systems allow the non-destructive screening of plants over a period of time by means of image acquisition techniques. During such screening different images of each plant are recorded and must be analysed by applying sophisticated image analysis algorithms.'),
(94296, 2011, 'bmc', 'Fast network centrality analysis using GPUs', 'Shi, Zhiao|Zhang, Bing', 'Advanced Computing Center for Research & Education, Vanderbilt University, Nashville, TN 37203, USA.|Advanced Computing Center for Research & Education, Vanderbilt University, Nashville, TN 37203, USA.', 'United States|United States', 43, 'Algorithms|Breast Neoplasms|Gene Regulatory Networks|Humans|Metabolic Networks and Pathways|Proteins|Signal Transduction|Software|Systems Biology', 'Journal Article', '10.1186/1471-2105-12-149', '21569426', 'With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU) provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs.'),
(94297, 2011, 'bmc', 'A user-friendly web portal for T-Coffee on supercomputers', 'Rius, Josep|Cores, Fernando|Solsona, Francesc|van Hemert, Jano I|Koetsier, Jos|Notredame, Cedric', 'Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat|Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat|Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat|Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat|Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat|Department of Computer Science and Industrial Engineering, University of Lleida, C/Jaume II 69, E-25001 Lleida, Spain. jrius@diei.udl.cat', 'Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Cluster Analysis|Genomics|Internet|Proteins|Sequence Alignment|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-12-150', '21569428', 'Parallel T-Coffee (PTC) was the first parallel implementation of the T-Coffee multiple sequence alignment tool. It is based on MPI and RMA mechanisms. Its purpose is to reduce the execution time of the large-scale sequence alignments. It can be run on distributed memory clusters allowing users to align data sets consisting of hundreds of proteins within a reasonable time. However, most of the potential users of this tool are not familiar with the use of grids or supercomputers.'),
(94298, 2011, 'bmc', 'PoPMuSiC 21: a web server for the estimation of protein stability changes upon mutation and sequence optimality', 'Dehouck, Yves|Kwasigroch, Jean Marc|Gilis, Dimitri|Rooman, Marianne', 'Bioinformatique génomique et structurale, Université Libre de Bruxelles, Av, Fr, Roosevelt 50, CP165/61, 1050 Brussels, Belgium. ydehouck@ulb.ac.be|Bioinformatique génomique et structurale, Université Libre de Bruxelles, Av, Fr, Roosevelt 50, CP165/61, 1050 Brussels, Belgium. ydehouck@ulb.ac.be|Bioinformatique génomique et structurale, Université Libre de Bruxelles, Av, Fr, Roosevelt 50, CP165/61, 1050 Brussels, Belgium. ydehouck@ulb.ac.be|Bioinformatique génomique et structurale, Université Libre de Bruxelles, Av, Fr, Roosevelt 50, CP165/61, 1050 Brussels, Belgium. ydehouck@ulb.ac.be', 'Belgium|Belgium|Belgium|Belgium', 232, 'Escherichia coli|Internet|Models, Molecular|Mutation|Protein Stability|Protein Structure, Tertiary|Proteins|Software|Thermodynamics', 'Journal Article', '10.1186/1471-2105-12-151', '21569468', 'The rational design of modified proteins with controlled stability is of extreme importance in a whole range of applications, notably in the biotechnological and environmental areas, where proteins are used for their catalytic or other functional activities. Future breakthroughs in medical research may also be expected from an improved understanding of the effect of naturally occurring disease-causing mutations on the molecular level.'),
(94299, 2011, 'bmc', 'ZFN-site searches genomes for zinc finger nuclease target sites and off-target sites', 'Cradick, Thomas J|Ambrosini, Giovanna|Iseli, Christian|Bucher, Philipp|McCaffrey, Anton P', 'University of Iowa School of Medicine, Department of Internal Medicine, Iowa City, Iowa 52245, USA. tj@alum.mit.edu|University of Iowa School of Medicine, Department of Internal Medicine, Iowa City, Iowa 52245, USA. tj@alum.mit.edu|University of Iowa School of Medicine, Department of Internal Medicine, Iowa City, Iowa 52245, USA. tj@alum.mit.edu|University of Iowa School of Medicine, Department of Internal Medicine, Iowa City, Iowa 52245, USA. tj@alum.mit.edu|University of Iowa School of Medicine, Department of Internal Medicine, Iowa City, Iowa 52245, USA. tj@alum.mit.edu', 'United States|United States|United States|United States|United States', 32, 'Base Sequence|Endonucleases|Genome|Humans|Protein Binding|Receptors, CCR5|User-Computer Interface|Zinc Fingers', 'Journal Article', '10.1186/1471-2105-12-152', '21569489', 'Zinc Finger Nucleases (ZFNs) are man-made restriction enzymes useful for manipulating genomes by cleaving target DNA sequences. ZFNs allow therapeutic gene correction or creation of genetically modified model organisms. ZFN specificity is not absolute, therefore, it is essential to select ZFN target sites without similar genomic off-target sites. It is important to assay for off-target cleavage events at sites similar to the target sequence.'),
(94300, 2011, 'bmc', 'To aggregate or not to aggregate high-dimensional classifiers', 'Xu, Cheng-Jian|Hoefsloot, Huub C J|Smilde, Age K', 'Biosystems Data Analysis group, University of Amsterdam, Amsterdam, The Netherlands.|Biosystems Data Analysis group, University of Amsterdam, Amsterdam, The Netherlands.|Biosystems Data Analysis group, University of Amsterdam, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Data Mining|Gaucher Disease|Genomics|Humans|Leukemia, Myeloid, Acute|Metabolomics|Models, Biological|Precursor Cell Lymphoblastic Leukemia-Lymphoma|Principal Component Analysis|Proteomics|Vitis', 'Journal Article', '10.1186/1471-2105-12-153', '21569498', 'High-throughput functional genomics technologies generate large amount of data with hundreds or thousands of measurements per sample. The number of sample is usually much smaller in the order of ten or hundred. This poses statistical challenges and calls for appropriate solutions for the analysis of this kind of data.'),
(94301, 2011, 'bmc', 'Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure', 'Aydin, Zafer|Singh, Ajit|Bilmes, Jeff|Noble, William S', 'Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.|Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States|United States', 25, 'Algorithms|Amino Acids|Bayes Theorem|Databases, Protein|Models, Statistical|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1186/1471-2105-12-154', '21569525', 'Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic Bayesian networks (DBNs) and support vector machines (SVMs) have been shown to provide state-of-the-art performance in secondary structure prediction. As the size of the protein database grows, it becomes feasible to use a richer model in an effort to capture subtle correlations among the amino acids and the predicted labels. In this context, it is beneficial to derive sparse models that discourage over-fitting and provide biological insight.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94302, 2011, 'bmc', 'Histone modification profiles are predictive for tissue/cell-type specific expression of both protein-coding and microRNA genes', 'Zhang, Zhihua|Zhang, Michael Q', 'Department of Molecular Cell Biology, Center for Systems Biology, University of Texas at Dallas, Richardson, TX 75080, USA.|Department of Molecular Cell Biology, Center for Systems Biology, University of Texas at Dallas, Richardson, TX 75080, USA.', 'United States|United States', 25, 'Artificial Intelligence|Base Sequence|CD4-Positive T-Lymphocytes|Gene Expression Profiling|Gene Expression Regulation|Histone Code|Histones|Humans|MicroRNAs|Muscle, Skeletal|Organ Specificity|Promoter Regions, Genetic|Regulatory Sequences, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-12-155', '21569556', 'Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR) is largely unknown. In this paper, we present a method to elucidate the relationship between histone modification/variation (HMV) and TCSR.'),
(94303, 2011, 'bmc', 'A hidden two-locus disease association pattern in genome-wide association studies', 'Yang, Can|Wan, Xiang|Yang, Qiang|Xue, Hong|Tang, Nelson L S|Yu, Weichuan', 'Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk|Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk|Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk|Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk|Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk|Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology, Hong Kong. eeyang@ust.hk', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 0, 'Computational Biology|Disease|Genetic Predisposition to Disease|Genome-Wide Association Study|Humans|Models, Statistical|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-12-156', '21569557', 'Recent association analyses in genome-wide association studies (GWAS) mainly focus on single-locus association tests (marginal tests) and two-locus interaction detections. These analysis methods have provided strong evidence of associations between genetics variances and complex diseases. However, there exists a type of association pattern, which often occurs within local regions in the genome and is unlikely to be detected by either marginal tests or interaction tests. This association pattern involves a group of correlated single-nucleotide polymorphisms (SNPs). The correlation among SNPs can lead to weak marginal effects and the interaction does not play a role in this association pattern. This phenomenon is due to the existence of unfaithfulness: the marginal effects of correlated SNPs do not express their significant joint effects faithfully due to the correlation cancelation.'),
(94304, 2011, 'bmc', 'Discrimination of approved drugs from experimental drugs by learning methods', 'Tang, Kailin|Zhu, Ruixin|Li, Yixue|Cao, Zhiwei', 'Shanghai Center for Bioinformation and Technology, 100 Qinzhou Road, Shanghai 200235, China.|Shanghai Center for Bioinformation and Technology, 100 Qinzhou Road, Shanghai 200235, China.|Shanghai Center for Bioinformation and Technology, 100 Qinzhou Road, Shanghai 200235, China.|Shanghai Center for Bioinformation and Technology, 100 Qinzhou Road, Shanghai 200235, China.', 'China|China|China|China', 3, 'Artificial Intelligence|Classification|Databases, Factual|Drug Approval|Drug Discovery|Herbal Medicine|Pharmaceutical Preparations', 'Journal Article', '10.1186/1471-2105-12-157', '21569562', 'To assess whether a compound is druglike or not as early as possible is always critical in drug discovery process. There have been many efforts made to create sets of rules or filters which, it is hoped, will help chemists to identify drug-like molecules from non-drug molecules. However, among the chemical space of the druglike molecules, the minority will be approved drugs. Classifying approved drugs from experimental drugs may be more helpful to obtain future approved drugs. Therefore, discrimination of approved drugs from experimental ones has been done in this paper by analyzing the compounds in terms of existing drugs features and machine learning methods.'),
(94305, 2011, 'bmc', 'Conformational and functional analysis of molecular dynamics trajectories by self-organising maps', 'Fraccalvieri, Domenico|Pandini, Alessandro|Stella, Fabio|Bonati, Laura', 'Dipartimento di Scienze dellAmbiente e del Territorio, Universitxc3xa0 degli Studi di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Universitxc3xa0 degli Studi di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Universitxc3xa0 degli Studi di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.|Dipartimento di Scienze dellAmbiente e del Territorio, Universitxc3xa0 degli Studi di Milano-Bicocca, Piazza della Scienza 1, 20126 Milano, Italy.', 'Italy|Italy|Italy|Italy', 25, 'Algorithms|Animals|Chickens|Molecular Dynamics Simulation|Point Mutation|Protein Structure, Tertiary|Proteins|Spectrin', 'Journal Article', '10.1186/1471-2105-12-158', '21569575', 'Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering.'),
(94306, 2011, 'bmc', 'RAPSearch: a fast protein similarity search tool for short reads', 'Ye, Yuzhen|Choi, Jeong-Hyeon|Tang, Haixu', 'School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. yye@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. yye@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, IN 47408, USA. yye@indiana.edu', 'India|India|India', 0, 'Algorithms|Amino Acid Sequence|Metagenomics|Molecular Sequence Data|Proteins|Search Engine|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-12-159', '21575167', 'Next Generation Sequencing (NGS) is producing enormous corpuses of short DNA reads, affecting emerging fields like metagenomics. Protein similarity search--a key step to achieve annotation of protein-coding genes in these short reads, and identification of their biological functions--faces daunting challenges because of the very sizes of the short read datasets.'),
(94307, 2011, 'bmc', 'FunFOLD: an improved automated method for the prediction of ligand binding residues using 3D models of proteins', 'Roche, Daniel B|Tetchner, Stuart J|McGuffin, Liam J', 'School of Biological Sciences, University of Reading, Whiteknights, Reading, UK.|School of Biological Sciences, University of Reading, Whiteknights, Reading, UK.|School of Biological Sciences, University of Reading, Whiteknights, Reading, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Binding Sites|Cluster Analysis|Internet|Models, Molecular|Protein Binding|Protein Conformation|Proteins|Sequence Homology, Amino Acid|Software|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-12-160', '21575183', 'The accurate prediction of ligand binding residues from amino acid sequences is important for the automated functional annotation of novel proteins. In the previous two CASP experiments, the most successful methods in the function prediction category were those which used structural superpositions of 3D models and related templates with bound ligands in order to identify putative contacting residues. However, whilst most of this prediction process can be automated, visual inspection and manual adjustments of parameters, such as the distance thresholds used for each target, have often been required to prevent over prediction. Here we describe a novel method FunFOLD, which uses an automatic approach for cluster identification and residue selection. The software provided can easily be integrated into existing fold recognition servers, requiring only a 3D model and list of templates as inputs. A simple web interface is also provided allowing access to non-expert users. The method has been benchmarked against the top servers and manual prediction groups tested at both CASP8 and CASP9.'),
(94308, 2011, 'bmc', 'PRIN: a predicted rice interactome network', 'Gu, Haibin|Zhu, Pengcheng|Jiao, Yinming|Meng, Yijun|Chen, Ming', 'Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.|Department of Bioinformatics, State Key Laboratory of Plant Physiology and Biochemistry, College of Life Sciences, Zhejiang University, Hangzhou 310058, China.', 'China|China|China|China|China', 0, 'Animals|Databases, Protein|Genome, Plant|Humans|Molecular Sequence Annotation|Oryza|Protein Interaction Mapping|Proteomics|Signal Transduction', 'Journal Article', '10.1186/1471-2105-12-161', '21575196', 'Protein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa.'),
(94309, 2011, 'bmc', 'NSMAP: a method for spliced isoforms identification and quantification from RNA-Seq', 'Xia, Zheng|Wen, Jianguo|Chang, Chung-Che|Zhou, Xiaobo', 'Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA.|Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA.|Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA.|Department of Radiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA.', 'United States|United States|United States|United States', 0, 'Alternative Splicing|Base Sequence|Gene Expression Profiling|Humans|Models, Genetic|Oligonucleotide Probes|Protein Isoforms|RNA Splicing|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-162', '21575225', 'The development of techniques for sequencing the messenger RNA (RNA-Seq) enables it to study the biological mechanisms such as alternative splicing and gene expression regulation more deeply and accurately. Most existing methods employ RNA-Seq to quantify the expression levels of already annotated isoforms from the reference genome. However, the current reference genome is very incomplete due to the complexity of the transcriptome which hiders the comprehensive investigation of transcriptome using RNA-Seq. Novel study on isoform inference and estimation purely from RNA-Seq without annotation information is desirable.'),
(94310, 2011, 'bmc', 'CASCADE_SCAN: mining signal transduction network from high-throughput data based on steepest descent method', 'Wang, Kai|Hu, Fuyan|Xu, Kejia|Cheng, Hua|Jiang, Meng|Feng, Ruili|Li, Jing|Wen, Tieqiao', 'Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.|Laboratory of Molecular Neurobiology, School of Life Sciences and Institute of Systems Biology, Shanghai University, Shanghai 200444, China.', 'China|China|China|China|China|China|China|China', 11, 'Computational Biology|Feedback|Pheromones|Proteins|Proteomics|Signal Transduction|Yeasts', 'Journal Article', '10.1186/1471-2105-12-164', '21575263', 'Signal transduction is an essential biological process involved in cell response to environment changes, by which extracellular signaling initiates intracellular signaling. Many computational methods have been generated in mining signal transduction networks with the increasing of high-throughput genomic and proteomic data. However, more effective means are still needed to understand the complex mechanisms of signaling pathways.'),
(94311, 2011, 'bmc', 'Identification of microRNA precursors based on random forest with network-level representation method of stem-loop structure', 'Xiao, Jiamin|Tang, Xiaojing|Li, Yizhou|Fang, Zheng|Ma, Daichuan|He, Yangzhige|Li, Menglong', 'College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.|College of Chemistry and State Key Laboratory of Biotherapy, Sichuan University, Chengdu 610064, PR China.', 'China|China|China|China|China|China|China', 0, 'Algorithms|Animals|Artificial Intelligence|Humans|MicroRNAs|Models, Statistical|Nucleic Acid Conformation|RNA Precursors|RNA, Messenger', 'Journal Article', '10.1186/1471-2105-12-165', '21575268', 'MicroRNAs (miRNAs) play a key role in regulating various biological processes such as participating in the post-transcriptional pathway and affecting the stability and/or the translation of mRNA. Current methods have extracted feature information at different levels, among which the characteristic stem-loop structure makes the greatest contribution to the prediction of putative miRNA precursor (pre-miRNA). We find that none of these features alone is capable of identifying new pre-miRNA accurately.'),
(94312, 2011, 'bmc', 'A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data', 'González, Juan R|Rodríguez-Santiago, Benjamín|Cáceres, Alejandro|Pique-Regi, Roger|Rothman, Nathaniel|Chanock, Stephen J|Armengol, Lluís|Pérez-Jurado, Luis A', 'Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. jrgonzalez@creal.cat', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 0, 'Allelic Imbalance|Chromosome Aberrations|Genome, Human|Humans|Mosaicism|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sensitivity and Specificity|Urinary Bladder Neoplasms', 'Journal Article', '10.1186/1471-2105-12-166', '21586113', 'Mosaicism for copy number and copy neutral chromosomal rearrangements has been recently identified as a relatively common source of genetic variation in the normal population. However its prevalence is poorly defined since it has been only studied systematically in one large-scale study and by using non optimal ad-hoc SNP array data analysis tools, uncovering rather large alterations (> 1 Mb) and affecting a high proportion of cells. Here we propose a novel methodology, Mosaic Alteration Detection-MAD, by providing a software tool that is effective for capturing previously described alterations as wells as new variants that are smaller in size and/or affecting a low percentage of cells.'),
(94313, 2011, 'bmc', 'A formal MIM specification and tools for the common exchange of MIM diagrams: an XML-Based format, an API, and a validation method', 'Luna, Augustin|Karac, Evrim I|Sunshine, Margot|Chang, Lucas|Nussinov, Ruth|Aladjem, Mirit I|Kohn, Kurt W', 'Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.|Laboratory of Molecular Pharmacology, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA.', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Information Storage and Retrieval|Metabolic Networks and Pathways|Models, Biological|Programming Languages|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-12-167', '21586134', 'The Molecular Interaction Map (MIM) notation offers a standard set of symbols and rules on their usage for the depiction of cellular signaling network diagrams. Such diagrams are essential for disseminating biological information in a concise manner. A lack of software tools for the notation restricts wider usage of the notation. Development of software is facilitated by a more detailed specification regarding software requirements than has previously existed for the MIM notation.'),
(94314, 2011, 'bmc', 'More accurate recombination prediction in HIV-1 using a robust decoding algorithm for HMMs', 'Truszkowski, Jakub|Brown, Daniel G', 'David R Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada. jmtruszk@uwaterloo.ca|David R Cheriton School of Computer Science, University of Waterloo, Waterloo, ON, Canada. jmtruszk@uwaterloo.ca', 'Canada|Canada', 0, 'Algorithms|Genome, Viral|HIV-1|Humans|Markov Chains|Recombination, Genetic', 'Journal Article', '10.1186/1471-2105-12-168', '21586147', 'Identifying recombinations in HIV is important for studying the epidemiology of the virus and aids in the design of potential vaccines and treatments. The previous widely-used tool for this task uses the Viterbi algorithm in a hidden Markov model to model recombinant sequences.'),
(94315, 2011, 'bmc', 'Predicting drug side-effect profiles: a chemical fragment-based approach', 'Pauwels, Edouard|Stoven, Véronique|Yamanishi, Yoshihiro', 'Mines ParisTech, Centre for Computational Biology, 35 Rue Saint-Honoré, F-77305 Fontainebleau Cedex, France.|Mines ParisTech, Centre for Computational Biology, 35 Rue Saint-Honoré, F-77305 Fontainebleau Cedex, France.|Mines ParisTech, Centre for Computational Biology, 35 Rue Saint-Honoré, F-77305 Fontainebleau Cedex, France.', 'France|France|France', 131, 'Computational Biology|Databases, Factual|Drug Delivery Systems|Drug Design|Drug-Related Side Effects and Adverse Reactions|Humans|Pharmaceutical Preparations', 'Journal Article', '10.1186/1471-2105-12-169', '21586169', 'Drug side-effects, or adverse drug reactions, have become a major public health concern. It is one of the main causes of failure in the process of drug development, and of drug withdrawal once they have reached the market. Therefore, in silico prediction of potential side-effects early in the drug discovery process, before reaching the clinical stages, is of great interest to improve this long and expensive process and to provide new efficient and safe therapies for patients.'),
(94316, 2011, 'bmc', 'Objective identification of residue ranges for the superposition of protein structures', 'Kirchner, Donata K|Güntert, Peter', 'Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute for Advanced Studies, Goethe University Frankfurt am Main, Max-von-Laue-Str, 9, 60438 Frankfurt am Main, Germany.|Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance, and Frankfurt Institute for Advanced Studies, Goethe University Frankfurt am Main, Max-von-Laue-Str, 9, 60438 Frankfurt am Main, Germany.', 'Germany|Germany', 34, 'Algorithms|Animals|Databases, Protein|Humans|Models, Molecular|Nuclear Magnetic Resonance, Biomolecular|Protein Structure, Tertiary|Proteins|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-12-170', '21592348', 'The automation of objectively selecting amino acid residue ranges for structure superpositions is important for meaningful and consistent protein structure analyses. So far there is no widely-used standard for choosing these residue ranges for experimentally determined protein structures, where the manual selection of residue ranges or the use of suboptimal criteria remain commonplace.'),
(94317, 2011, 'bmc', 'TAFFEL: Independent Enrichment Analysis of gene sets', 'Kurki, Mitja I|Paananen, Jussi|Storvik, Markus|Ylä-Herttuala, Seppo|Jääskeläinen, Juha E|von Und Zu Fraunberg, Mikael|Wong, Garry|Pehkonen, Petri', 'Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.|Department of Biosciences, University of Eastern Finland, PO Box 1627, FIN-70211 Kuopio, Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Cell Line|Cluster Analysis|Colforsin|Gene Expression|Gene Expression Profiling|Humans|Intracranial Aneurysm|Software|Transcription, Genetic', 'Journal Article', '10.1186/1471-2105-12-171', '21592412', 'A major challenge in genomic research is identifying significant biological processes and generating new hypotheses from large gene sets. Gene sets often consist of multiple separate biological pathways, controlled by distinct regulatory mechanisms. Many of these pathways and the associated regulatory mechanisms might be obscured by a large number of other significant processes and thus not identified as significant by standard gene set enrichment analysis tools.'),
(94318, 2011, 'bmc', 'Genotype calling in tetraploid species from bi-allelic marker data using mixture models', 'Voorrips, Roeland E|Gort, Gerrit|Vosman, Ben', 'Plant Breeding Department, Wageningen University and Research Centre, Wageningen, The Netherlands. roeland.voorrips@wur.nl|Plant Breeding Department, Wageningen University and Research Centre, Wageningen, The Netherlands. roeland.voorrips@wur.nl|Plant Breeding Department, Wageningen University and Research Centre, Wageningen, The Netherlands. roeland.voorrips@wur.nl', 'Netherlands|Netherlands|Netherlands', 93, 'Algorithms|Alleles|DNA, Plant|Genotype|Heterozygote|Plants|Polymorphism, Single Nucleotide|Software|Solanum tuberosum|Tetraploidy', 'Journal Article', '10.1186/1471-2105-12-172', '21595880', 'Automated genotype calling in tetraploid species was until recently not possible, which hampered genetic analysis. Modern genotyping assays often produce two signals, one for each allele of a bi-allelic marker. While ample software is available to obtain genotypes (homozygous for either allele, or heterozygous) for diploid species from these signals, such software is not available for tetraploid species which may be scored as five alternative genotypes (aaaa, baaa, bbaa, bbba and bbbb, nulliplex to quadruplex).'),
(94319, 2011, 'bmc', 'An analysis of single amino acid repeats as use case for application specific background models', 'xc5x81abaj, Pawexc5x82 P|Sykacek, Peter|Kreil, David P', 'Chair of Bioinformatics, Boku University Vienna, Muthgasse 18, 1190 Vienna, Austria. Pawel.Labaj@boku.ac.at|Chair of Bioinformatics, Boku University Vienna, Muthgasse 18, 1190 Vienna, Austria. Pawel.Labaj@boku.ac.at|Chair of Bioinformatics, Boku University Vienna, Muthgasse 18, 1190 Vienna, Austria. Pawel.Labaj@boku.ac.at', 'Austria|Austria|Austria', 1, 'Amino Acid Motifs|Amino Acids|Eukaryota|Markov Chains|Models, Genetic|Protein Structure, Tertiary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-173', '21595908', 'Sequence analysis aims to identify biologically relevant signals against a backdrop of functionally meaningless variation. Increasingly, it is recognized that the quality of the background model directly affects the performance of analyses. State-of-the-art approaches rely on classical sequence models that are adapted to the studied dataset. Although performing well in the analysis of globular protein domains, these models break down in regions of stronger compositional bias or low complexity. While these regions are typically filtered, there is increasing anecdotal evidence of functional roles. This motivates an exploration of more complex sequence models and application-specific approaches for the investigation of biased regions.'),
(94320, 2011, 'bmc', 'Rebooting the human mitochondrial phylogeny: an automated and scalable methodology with expert knowledge', 'Blanco, Roberto|Mayordomo, Elvira|Montoya, Julio|Ruiz-Pesini, Eduardo', 'Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza, Zaragoza, Spain. robertob@unizar.es|Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza, Zaragoza, Spain. robertob@unizar.es|Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza, Zaragoza, Spain. robertob@unizar.es|Departamento de Informática e Ingeniería de Sistemas, Universidad de Zaragoza, Zaragoza, Spain. robertob@unizar.es', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|DNA, Mitochondrial|Genetic Variation|Humans|Mitochondria|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-174', '21595926', 'Mitochondrial DNA is an ideal source of information to conduct evolutionary and phylogenetic studies due to its extraordinary properties and abundance. Many insights can be gained from these, including but not limited to screening genetic variation to identify potentially deleterious mutations. However, such advances require efficient solutions to very difficult computational problems, a need that is hampered by the very plenty of data that confers strength to the analysis.'),
(94321, 2011, 'bmc', 'Toward an interactive article: integrating journals and biological databases', 'Rangarajan, Arun|Schedl, Tim|Yook, Karen|Chan, Juancarlos|Haenel, Stephen|Otis, Lolly|Faelten, Sharon|DePellegrin-Connelly, Tracey|Isaacson, Ruth|Skrzypek, Marek S|Marygold, Steven J|Stefancsik, Raymund|Cherry, J Michael|Sternberg, Paul W|Müller, Hans-Michael', 'Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, USA.|Division of Biology, California Institute of Technology, Pasadena, CA 91125, 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|United States|United States|United States', 0, 'Animals|Biology|Caenorhabditis elegans|Databases, Factual|Databases, Genetic|Internet|Periodicals as Topic|Quality Control', 'Journal Article', '10.1186/1471-2105-12-175', '21595960', 'Journal articles and databases are two major modes of communication in the biological sciences, and thus integrating these critical resources is of urgent importance to increase the pace of discovery. Projects focused on bridging the gap between journals and databases have been on the rise over the last five years and have resulted in the development of automated tools that can recognize entities within a document and link those entities to a relevant database. Unfortunately, automated tools cannot resolve ambiguities that arise from one term being used to signify entities that are quite distinct from one another. Instead, resolving these ambiguities requires some manual oversight. Finding the right balance between the speed and portability of automation and the accuracy and flexibility of manual effort is a crucial goal to making text markup a successful venture.'),
(94322, 2011, 'bmc', 'Web-based metabolic network visualization with a zooming user interface', 'Latendresse, Mario|Karp, Peter D', 'Bioinformatics Research Group, SRI International, Menlo Park, CA 94025, USA. latendre@ai.sri.com|Bioinformatics Research Group, SRI International, Menlo Park, CA 94025, USA. latendre@ai.sri.com', 'United States|United States', 20, 'Cells|Databases, Factual|Escherichia coli|Internet|Metabolic Networks and Pathways|Software|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-12-176', '21595965', 'Displaying complex metabolic-map diagrams, for Web browsers, and allowing users to interact with them for querying and overlaying expression data over them is challenging.'),
(94323, 2011, 'bmc', 'An application of kernel methods to variety identification based on SSR markers genetic fingerprinting', 'Martin, Florian', 'Biological Systems Research, Philip Morris International R&D, Philip Morris Products S,A,, Neuchâtel, Switzerland. florian.martin@pmi.com', 'Switzerland', 0, 'Algorithms|Chromosome Mapping|DNA Fingerprinting|DNA Primers|DNA, Plant|Genetic Markers|Polymorphism, Genetic|Tandem Repeat Sequences|Tobacco', 'Journal Article', '10.1186/1471-2105-12-177', '21595989', 'In crop production systems, genetic markers are increasingly used to distinguish individuals within a larger population based on their genetic make-up. Supervised approaches cannot be applied directly to genotyping data due to the specific nature of those data which are neither continuous, nor nominal, nor ordinal but only partially ordered. Therefore, a strategy is needed to encode the polymorphism between samples such that known supervised approaches can be applied. Moreover, finding a minimal set of molecular markers that have optimal ability to discriminate, for example, between given groups of varieties, is important as the genotyping process can be costly in terms of laboratory consumables, labor, and time. This feature selection problem also needs special care due to the specific nature of the data used.'),
(94324, 2011, 'bmc', 'TreeRipper web application: towards a fully automated optical tree recognition software', 'Hughes, Joseph', 'IBAHCM, College of Medical, Veterinary and Life Sciences, University of Glasgow, Graham Kerr Building, University Avenue, Glasgow, G12 8QQ, UK. joseph.hughes@glasgow.ac.uk', 'United Kingdom', 7, 'Animals|Biological Evolution|Classification|Genome|Humans|Internet|Phylogeny|Software', 'Journal Article', '10.1186/1471-2105-12-178', '21599881', 'Relationships between species, genes and genomes have been printed as trees for over a century. Whilst this may have been the best format for exchanging and sharing phylogenetic hypotheses during the 20th century, the worldwide web now provides faster and automated ways of transferring and sharing phylogenetic knowledge. However, novel software is needed to defrost these published phylogenies for the 21st century.'),
(94325, 2011, 'bmc', 'Brunn: an open source laboratory information system for microplates with a graphical plate layout design process', 'Alvarsson, Jonathan|Andersson, Claes|Spjuth, Ola|Larsson, Rolf|Wikberg, Jarl E S', 'Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. jonathan.alvarsson@farmbio.uu.se|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. jonathan.alvarsson@farmbio.uu.se|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. jonathan.alvarsson@farmbio.uu.se|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. jonathan.alvarsson@farmbio.uu.se|Department of Pharmaceutical Biosciences, Uppsala University, Uppsala, Sweden. jonathan.alvarsson@farmbio.uu.se', 'Sweden|Sweden|Sweden|Sweden|Sweden', 5, 'Cytological Techniques|Databases, Factual|Dose-Response Relationship, Drug|Drug Evaluation, Preclinical|High-Throughput Screening Assays|Software', 'Journal Article', '10.1186/1471-2105-12-179', '21599898', 'Compound profiling and drug screening generates large amounts of data and is generally based on microplate assays. Current information systems used for handling this are mainly commercial, closed source, expensive, and heavyweight and there is a need for a flexible lightweight open system for handling plate design, and validation and preparation of data.'),
(94326, 2011, 'bmc', 'A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression', 'Kalaitzis, Alfredo A|Lawrence, Neil D', 'The Sheffield Institute for Translational Neuroscience, 385A Glossop Road, Sheffield, S10 2HQ, UK. A.Kalaitzis@sheffield.ac.uk|The Sheffield Institute for Translational Neuroscience, 385A Glossop Road, Sheffield, S10 2HQ, UK. A.Kalaitzis@sheffield.ac.uk', 'United Kingdom|United Kingdom', 0, 'Bayes Theorem|Gene Expression Profiling|Normal Distribution|Oligonucleotide Array Sequence Analysis|Regression Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-180', '21599902', 'The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which genes are differentially expressed. Often these analysis stages are applied disregarding the fact that the data is drawn from a time series. In this paper we propose a simple model for accounting for the underlying temporal nature of the data based on a Gaussian process.'),
(94327, 2011, 'bmc', 'Protein alignment algorithms with an efficient backtracking routine on multiple GPUs', 'Blazewicz, Jacek|Frohmberg, Wojciech|Kierzynka, Michal|Pesch, Erwin|Wojciechowski, Pawel', 'Poznaxc5x84 University of Technology, Poznaxc5x84, Poland.|Poznaxc5x84 University of Technology, Poznaxc5x84, Poland.|Poznaxc5x84 University of Technology, Poznaxc5x84, Poland.|Poznaxc5x84 University of Technology, Poznaxc5x84, Poland.|Poznaxc5x84 University of Technology, Poznaxc5x84, Poland.', 'Poland|Poland|Poland|Poland|Poland', 0, 'Algorithms|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-12-181', '21599912', 'Pairwise sequence alignment methods are widely used in biological research. The increasing number of sequences is perceived as one of the upcoming challenges for sequence alignment methods in the nearest future. To overcome this challenge several GPU (Graphics Processing Unit) computing approaches have been proposed lately. These solutions show a great potential of a GPU platform but in most cases address the problem of sequence database scanning and computing only the alignment score whereas the alignment itself is omitted. Thus, the need arose to implement the global and semiglobal Needleman-Wunsch, and Smith-Waterman algorithms with a backtracking procedure which is needed to construct the alignment.'),
(94328, 2011, 'bmc', 'CLOTU: an online pipeline for processing and clustering of 454 amplicon reads into OTUs followed by taxonomic annotation', 'Kumar, Surendra|Carlsen, Tor|Mevik, Bjørn-Helge|Enger, Pål|Blaalid, Rakel|Shalchian-Tabrizi, Kamran|Kauserud, Håvard', 'Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no|Microbial Evolution Research Group, Department of Biology, University of Oslo, Blindern, N-0316 Oslo, Norway. surendra.kumar@bio.uio.no', 'Norway|Norway|Norway|Norway|Norway|Norway|Norway', 53, 'Classification|Computational Biology|DNA, Fungal|DNA, Ribosomal|Fungi|High-Throughput Nucleotide Sequencing|Software', 'Journal Article', '10.1186/1471-2105-12-182', '21599929', 'The implementation of high throughput sequencing for exploring biodiversity poses high demands on bioinformatics applications for automated data processing. Here we introduce CLOTU, an online and open access pipeline for processing 454 amplicon reads. CLOTU has been constructed to be highly user-friendly and flexible, since different types of analyses are needed for different datasets.'),
(94329, 2011, 'bmc', 'Normalization and centering of array-based heterologous genome hybridization based on divergent control probes', 'Darby, Brian J|Jones, Kenneth L|Wheeler, David|Herman, Michael A', 'Ecological Genomics Institute, Division of Biology, Kansas State University, Manhattan, KS 66506, USA.|Ecological Genomics Institute, Division of Biology, Kansas State University, Manhattan, KS 66506, USA.|Ecological Genomics Institute, Division of Biology, Kansas State University, Manhattan, KS 66506, USA.|Ecological Genomics Institute, Division of Biology, Kansas State University, Manhattan, KS 66506, USA.', 'United States|United States|United States|United States', 0, 'Animals|Caenorhabditis|Caenorhabditis elegans|Genome|Nucleic Acid Hybridization|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-183', '21600029', 'Hybridization of heterologous (non-specific) nucleic acids onto arrays designed for model-organisms has been proposed as a viable genomic resource for estimating sequence variation and gene expression in non-model organisms. However, conventional methods of normalization that assume equivalent distributions (such as quantile normalization) are inappropriate when applied to non-specific (heterologous) hybridization. We propose an algorithm for normalizing and centering intensity data from heterologous hybridization that makes no prior assumptions of distribution, reduces the false appearance of homology, and provides a way for researchers to confirm whether heterologous hybridization is suitable.'),
(94330, 2011, 'bmc', 'SuiteMSA: visual tools for multiple sequence alignment comparison and molecular sequence simulation', 'Anderson, Catherine L|Strope, Cory L|Moriyama, Etsuko N', 'Department of Computer Science and Engineering, University of Nebraska, Lincoln, Nebraska 68588, USA.|Department of Computer Science and Engineering, University of Nebraska, Lincoln, Nebraska 68588, USA.|Department of Computer Science and Engineering, University of Nebraska, Lincoln, Nebraska 68588, USA.', 'United States|United States|United States', 15, 'Amino Acid Sequence|Animals|Humans|Lipocalins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1186/1471-2105-12-184', '21600033', 'Multiple sequence alignment (MSA) plays a central role in nearly all bioinformatics and molecular evolutionary applications. MSA reconstruction is thus one of the most heavily scrutinized bioinformatics fields. Evaluating the quality of MSA reconstruction is often hindered by the lack of good reference MSAs. The use of sequence evolution simulation can provide such reference MSAs. Furthermore, none of the MSA viewing/editing programs currently available allows the user to make direct comparisons between two or more MSAs. Considering the importance of MSA quality in a wide range of research, it is desirable if MSA assessment can be performed more easily.'),
(94331, 2011, 'bmc', 'GPCR-SSFE: a comprehensive database of G-protein-coupled receptor template predictions and homology models', 'Worth, Catherine L|Kreuchwig, Annika|Kleinau, Gunnar|Krause, Gerd', 'Leibniz-Institut für Molekulare Pharmakologie, 13125 Berlin, Germany.|Leibniz-Institut für Molekulare Pharmakologie, 13125 Berlin, Germany.|Leibniz-Institut für Molekulare Pharmakologie, 13125 Berlin, Germany.|Leibniz-Institut für Molekulare Pharmakologie, 13125 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 47, 'Amino Acid Motifs|Animals|Databases, Protein|Humans|Models, Molecular|Protein Structure, Secondary|Receptors, G-Protein-Coupled|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-12-185', '21605354', 'G protein-coupled receptors (GPCRs) transduce a wide variety of extracellular signals to within the cell and therefore have a key role in regulating cell activity and physiological function. GPCR malfunction is responsible for a wide range of diseases including cancer, diabetes and hyperthyroidism and a large proportion of drugs on the market target these receptors. The three dimensional structure of GPCRs is important for elucidating the molecular mechanisms underlying these diseases and for performing structure-based drug design. Although structural data are restricted to only a handful of GPCRs, homology models can be used as a proxy for those receptors not having crystal structures. However, many researchers working on GPCRs are not experienced homology modellers and are therefore unable to benefit from the information that can be gleaned from such three-dimensional models. Here, we present a comprehensive database called the GPCR-SSFE, which provides initial homology models of the transmembrane helices for a large variety of family A GPCRs.'),
(94332, 2011, 'bmc', 'Extension of the bayesian alphabet for genomic selection', 'Habier, David|Fernando, Rohan L|Kizilkaya, Kadir|Garrick, Dorian J', 'Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA. dhabier@gmail.com|Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA. dhabier@gmail.com|Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA. dhabier@gmail.com|Department of Animal Science and Center for Integrated Animal Genomics, Iowa State University, Ames, IA 50011, USA. dhabier@gmail.com', 'United States|United States|United States|United States', 0, 'Animals|Bayes Theorem|Cattle|Computer Simulation|Female|Genome|Male|Milk|Polymorphism, Single Nucleotide|Proteins|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-12-186', '21605355', 'Two bayesian methods, BayesCxcfx80 and BayesDxcfx80, were developed for genomic prediction to address the drawback of BayesA and BayesB regarding the impact of prior hyperparameters and treat the prior probability xcfx80 that a SNP has zero effect as unknown. The methods were compared in terms of inference of the number of QTL and accuracy of genomic estimated breeding values (GEBVs), using simulated scenarios and real data from North American Holstein bulls.'),
(94333, 2011, 'bmc', 'Extracting scientific articles from a large digital archive: BioStor and the Biodiversity Heritage Library', 'Page, Roderic D M', 'Institute of Biodiversity, Animal Health and Comparative Medicine, College of Medical, Veterinary and Life Sciences, Graham Kerr Building, University of Glasgow, Glasgow G12 8QQ, UK. Roderic.Page@glasgow.ac.uk', 'United Kingdom', 12, 'Archives|Biodiversity|Biology|Information Storage and Retrieval|Libraries, Digital|Periodicals as Topic|Publications', 'Journal Article', '10.1186/1471-2105-12-187', '21605356', 'The Biodiversity Heritage Library (BHL) is a large digital archive of legacy biological literature, comprising over 31 million pages scanned from books, monographs, and journals. During the digitisation process basic metadata about the scanned items is recorded, but not article-level metadata. Given that the article is the standard unit of citation, this makes it difficult to locate cited literature in BHL. Adding the ability to easily find articles in BHL would greatly enhance the value of the archive.'),
(94334, 2011, 'bmc', 'The biomedical discourse relation bank', 'Prasad, Rashmi|McRoy, Susan|Frid, Nadya|Joshi, Aravind|Yu, Hong', 'Institute for Research in Cognitive Science, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA 19104, USA.|Institute for Research in Cognitive Science, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA 19104, USA.|Institute for Research in Cognitive Science, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA 19104, USA.|Institute for Research in Cognitive Science, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA 19104, USA.|Institute for Research in Cognitive Science, University of Pennsylvania, 3401 Walnut Street, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States', 0, 'Computational Biology|Data Mining|Humans|Natural Language Processing|Semantics|Software', 'Journal Article', '10.1186/1471-2105-12-188', '21605399', 'Identification of discourse relations, such as causal and contrastive relations, between situations mentioned in text is an important task for biomedical text-mining. A biomedical text corpus annotated with discourse relations would be very useful for developing and evaluating methods for biomedical discourse processing. However, little effort has been made to develop such an annotated resource.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94335, 2011, 'bmc', 'Enriching for correct prediction of biological processes using a combination of diverse classifiers', 'Ko, Daijin|Windle, Brad', 'Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.|Department of Medicinal Chemistry, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA.', 'United States|United States', 4, 'Algorithms|Animals|Artificial Intelligence|Cell Line, Tumor|Gene Expression Profiling|Humans|Neural Networks (Computer)|Probability', 'Journal Article', '10.1186/1471-2105-12-189', '21605426', 'Machine learning models (classifiers) for classifying genes to biological processes each have their own unique characteristics in what genes can be classified and to what biological processes. No single learning model is qualitatively superior to any other model and overall precision for each model tends to be low. The classification results for each classifier can be complementary and synergistic suggesting the benefit of a combination of algorithms, but often the prediction probability outputs of various learning models are neither comparable nor compatible for combining. A means to compare outputs regardless of the model and data used and combine the results into an improved comprehensive model is needed.'),
(94336, 2011, 'bmc', 'Stereochemical errors and their implications for molecular dynamics simulations', 'Schreiner, Eduard|Trabuco, Leonardo G|Freddolino, Peter L|Schulten, Klaus', 'Beckman Institute for Advanced Science Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Beckman Institute for Advanced Science Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Beckman Institute for Advanced Science Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.|Beckman Institute for Advanced Science Technology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA.', 'United States|United States|United States|United States', 33, 'Amino Acids|Models, Molecular|Molecular Dynamics Simulation|Nucleic Acids|Nucleosides|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-190', '21605430', 'Biological molecules are often asymmetric with respect to stereochemistry, and correct stereochemistry is essential to their function. Molecular dynamics simulations of biomolecules have increasingly become an integral part of biophysical research. However, stereochemical errors in biomolecular structures can have a dramatic impact on the results of simulations.'),
(94337, 2011, 'bmc', 'MINE: Module Identification in Networks', 'Rhrissorrakrai, Kahn|Gunsalus, Kristin C', 'Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA.|Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA.', 'United States|United States', 0, 'Algorithms|Animals|Caenorhabditis elegans|Cluster Analysis|Proteins|Saccharomyces cerevisiae', 'Journal Article', '10.1186/1471-2105-12-192', '21605434', 'Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks.'),
(94338, 2011, 'bmc', 'Bacterial syntenies: an exact approach with gene quorum', 'Deniélou, Yves-Pol|Sagot, Marie-France|Boyer, Frédéric|Viari, Alain', 'INRIA Grenoble-Rhône-Alpes, Team BAMBOO, 655 Avenue de lEurope, 38334 Montbonnot Cedex, France. yves-pol.denielou@laposte.net|INRIA Grenoble-Rhône-Alpes, Team BAMBOO, 655 Avenue de lEurope, 38334 Montbonnot Cedex, France. yves-pol.denielou@laposte.net|INRIA Grenoble-Rhône-Alpes, Team BAMBOO, 655 Avenue de lEurope, 38334 Montbonnot Cedex, France. yves-pol.denielou@laposte.net|INRIA Grenoble-Rhône-Alpes, Team BAMBOO, 655 Avenue de lEurope, 38334 Montbonnot Cedex, France. yves-pol.denielou@laposte.net', 'France|France|France|France', 0, 'Algorithms|Bacteria|Gene Expression Regulation, Bacterial|Gene Order|Genome, Bacterial|Synteny', 'Journal Article', '10.1186/1471-2105-12-193', '21605461', 'The automatic identification of syntenies across multiple species is a key step in comparative genomics that helps biologists shed light both on evolutionary and functional problems.'),
(94339, 2011, 'bmc', 'Inference of chromosome-specific copy numbers using population haplotypes', 'Huang, Yao-Ting|Wu, Min-Han', 'Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan. ythuang@cs.ccu.edu.tw|Department of Computer Science and Information Engineering, National Chung Cheng University, Chia-Yi, Taiwan. ythuang@cs.ccu.edu.tw', '-|-', 0, 'Algorithms|Chromosomes|DNA Copy Number Variations|Genetics, Population|Genome, Human|Haplotypes|Humans|Linkage Disequilibrium|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-12-194', '21605463', 'Using microarray and sequencing platforms, a large number of copy number variations (CNVs) have been identified in humans. In practice, because our human genome is a diploid, these platforms are limited to or more accurate for detecting total copy numbers rather than chromosome-specific copy numbers at each of the two homologous chromosomes. Nevertheless, the analysis of linkage disequilibrium (LD) between CNVs and SNPs indicates that distinct copy numbers often sit on their own background haplotypes.'),
(94340, 2011, 'bmc', 'Mapping the distribution of packing topologies within protein interiors shows predominant preference for specific packing motifs', 'Basu, Sankar|Bhattacharyya, Dhananjay|Banerjee, Rahul', 'Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Bidhannagar, Kolkata, India.|Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Bidhannagar, Kolkata, India.|Crystallography and Molecular Biology Division, Saha Institute of Nuclear Physics, Bidhannagar, Kolkata, India.', 'India|India|India', 14, 'Amino Acid Motifs|Crystallography, X-Ray|Microtubule-Associated Proteins|Models, Molecular|Protein Folding|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-12-195', '21605466', 'Mapping protein primary sequences to their three dimensional folds referred to as the second genetic code remains an unsolved scientific problem. A crucial part of the problem concerns the geometrical specificity in side chain association leading to densely packed protein cores, a hallmark of correctly folded native structures. Thus, any model of packing within proteins should constitute an indispensable component of protein folding and design.'),
(94341, 2011, 'bmc', 'Acorn: a grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface', 'Sroka, Jacek|Bieniasz-Krzywiec, Lukasz|Gwxc3xb3xc5xbadxc5xba, Szymon|Leniowski, Dariusz|Lxc4x85cki, Jakub|Markowski, Mateusz|Avignone-Rossa, Claudio|Bushell, Michael E|McFadden, Johnjoe|Kierzek, Andrzej M', 'Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.|Institute of Informatics University of Warsaw, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland|Poland', 0, 'Computer Simulation|Escherichia coli|Game Theory|Humans|Metabolic Networks and Pathways|Mycobacterium tuberculosis|Protein Structure, Secondary|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1186/1471-2105-12-196', '21609434', 'Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment.'),
(94342, 2011, 'bmc', 'Linear and non-linear dependencies between copy number aberrations and mRNA expression reveal distinct molecular pathways in breast cancer', 'Solvang, Hiroko K|Lingjærde, Ole Christian|Frigessi, Arnoldo|Børresen-Dale, Anne-Lise|Kristensen, Vessela N', 'Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Montebello, and Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, 0310 Oslo, Norway. hsolvang@rr-research.no|Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Montebello, and Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, 0310 Oslo, Norway. hsolvang@rr-research.no|Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Montebello, and Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, 0310 Oslo, Norway. hsolvang@rr-research.no|Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Montebello, and Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, 0310 Oslo, Norway. hsolvang@rr-research.no|Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Montebello, and Department of Biostatistics, Institute of Basic Medical Science, University of Oslo, 0310 Oslo, Norway. hsolvang@rr-research.no', 'Norway|Norway|Norway|Norway|Norway', 25, 'Algorithms|Breast Neoplasms|Comparative Genomic Hybridization|Gene Dosage|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Signal Transduction', 'Journal Article', '10.1186/1471-2105-12-197', '21609452', 'Elucidating the exact relationship between gene copy number and expression would enable identification of regulatory mechanisms of abnormal gene expression and biological pathways of regulation. Most current approaches either depend on linear correlation or on nonparametric tests of association that are insensitive to the exact shape of the relationship. Based on knowledge of enzyme kinetics and gene regulation, we would expect the functional shape of the relationship to be gene dependent and to be related to the gene regulatory mechanisms involved. Here, we propose a statistical approach to investigate and distinguish between linear and nonlinear dependences between DNA copy number alteration and mRNA expression.'),
(94343, 2011, 'bmc', 'HMM-FRAME: accurate protein domain classification for metagenomic sequences containing frameshift errors', 'Zhang, Yuan|Sun, Yanni', 'Computer Science and Engineering Department, Michigan State University, East Lansing, USA.|Computer Science and Engineering Department, Michigan State University, East Lansing, USA.', 'United States|United States', 44, 'Algorithms|Anabaena|Burkholderia|Desulfitobacterium|Dioxygenases|Markov Chains|Metagenomics|Protein Structure, Tertiary|Reading Frames|Research Design|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-198', '21609463', 'Protein domain classification is an important step in metagenomic annotation. The state-of-the-art method for protein domain classification is profile HMM-based alignment. However, the relatively high rates of insertions and deletions in homopolymer regions of pyrosequencing reads create frameshifts, causing conventional profile HMM alignment tools to generate alignments with marginal scores. This makes error-containing gene fragments unclassifiable with conventional tools. Thus, there is a need for an accurate domain classification tool that can detect and correct sequencing errors.'),
(94344, 2011, 'bmc', 'MimoPro: a more efficient Web-based tool for epitope prediction using phage display libraries', 'Chen, Wen Han|Sun, Ping Ping|Lu, Yang|Guo, William W|Huang, Yan Xin|Ma, Zhi Qiang', 'School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.|School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.|School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.|School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.|School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.|School of Computer Science and Information Technology, Northeast Normal University, Changchun 130024, P.R. China.', 'China|China|China|China|China|China', 27, 'Algorithms|Antigens|Bacteriophages|Crystallography, X-Ray|Epitope Mapping|Epitopes, B-Lymphocyte|Internet|Peptide Library|Peptides|Software', 'Journal Article', '10.1186/1471-2105-12-199', '21609501', 'A B-cell epitope is a group of residues on the surface of an antigen which stimulates humoral responses. Locating these epitopes on antigens is important for the purpose of effective vaccine design. In recent years, mapping affinity-selected peptides screened from a random phage display library to the native epitope has become popular in epitope prediction. These peptides, also known as mimotopes, share the similar structure and function with the corresponding native epitopes. Great effort has been made in using this similarity between such mimotopes and native epitopes in prediction, which has resulted in better outcomes than statistics-based methods can. However, it cannot maintain a high degree of satisfaction in various circumstances.'),
(94345, 2011, 'bmc', 'rnaSeqMap: a Bioconductor package for RNA sequencing data exploration', 'Lexc5x9bniewska, Anna|Okoniewski, Michaxc5x82 J', 'Functional Genomics Center UNI ETH Zurich, Winterthurerstrasse, Switzerland.|Functional Genomics Center UNI ETH Zurich, Winterthurerstrasse, Switzerland.', 'Switzerland|Switzerland', 7, 'Animals|Gene Expression Profiling|Genome|Humans|Oligonucleotide Array Sequence Analysis|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-200', '21612622', 'The throughput of commercially available sequencers has recently significantly increased. It has reached the point where measuring the RNA expression by the depth of coverage has become feasible even for largest genomes. The development of software tools is constantly following the progress of biological hardware. In particular, as RNA sequencing software can be regarded genome browsers, exon junction tools and statistical tools operating on counts of reads in predefined regions. The library rnaSeqMap, freely available via Bioconductor, is an RNA sequencing software which is independent of any biological hardware platform. It is based upon standard Bioconductor infrastructure for sequencing data and includes several novel features focused on deeper understanding of coverage expression profiles and discovery of novel transcription regions.'),
(94346, 2011, 'bmc', 'CAPL: an efficient association software package using family and case-control data and accounting for population stratification', 'Chung, Ren-Hua|Schmidt, Michael A|Martin, Eden R', 'Center for Genetic Epidemiology and Statistical Genetics, John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA. rchung@med.miami.edu|Center for Genetic Epidemiology and Statistical Genetics, John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA. rchung@med.miami.edu|Center for Genetic Epidemiology and Statistical Genetics, John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA. rchung@med.miami.edu', 'United States|United States|United States', 2, 'Algorithms|Biometry|Case-Control Studies|Genome-Wide Association Study|Humans|Software', 'Journal Article', '10.1186/1471-2105-12-201', '21612626', 'With many genome-wide association study (GWAS) datasets available, it is critical that we have statistical tools that are both flexible to accommodate different study designs and fast. We recently proposed the combined APL (CAPL) method, which can use family and case-control datasets and can account for population stratification in the data. Because computationally intensive algorithms are used in CAPL, implementing CAPL with efficient parallel algorithms is essential.'),
(94347, 2011, 'bmc', 'Qxpak5: old mixed model solutions for new genomics problems', 'Pérez-Enciso, Miguel|Misztal, Ignacy', 'ICREA-CRAG-Universitat Autònoma de Barcelona, Bellaterra, Spain. miguel.perez@uab.es|ICREA-CRAG-Universitat Autònoma de Barcelona, Bellaterra, Spain. miguel.perez@uab.es', 'Spain|Spain', 68, 'Algorithms|Animals|Databases, Genetic|Genomics|Humans|Models, Statistical|Quantitative Trait Loci|Software', 'Journal Article', '10.1186/1471-2105-12-202', '21612630', 'Mixed models have a long and fruitful history in statistics. They are pertinent to genomics problems because they are highly versatile, accommodating a wide variety of situations within the same theoretical and algorithmic framework.'),
(94348, 2011, 'bmc', 'Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis', 'Lysenko, Artem|Defoin-Platel, Michael|Hassani-Pak, Keywan|Taubert, Jan|Hodgman, Charlie|Rawlings, Christopher J|Saqi, Mansoor', 'Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk|Centre for Mathematical and Computational Biology, Rothamsted Research, Harpenden, Herts, AL5, 2JQ, UK. sbxal1@nottingham.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 15, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Cluster Analysis|Databases, Genetic|Markov Chains|Metabolic Networks and Pathways|Metabolomics', 'Journal Article', '10.1186/1471-2105-12-203', '21612636', 'Combining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems.'),
(94349, 2011, 'bmc', 'Tree edit distance for leaf-labelled trees on free leafset and its comparison with frequent subsplit dissimilarity and popular distance measures', 'Koperwas, Jakub|Walczak, Krzysztof', 'Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland. j.koperwas@elka.pw.edu.pl|Institute of Computer Science, Warsaw University of Technology, Nowowiejska 15/19, 00-665 Warsaw, Poland. j.koperwas@elka.pw.edu.pl', 'Poland|Poland', 0, 'Biological Evolution|Computational Biology|Phylogeny', 'Journal Article', '10.1186/1471-2105-12-204', '21612645', 'This paper is devoted to distance measures for leaf-labelled trees on free leafset. A leaf-labelled tree is a data structure which is a special type of a tree where only leaves (terminal) nodes are labelled. This data structure is used in bioinformatics for modelling of evolution history of genes and species and also in linguistics for modelling of languages evolution history. Many domain specific problems occur and need to be solved with help of tree postprocessing techniques such as distance measures.'),
(94350, 2011, 'bmc', 'A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data', 'Nishiyama, Takeshi|Takahashi, Kunihiko|Tango, Toshiro|Pinto, Dalila|Scherer, Stephen W|Takami, Satoshi|Kishino, Hirohisa', 'National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp|National Institute of Public Health, Wako, Saitama 351-0197, Japan. nishiyama@minos.ocn.ne.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 3, 'Autistic Disorder|Case-Control Studies|Computer Simulation|Gene Dosage|Genome-Wide Association Study|Humans|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-12-205', '21612662', 'Several statistical tests have been developed for analyzing genome-wide association data by incorporating gene pathway information in terms of gene sets. Using these methods, hundreds of gene sets are typically tested, and the tested gene sets often overlap. This overlapping greatly increases the probability of generating false positives, and the results obtained are difficult to interpret, particularly when many gene sets show statistical significance.'),
(94351, 2011, 'bmc', 'New methods to measure residues coevolution in proteins', 'Gao, Hongyun|Dou, Yongchao|Yang, Jialiang|Wang, Jun', 'School of Mathematical Sciences, Dalian University of Technology, Dalian, Peoples Republic of China.|School of Mathematical Sciences, Dalian University of Technology, Dalian, Peoples Republic of China.|School of Mathematical Sciences, Dalian University of Technology, Dalian, Peoples Republic of China.|School of Mathematical Sciences, Dalian University of Technology, Dalian, Peoples Republic of China.', 'China|China|China|China', 12, 'Amino Acid Sequence|Evolution, Molecular|Models, Molecular|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-206', '21612664', 'The covariation of two sites in a protein is often used as the degree of their coevolution. To quantify the covariation many methods have been developed and most of them are based on residues position-specific frequencies by using the mutual information (MI) model.'),
(94352, 2011, 'bmc', 'HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information', 'Liu, Rong|Hu, Jianjun', 'Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.|Department of Computer Science and Engineering, University of South Carolina, Columbia, SC 29208, USA.', 'United States|United States', 0, 'Algorithms|Computational Biology|Heme|Ligands|Protein Binding|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-207', '21612668', 'Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligand that plays critical roles in electron transfer, catalysis, signal transduction and gene expression. Although much effort has been devoted to the development of various generic algorithms for ligand binding site prediction over the last decade, no algorithm has been specifically designed to complement experimental techniques for identification of heme binding residues. Consequently, an urgent need is to develop a computational method for recognizing these important residues.'),
(94353, 2011, 'bmc', 'NCACO-score: an effective main-chain dependent scoring function for structure modeling', 'Tian, Liqing|Wu, Aiping|Cao, Yang|Dong, Xiaoxi|Hu, Yun|Jiang, Taijiao', 'National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.|National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China|China|China', 4, 'Amino Acids|Databases, Protein|Models, Molecular|Proteins', 'Journal Article', '10.1186/1471-2105-12-208', '21612673', 'Development of effective scoring functions is a critical component to the success of protein structure modeling. Previously, many efforts have been dedicated to the development of scoring functions. Despite these efforts, development of an effective scoring function that can achieve both good accuracy and fast speed still presents a grand challenge.'),
(94354, 2011, 'bmc', 'Multiple testing for gene sets from microarray experiments', 'Sohn, Insuk|Owzar, Kouros|Lim, Johan|George, Stephen L|Mackey Cushman, Stephanie|Jung, Sin-Ho', 'Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.|Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.|Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.|Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.|Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.|Biostatistics and Bioinformatics Center, Samsung Cancer Research Institute, Samsung Medical Center, Seoul 137-710, Republic of Korea.', '-|-|-|-|-|-', 4, 'Gene Expression Profiling|Genetic Association Studies|Humans|Lung Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-12-209', '21615889', 'A key objective in many microarray association studies is the identification of individual genes associated with clinical outcome. It is often of additional interest to identify sets of genes, known a priori to have similar biologic function, associated with the outcome.'),
(94355, 2011, 'bmc', 'A novel and well-defined benchmarking method for second generation read mapping', 'Holtgrewe, Manuel|Emde, Anne-Katrin|Weese, David|Reinert, Knut', 'Department of Computer Science, Free University of Berlin, Takustr, Germany. holtgrewe@inf.fu-berlin.de|Department of Computer Science, Free University of Berlin, Takustr, Germany. holtgrewe@inf.fu-berlin.de|Department of Computer Science, Free University of Berlin, Takustr, Germany. holtgrewe@inf.fu-berlin.de|Department of Computer Science, Free University of Berlin, Takustr, Germany. holtgrewe@inf.fu-berlin.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Animals|High-Throughput Nucleotide Sequencing|Humans|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-210', '21615913', 'Second generation sequencing technologies yield DNA sequence data at ultra high-throughput. Common to most biological applications is a mapping of the reads to an almost identical or highly similar reference genome. The assessment of the quality of read mapping results is not straightforward and has not been formalized so far. Hence, it has not been easy to compare different read mapping approaches in a unified way and to determine which program is the best for what task.'),
(94356, 2011, 'bmc', 'Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping', 'Cai, Xiaodong|Huang, Anhui|Xu, Shizhong', 'Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33146, USA. x.cai@miami.edu|Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33146, USA. x.cai@miami.edu|Department of Electrical and Computer Engineering, University of Miami, Coral Gables, FL 33146, USA. x.cai@miami.edu', 'United States|United States|United States', 40, 'Algorithms|Ascomycota|Bayes Theorem|Chromosome Mapping|Linear Models|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-12-211', '21615941', 'The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs) mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB) method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model.'),
(94357, 2011, 'bmc', 'MixtureTree: a program for constructing phylogeny', 'Chen, Shu-Chuan|Rosenberg, Michael S|Lindsay, Bruce G', 'School of Mathematical and Statistical Sciences, Arizona State University, Tempe, 85287, USA. scchen@math.asu.edu|School of Mathematical and Statistical Sciences, Arizona State University, Tempe, 85287, USA. scchen@math.asu.edu|School of Mathematical and Statistical Sciences, Arizona State University, Tempe, 85287, USA. scchen@math.asu.edu', 'United States|United States|United States', 3, 'Algorithms|Likelihood Functions|Phylogeny|Polymorphism, Single Nucleotide|Software|Time Factors', 'Comparative Study', '10.1186/1471-2105-12-111', '21615972', 'MixtureTree v1.0 is a Linux based program (written in C++) which implements an algorithm based on mixture models for reconstructing phylogeny from binary sequence data, such as single-nucleotide polymorphisms (SNPs). In addition to the mixture algorithm with three different optimization options, the program also implements a bootstrap procedure with majority-rule consensus.'),
(94358, 2010, 'bmc', 'Proceedings of the 11th Annual Bioinformatics Open Source Conference (BOSC) 2010 July 9-10, 2010 Boston, Massachusetts, USA', '-', '-', '-', 0, 'Computational Biology|Humans', 'Congress', '10.1186/1471-2105-12-111', '21618735', '-'),
(94359, 2011, 'bmc', 'Exploring subdomain variation in biomedical language', 'Lippincott, Thomas|Séaghdha, Diarmuid Ó|Korhonen, Anna', 'Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK. Thomas.Lippincott@cl.cam.ac.uk|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK. Thomas.Lippincott@cl.cam.ac.uk|Computer Laboratory, University of Cambridge, Cambridge CB3 0FD, UK. Thomas.Lippincott@cl.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 18, 'Artificial Intelligence|Biomedical Research|Child|Data Mining|Humans|Natural Language Processing|Semantics', 'Journal Article', '10.1186/1471-2105-12-212', '21619603', 'Applications of Natural Language Processing (NLP) technology to biomedical texts have generated significant interest in recent years. In this paper we identify and investigate the phenomenon of linguistic subdomain variation within the biomedical domain, i.e., the extent to which different subject areas of biomedicine are characterised by different linguistic behaviour. While variation at a coarser domain level such as between newswire and biomedical text is well-studied and known to affect the portability of NLP systems, we are the first to conduct an extensive investigation into more fine-grained levels of variation.'),
(94360, 2011, 'bmc', 'Identifier mapping performance for integrating transcriptomics and proteomics experimental results', 'Day, Roger S|McDade, Kevin K|Chandran, Uma R|Lisovich, Alex|Conrads, Thomas P|Hood, Brian L|Kolli, V S Kumar|Kirchner, David|Litzi, Traci|Maxwell, G Larry', 'Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu|Department of Biomedical Informatics, University of Pittsburgh School of Medicine, Pittsburgh, PA 15261, USA. day01@pitt.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 34, 'Endometrial Neoplasms|Endometrium|Female|Gene Expression Profiling|Humans|Proteome|Proteomics|Regression Analysis', 'Journal Article', '10.1186/1471-2105-12-213', '21619611', 'Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit.'),
(94361, 2011, 'bmc', 'Structator: fast index-based search for RNA sequence-structure patterns', 'Meyer, Fernando|Kurtz, Stefan|Backofen, Rolf|Will, Sebastian|Beckstette, Michael', 'Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.|Center for Bioinformatics, University of Hamburg, Bundesstrasse 43, 20146 Hamburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 24, 'Algorithms|Base Sequence|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-214', '21619640', 'The secondary structure of RNA molecules is intimately related to their function and often more conserved than the sequence. Hence, the important task of searching databases for RNAs requires to match sequence-structure patterns. Unfortunately, current tools for this task have, in the best case, a running time that is only linear in the size of sequence databases. Furthermore, established index data structures for fast sequence matching, like suffix trees or arrays, cannot benefit from the complementarity constraints introduced by the secondary structure of RNAs.'),
(94362, 2011, 'bmc', 'A beta-mixture model for dimensionality reduction, sample classification and analysis', 'Laurila, Kirsti|Oster, Bodil|Andersen, Claus L|Lamy, Philippe|Orntoft, Torben|Yli-Harja, Olli|Wiuf, Carsten', 'Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.|Bioinformatics Research Centre, Aarhus University, C.F. Møllers Allé 8, DK-8000 Århus C, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 10, 'Algorithms|Colonic Neoplasms|CpG Islands|DNA Methylation|Genome, Human|Genome-Wide Association Study|Humans|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis', 'Journal Article', '10.1186/1471-2105-12-215', '21619656', 'Patterns of genome-wide methylation vary between tissue types. For example, cancer tissue shows markedly different patterns from those of normal tissue. In this paper we propose a beta-mixture model to describe genome-wide methylation patterns based on probe data from methylation microarrays. The model takes dependencies between neighbour probe pairs into account and assumes three broad categories of methylation, low, medium and high. The model is described by 37 parameters, which reduces the dimensionality of a typical methylation microarray significantly. We used methylation microarray data from 42 colon cancer samples to assess the model.'),
(94363, 2011, 'bmc', 'miRFam: an effective automatic miRNA classification method based on n-grams and a multiclass SVM', 'Ding, Jiandong|Zhou, Shuigeng|Guan, Jihong', 'School of Computer Science, Fudan University, Shanghai 200433, China.|School of Computer Science, Fudan University, Shanghai 200433, China.|School of Computer Science, Fudan University, Shanghai 200433, China.', 'China|China|China', 27, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|MicroRNAs|RNA, Helminth|Schistosoma|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-12-216', '21619662', 'MicroRNAs (miRNAs) are ~22 nt long integral elements responsible for post-transcriptional control of gene expressions. After the identification of thousands of miRNAs, the challenge is now to explore their specific biological functions. To this end, it will be greatly helpful to construct a reasonable organization of these miRNAs according to their homologous relationships. Given an established miRNA family system (e.g. the miRBase family organization), this paper addresses the problem of automatically and accurately classifying newly found miRNAs to their corresponding families by supervised learning techniques. Concretely, we propose an effective method, miRFam, which uses only primary information of pre-miRNAs or mature miRNAs and a multiclass SVM, to automatically classify miRNA genes.'),
(94364, 2011, 'bmc', 'Conotoxin protein classification using free scores of words and support vector machines', 'Zaki, Nazar|Wolfsheimer, Stefan|Nuel, Gregory|Khuri, Sawsan', 'Faculty of Information Technology, UAE University, 17551 Al-Ain, UAE. nzaki@uaeu.ac.ae|Faculty of Information Technology, UAE University, 17551 Al-Ain, UAE. nzaki@uaeu.ac.ae|Faculty of Information Technology, UAE University, 17551 Al-Ain, UAE. nzaki@uaeu.ac.ae|Faculty of Information Technology, UAE University, 17551 Al-Ain, UAE. nzaki@uaeu.ac.ae', '-|-|-|-', 21, 'Algorithms|Animals|Artificial Intelligence|Conotoxins|Conus Snail|Neuropeptides|Software', 'Journal Article', '10.1186/1471-2105-12-217', '21619696', 'Conotoxin has been proven to be effective in drug design and could be used to treat various disorders such as schizophrenia, neuromuscular disorders and chronic pain. With the rapidly growing interest in conotoxin, accurate conotoxin superfamily classification tools are desirable to systematize the increasing number of newly discovered sequences and structures. However, despite the significance and extensive experimental investigations on conotoxin, those tools have not been intensively explored.'),
(94365, 2011, 'bmc', 'OntoCAT--simple ontology search and integration in Java, R and REST/JavaScript', 'Adamusiak, Tomasz|Burdett, Tony|Kurbatova, Natalja|Joeri van der Velde, K|Abeygunawardena, Niran|Antonakaki, Despoina|Kapushesky, Misha|Parkinson, Helen|Swertz, Morris A', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Cambridge, CB10 1SD, UK. tomasz@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Computational Biology|Databases, Factual|Humans|Programming Languages|Software|User-Computer Interface|Vocabulary|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-12-218', '21619703', 'Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups.'),
(94366, 2011, 'bmc', 'RAG: an update to the RNA-As-Graphs resource', 'Izzo, Joseph A|Kim, Namhee|Elmetwaly, Shereef|Schlick, Tamar', 'Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.', 'United States|United States|United States|United States', 32, 'Algorithms|Cluster Analysis|Databases, Nucleic Acid|Internet|Nucleic Acid Conformation|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-219', '21627789', 'In 2004, we presented a web resource for stimulating the search for novel RNAs, RNA-As-Graphs (RAG), which classified, catalogued, and predicted RNA secondary structure motifs using clustering and build-up approaches. With the increased availability of secondary structures in recent years, we update the RAG resource and provide various improvements for analyzing RNA structures.'),
(94367, 2011, 'bmc', 'Software comparison for evaluating genomic copy number variation for Affymetrix 60 SNP array platform', 'Eckel-Passow, Jeanette E|Atkinson, Elizabeth J|Maharjan, Sooraj|Kardia, Sharon L R|de Andrade, Mariza', 'Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. eckel@mayo.edu|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. eckel@mayo.edu|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. eckel@mayo.edu|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. eckel@mayo.edu|Division of Biomedical Statistics and Informatics, Mayo Clinic, 200 First Street SW, Rochester, MN 55905, USA. eckel@mayo.edu', 'United States|United States|United States|United States|United States', 39, 'Algorithms|DNA Copy Number Variations|Gene Dosage|Genome|Genome, Human|Genome-Wide Association Study|Genotype|Humans|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1186/1471-2105-12-220', '21627824', 'Copy number data are routinely being extracted from genome-wide association study chips using a variety of software. We empirically evaluated and compared four freely-available software packages designed for Affymetrix SNP chips to estimate copy number: Affymetrix Power Tools (APT), Aroma.Affymetrix, PennCNV and CRLMM. Our evaluation used 1,418 GENOA samples that were genotyped on the Affymetrix Genome-Wide Human SNP Array 6.0. We compared bias and variance in the locus-level copy number data, the concordance amongst regions of copy number gains/deletions and the false-positive rate amongst deleted segments.'),
(94368, 2011, 'bmc', 'Faster Smith-Waterman database searches with inter-sequence SIMD parallelisation', 'Rognes, Torbjørn', 'Department of Informatics, University of Oslo, PO Box 1080 Blindern, NO-0316 Oslo, Norway. torognes@ifi.uio.no', 'Norway', 112, 'Algorithms|Amino Acid Sequence|Computers|Databases, Protein|Molecular Sequence Data|Programming Languages|Proteins|Sequence Alignment|Software', 'Journal Article', '10.1186/1471-2105-12-221', '21631914', 'The Smith-Waterman algorithm for local sequence alignment is more sensitive than heuristic methods for database searching, but also more time-consuming. The fastest approach to parallelisation with SIMD technology has previously been described by Farrar in 2007. The aim of this study was to explore whether further speed could be gained by other approaches to parallelisation.'),
(94369, 2011, 'bmc', 'Kernel density weighted loess normalization improves the performance of detection within asymmetrical data', 'Hsieh, Wen-Ping|Chu, Tzu-Ming|Lin, Yu-Min|Wolfinger, Russell D', 'Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan. wphsieh@stat.nthu.edu.tw|Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan. wphsieh@stat.nthu.edu.tw|Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan. wphsieh@stat.nthu.edu.tw|Institute of Statistics, National Tsing Hua University, Hsin-Chu City, 300, Taiwan. wphsieh@stat.nthu.edu.tw', '-|-|-|-', 5, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|ROC Curve|Regression Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-222', '21631915', 'Normalization of gene expression data has been studied for many years and various strategies have been formulated to deal with various types of data. Most normalization algorithms rely on the assumption that the number of up-regulated genes and the number of down-regulated genes are roughly the same. However, the well-known Golden Spike experiment presents a unique situation in which differentially regulated genes are biased toward one direction, thereby challenging the conclusions of previous bench mark studies.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94370, 2011, 'bmc', 'A network of SCOP hidden Markov models and its analysis', 'Zhang, Liqing|Watson, Layne T|Heath, Lenwood S', 'Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA. lqzhang@cs.vt.edu|Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA. lqzhang@cs.vt.edu|Department of Computer Science, Virginia Tech, Blacksburg, VA 24061, USA. lqzhang@cs.vt.edu', 'United States|United States|United States', 1, 'Databases, Protein|Evolution, Molecular|Markov Chains|Multigene Family|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1186/1471-2105-12-191', '21635719', 'The Structural Classification of Proteins (SCOP) database uses a large number of hidden Markov models (HMMs) to represent families and superfamilies composed of proteins that presumably share the same evolutionary origin. However, how the HMMs are related to one another has not been examined before.'),
(94371, 2011, 'bmc', 'Exploiting MeSH indexing in MEDLINE to generate a data set for word sense disambiguation', 'Jimeno-Yepes, Antonio J|McInnes, Bridget T|Aronson, Alan R', 'National Library of Medicine, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com|National Library of Medicine, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com|National Library of Medicine, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com', 'United States|United States|United States', 52, 'Abstracting and Indexing as Topic|Algorithms|Humans|Knowledge Bases|MEDLINE|Medical Subject Headings|Natural Language Processing|Semantics|Unified Medical Language System|United States', 'Journal Article', '10.1186/1471-2105-12-223', '21635749', 'Evaluation of Word Sense Disambiguation (WSD) methods in the biomedical domain is difficult because the available resources are either too small or too focused on specific types of entities (e.g. diseases or genes). We present a method that can be used to automatically develop a WSD test collection using the Unified Medical Language System (UMLS) Metathesaurus and the manual MeSH indexing of MEDLINE. We demonstrate the use of this method by developing such a data set, called MSH WSD.'),
(94372, 2011, 'bmc', 'Using affinity propagation for identifying subspecies among clonal organisms: lessons from M tuberculosis', 'Borile, Claudio|Labarre, Mathieu|Franz, Silvio|Sola, Christophe|Refrégier, Guislaine', 'LPTMS, CNRS and Univ. Paris-Sud, UMR8626, Bat. 100, 91405 Orsay, France.|LPTMS, CNRS and Univ. Paris-Sud, UMR8626, Bat. 100, 91405 Orsay, France.|LPTMS, CNRS and Univ. Paris-Sud, UMR8626, Bat. 100, 91405 Orsay, France.|LPTMS, CNRS and Univ. Paris-Sud, UMR8626, Bat. 100, 91405 Orsay, France.|LPTMS, CNRS and Univ. Paris-Sud, UMR8626, Bat. 100, 91405 Orsay, France.', 'France|France|France|France|France', 17, 'Cells, Cultured|Evolution, Molecular|Humans|Inverted Repeat Sequences|Mycobacterium tuberculosis|Tuberculosis', 'Journal Article', '10.1186/1471-2105-12-224', '21635750', 'Classification and naming is a key step in the analysis, understanding and adequate management of living organisms. However, where to set limits between groups can be puzzling especially in clonal organisms. Within the Mycobacterium tuberculosis complex (MTC), the etiological agent of tuberculosis (TB), experts have first identified several groups according to their pattern at repetitive sequences, especially at the CRISPR locus (spoligotyping), and to their epidemiological relevance. Most groups such as Beijing found good support when tested with other loci. However, other groups such as T family and T1 subfamily (belonging to the Euro-American lineage) correspond to non-monophyletic groups and still need to be refined. Here, we propose to use a method called Affinity Propagation that has been successfully used in image categorization to identify relevant patterns at the CRISPR locus in MTC.'),
(94373, 2011, 'bmc', 'Binding site prediction for protein-protein interactions and novel motif discovery using re-occurring polypeptide sequences', 'Amos-Binks, Adam|Patulea, Catalin|Pitre, Sylvain|Schoenrock, Andrew|Gui, Yuan|Green, James R|Golshani, Ashkan|Dehne, Frank', 'School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.|School of Computer Science, Carleton University, Ottawa, ON K1S5B6, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 12, 'Algorithms|Amino Acid Motifs|Humans|Protein Binding|Protein Interaction Domains and Motifs|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-225', '21635751', 'While there are many methods for predicting protein-protein interaction, very few can determine the specific site of interaction on each protein. Characterization of the specific sequence regions mediating interaction (binding sites) is crucial for an understanding of cellular pathways. Experimental methods often report false binding sites due to experimental limitations, while computational methods tend to require data which is not available at the proteome-scale. Here we present PIPE-Sites, a novel method of protein specific binding site prediction based on pairs of re-occurring polypeptide sequences, which have been previously shown to accurately predict protein-protein interactions. PIPE-Sites operates at high specificity and requires only the sequences of query proteins and a database of known binary interactions with no binding site data, making it applicable to binding site prediction at the proteome-scale.'),
(94374, 2011, 'bmc', 'StralSV: assessment of sequence variability within similar 3D structures and application to polio RNA-dependent RNA polymerase', 'Zemla, Adam T|Lang, Dorothy M|Kostova, Tanya|Andino, Raul|Ecale Zhou, Carol L', 'Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. zemla1@llnl.gov|Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. zemla1@llnl.gov|Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. zemla1@llnl.gov|Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. zemla1@llnl.gov|Global Security Computing Applications Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA. zemla1@llnl.gov', 'United States|United States|United States|United States|United States', 9, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|DNA Primers|Models, Molecular|Molecular Sequence Data|Poliovirus|RNA Replicase|Structural Homology, Protein', 'Journal Article', '10.1186/1471-2105-12-226', '21635786', 'Most of the currently used methods for protein function prediction rely on sequence-based comparisons between a query protein and those for which a functional annotation is provided. A serious limitation of sequence similarity-based approaches for identifying residue conservation among proteins is the low confidence in assigning residue-residue correspondences among proteins when the level of sequence identity between the compared proteins is poor. Multiple sequence alignment methods are more satisfactory--still, they cannot provide reliable results at low levels of sequence identity. Our goal in the current work was to develop an algorithm that could help overcome these difficulties by facilitating the identification of structurally (and possibly functionally) relevant residue-residue correspondences between compared protein structures.'),
(94375, 2011, 'bmc', 'Evaluating methods for ranking differentially expressed genes applied to microArray quality control data', 'Kadota, Koji|Shimizu, Kentaro', 'Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi, Bunkyo-ku, Japan. kadota@bi.a.u-tokyo.ac.jp|Agricultural Bioinformatics Research Unit, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Yayoi, Bunkyo-ku, Japan. kadota@bi.a.u-tokyo.ac.jp', 'Japan|Japan', 23, 'Biometry|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Quality Control|Research Design|Sensitivity and Specificity', 'Evaluation Studies', '10.1186/1471-2105-12-227', '21639945', 'Statistical methods for ranking differentially expressed genes (DEGs) from gene expression data should be evaluated with regard to high sensitivity, specificity, and reproducibility. In our previous studies, we evaluated eight gene ranking methods applied to only Affymetrix GeneChip data. A more general evaluation that also includes other microarray platforms, such as the Agilent or Illumina systems, is desirable for determining which methods are suitable for each platform and which method has better inter-platform reproducibility.'),
(94376, 2011, 'bmc', 'Proportion statistics to detect differentially expressed genes: a comparison with log-ratio statistics', 'Bergemann, Tracy L|Wilson, Jason', 'Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. tracy.l.bergemann@medtronic.com|Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA. tracy.l.bergemann@medtronic.com', 'United States|United States', 0, 'Animals|Apolipoprotein A-I|Cells, Cultured|Gene Expression Profiling|Humans|Kidney|Liver|Mice|Oligonucleotide Array Sequence Analysis|Reverse Transcriptase Polymerase Chain Reaction|Sequence Analysis, RNA', 'Journal Article', '10.1186/1471-2105-12-228', '21649912', 'In genetic transcription research, gene expression is typically reported in a test sample relative to a reference sample. Laboratory assays that measure gene expression levels, from Q-RT-PCR to microarrays to RNA-Seq experiments, will compare two samples to the same genetic sequence of interest. Standard practice is to use the log(2)-ratio as the measure of relative expression. There are drawbacks to using this measurement, including unstable ratios when the denominator is small. This paper suggests an alternative estimate based on a proportion that is just as simple to calculate, just as intuitive, with the added benefit of greater numerical stability.'),
(94377, 2010, 'bmc', 'Proceedings of the 21st International Conference on Genome Informatics, December 16-18, 2010, Hangzhou, China', '-', '-', '-', 17, 'Animals|Computational Biology|Genomics|Humans', 'Congress', '10.1186/1471-2105-12-228', '21649957', '-'),
(94378, 2011, 'bmc', 'Towards an Age-Phenome Knowledge-base', 'Geifman, Nophar|Rubin, Eitan', 'Shraga Segal Department of Microbiology and Immunology, The National Institute for Biotechnology in the Negev, Ben Gurion University, Israel.|Shraga Segal Department of Microbiology and Immunology, The National Institute for Biotechnology in the Negev, Ben Gurion University, Israel.', 'Israel|Israel', 8, 'Age Factors|Data Mining|Humans|Knowledge|Phenotype', 'Journal Article', '10.1186/1471-2105-12-229', '21651792', 'Currently, data about age-phenotype associations are not systematically organized and cannot be studied methodically. Searching for scientific articles describing phenotypic changes reported as occurring at a given age is not possible for most ages.'),
(94379, 2011, 'bmc', 'NeurphologyJ: an automatic neuronal morphology quantification method and its application in pharmacological discovery', 'Ho, Shinn-Ying|Chao, Chih-Yuan|Huang, Hui-Ling|Chiu, Tzai-Wen|Charoenkwan, Phasit|Hwang, Eric', 'Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, Taiwan.', '-|-|-|-|-|-', 65, 'Animals|Image Processing, Computer-Assisted|Mice|Microscopy, Fluorescence|Neurites|Neurons|Nocodazole|Software|Tubulin Modulators', 'Journal Article', '10.1186/1471-2105-12-230', '21651810', 'Automatic quantification of neuronal morphology from images of fluorescence microscopy plays an increasingly important role in high-content screenings. However, there exist very few freeware tools and methods which provide automatic neuronal morphology quantification for pharmacological discovery.'),
(94380, 2011, 'bmc', 'Topics in machine learning for biomedical literature analysis and text retrieval', 'Islamaj Doxc4x9fan, Rezarta|Yeganova, Lana', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Information Storage and Retrieval|Natural Language Processing', 'Introductory Journal Article', '10.1186/1471-2105-12-S3-I1', '21658287', '-'),
(94381, 2011, 'bmc', 'Building a biomedical tokenizer using the token lattice design pattern and the adapted Viterbi algorithm', 'Barrett, Neil|Weber-Jahnke, Jens', 'Department of Computer Science, University of Victoria, Victoria, Canada. nbarrett@uvic.ca|Department of Computer Science, University of Victoria, Victoria, Canada. nbarrett@uvic.ca', 'Canada|Canada', 12, 'Algorithms|Information Storage and Retrieval|Natural Language Processing', 'Journal Article', '10.1186/1471-2105-12-S3-S1', '21658288', 'Tokenization is an important component of language processing yet there is no widely accepted tokenization method for English texts, including biomedical texts. Other than rule based techniques, tokenization in the biomedical domain has been regarded as a classification task. Biomedical classifier-based tokenizers either split or join textual objects through classification to form tokens. The idiosyncratic nature of each biomedical tokenizers output complicates adoption and reuse. Furthermore, biomedical tokenizers generally lack guidance on how to apply an existing tokenizer to a new domain (subdomain). We identify and complete a novel tokenizer design pattern and suggest a systematic approach to tokenizer creation. We implement a tokenizer based on our design pattern that combines regular expressions and machine learning. Our machine learning approach differs from the previous split-join classification approaches. We evaluate our approach against three other tokenizers on the task of tokenizing biomedical text.'),
(94382, 2011, 'bmc', 'A system for de-identifying medical message board text', 'Benton, Adrian|Hill, Shawndra|Ungar, Lyle|Chung, Annie|Leonard, Charles|Freeman, Cristin|Holmes, John H', 'University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.|University of Pennsylvania School of Medicine, Philadelphia, PA, USA. adrianb@mail.med.upenn.edu.', 'United States|United States|United States|United States|United States|United States|United States', 16, 'Artificial Intelligence|Confidentiality|Humans|Internet|Names|Semantics|Social Support|Software', 'Journal Article', '10.1186/1471-2105-12-S3-S2', '21658289', 'There are millions of public posts to medical message boards by users seeking support and information on a wide range of medical conditions. It has been shown that these posts can be used to gain a greater understanding of patients experiences and concerns. As investigators continue to explore large corpora of medical discussion board data for research purposes, protecting the privacy of the members of these online communities becomes an important challenge that needs to be met. Extant entity recognition methods used for more structured text are not sufficient because message posts present additional challenges: the posts contain many typographical errors, larger variety of possible names, terms and abbreviations specific to Internet posts or a particular message board, and mentions of the authors personal lives. The main contribution of this paper is a system to de-identify the authors of message board posts automatically, taking into account the aforementioned challenges. We demonstrate our system on two different message board corpora, one on breast cancer and another on arthritis. We show that our approach significantly outperforms other publicly available named entity recognition and de-identification systems, which have been tuned for more structured text like operative reports, pathology reports, discharge summaries, or newswire.'),
(94383, 2011, 'bmc', 'A context-blocks model for identifying clinical relationships in patient records', 'Islamaj Doxc4x9fan, Rezarta|Nxc3xa9vxc3xa9ol, Aurxc3xa9lie|Lu, Zhiyong', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA. Rezarta.Islamaj@nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA. Rezarta.Islamaj@nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA. Rezarta.Islamaj@nih.gov', 'United States|United States|United States', 11, 'Humans|Medical Records Systems, Computerized|Medical Records, Problem-Oriented|Models, Statistical|Natural Language Processing', 'Journal Article', '10.1186/1471-2105-12-S3-S3', '21658290', 'Patient records contain valuable information regarding explanation of diagnosis, progression of disease, prescription and/or effectiveness of treatment, and more. Automatic recognition of clinically important concepts and the identification of relationships between those concepts in patient records are preliminary steps for many important applications in medical informatics, ranging from quality of care to hypothesis generation.'),
(94384, 2011, 'bmc', 'Collocation analysis for UMLS knowledge-based word sense disambiguation', 'Jimeno-Yepes, Antonio|McInnes, Bridget T|Aronson, Alan R', 'National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com|National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com|National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. antonio.jimeno@gmail.com', 'United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Knowledge Bases|MEDLINE|Medical Informatics|Medical Subject Headings|Natural Language Processing|Semantics|Terminology as Topic|Unified Medical Language System', 'Journal Article', '10.1186/1471-2105-12-S3-S4', '21658291', 'The effectiveness of knowledge-based word sense disambiguation (WSD) approaches depends in part on the information available in the reference knowledge resource. Off the shelf, these resources are not optimized for WSD and might lack terms to model the context properly. In addition, they might include noisy terms which contribute to false positives in the disambiguation results.'),
(94385, 2011, 'bmc', 'Improving a gold standard: treating human relevance judgments of MEDLINE document pairs', 'Wilbur, W John|Kim, Won', 'National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA. wilbur@ncbi.nlm.nih.gov|National Center for Biotechnology Information, National Library of Medicine, National Institute of Health, Bethesda, MD 20894, USA. wilbur@ncbi.nlm.nih.gov', 'United States|United States', 0, 'Humans|Judgment|Likelihood Functions|MEDLINE|Research Design', 'Comparative Study', '10.1186/1471-2105-12-S3-S5', '21658292', 'Given prior human judgments of the condition of an object it is possible to use these judgments to make a maximal likelihood estimate of what future human judgments of the condition of that object will be. However, if one has a reasonably large collection of similar objects and the prior human judgments of a number of judges regarding the condition of each object in the collection, then it is possible to make predictions of future human judgments for the whole collection that are superior to the simple maximal likelihood estimate for each object in isolation. This is possible because the multiple judgments over the collection allow an analysis to determine the relative value of a judge as compared with the other judges in the group and this value can be used to augment or diminish a particular judges influence in predicting future judgments. Here we study and compare five different methods for making such improved predictions and show that each is superior to simple maximal likelihood estimates.'),
(94386, 2011, 'bmc', 'Machine learning with naturally labeled data for identifying abbreviation definitions', 'Yeganova, Lana|Comeau, Donald C|Wilbur, W John', 'National Center for Biotechnology Information, NLM, NIH, Bethesda, MD, USA. yeganova@mail.nih.gov|National Center for Biotechnology Information, NLM, NIH, Bethesda, MD, USA. yeganova@mail.nih.gov|National Center for Biotechnology Information, NLM, NIH, Bethesda, MD, USA. yeganova@mail.nih.gov', 'United States|United States|United States', 7, 'Abbreviations as Topic|Algorithms|Artificial Intelligence|Information Storage and Retrieval|Pattern Recognition, Automated', 'Journal Article', '10.1186/1471-2105-12-S3-S6', '21658293', 'The rapid growth of biomedical literature requires accurate text analysis and text processing tools. Detecting abbreviations and identifying their definitions is an important component of such tools. Most existing approaches for the abbreviation definition identification task employ rule-based methods. While achieving high precision, rule-based methods are limited to the rules defined and fail to capture many uncommon definition patterns. Supervised learning techniques, which offer more flexibility in detecting abbreviation definitions, have also been applied to the problem. However, they require manually labeled training data.'),
(94387, 2011, 'bmc', 'A structural SVM approach for reference parsing', 'Zhang, Xiaoli|Zou, Jie|Le, Daniel X|Thoma, George R', 'Lister Hill National Center for Biomedical Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. zhangxiaol@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. zhangxiaol@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. zhangxiaol@mail.nih.gov|Lister Hill National Center for Biomedical Communications, National Library of Medicine, 8600 Rockville Pike, Bethesda, MD 20894, USA. zhangxiaol@mail.nih.gov', 'United States|United States|United States|United States', 8, 'Algorithms|Artificial Intelligence|Databases, Bibliographic|Information Storage and Retrieval|Software', 'Comparative Study', '10.1186/1471-2105-12-S3-S7', '21658294', 'Automated extraction of bibliographic data, such as article titles, author names, abstracts, and references is essential to the affordable creation of large citation databases. References, typically appearing at the end of journal articles, can also provide valuable information for extracting other bibliographic data. Therefore, parsing individual reference to extract author, title, journal, year, etc. is sometimes a necessary preprocessing step in building citation-indexing systems. The regular structure in references enables us to consider reference parsing a sequence learning problem and to study structural Support Vector Machine (structural SVM), a newly developed structured learning algorithm on parsing references.'),
(94388, 2011, 'bmc', 'Estimation of allele frequency and association mapping using next-generation sequencing data', 'Kim, Su Yeon|Lohmueller, Kirk E|Albrechtsen, Anders|Li, Yingrui|Korneliussen, Thorfinn|Tian, Geng|Grarup, Niels|Jiang, Tao|Andersen, Gitte|Witte, Daniel|Jorgensen, Torben|Hansen, Torben|Pedersen, Oluf|Wang, Jun|Nielsen, Rasmus', 'Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.edu|Departments of Integrative Biology and Statistics, UC Berkeley, Berkeley, CA 94720, USA. suyeonkim@berkeley.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', 97, 'Gene Frequency|Genetics, Population|Genotype|High-Throughput Nucleotide Sequencing|Humans|Likelihood Functions|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1186/1471-2105-12-231', '21663684', 'Estimation of allele frequency is of fundamental importance in population genetic analyses and in association mapping. In most studies using next-generation sequencing, a cost effective approach is to use medium or low-coverage data (e.g., < 15X). However, SNP calling and allele frequency estimation in such studies is associated with substantial statistical uncertainty because of varying coverage and high error rates.'),
(94389, 2011, 'bmc', 'Gebiss: an ImageJ plugin for the specification of ground truth and the performance evaluation of 3D segmentation algorithms', 'Kriston-Vizi, Janos|Thong, Ng Wee|Poh, Cheok Leong|Yee, Kwo Chia|Ling, Joan Sim Poh|Kraut, Rachel|Wasser, Martin', 'Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk|Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), 138671, Singapore. dmcbjkr@ucl.ac.uk', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 3, 'Algorithms|Animals|Brain|Drosophila melanogaster|Imaging, Three-Dimensional|Software', 'Journal Article', '10.1186/1471-2105-12-232', '21668958', 'Image segmentation is a crucial step in quantitative microscopy that helps to define regions of tissues, cells or subcellular compartments. Depending on the degree of user interactions, segmentation methods can be divided into manual, automated or semi-automated approaches. 3D image stacks usually require automated methods due to their large number of optical sections. However, certain applications benefit from manual or semi-automated approaches. Scenarios include the quantification of 3D images with poor signal-to-noise ratios or the generation of so-called ground truth segmentations that are used to evaluate the accuracy of automated segmentation methods.'),
(94390, 2011, 'bmc', 'Reconstructing genome-wide regulatory network of E coli using transcriptome data and predicted transcription factor activities', 'Fu, Yao|Jarboe, Laura R|Dickerson, Julie A', 'Bioinformatics and Computational Biology Program, Iowa State University, Ames, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, USA.|Bioinformatics and Computational Biology Program, Iowa State University, Ames, USA.', 'United States|United States|United States', 0, 'Algorithms|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Regulatory Networks|Genome, Bacterial|Transcription Factors', 'Journal Article', '10.1186/1471-2105-12-233', '21668997', 'Gene regulatory networks play essential roles in living organisms to control growth, keep internal metabolism running and respond to external environmental changes. Understanding the connections and the activity levels of regulators is important for the research of gene regulatory networks. While relevance score based algorithms that reconstruct gene regulatory networks from transcriptome data can infer genome-wide gene regulatory networks, they are unfortunately prone to false positive results. Transcription factor activities (TFAs) quantitatively reflect the ability of the transcription factor to regulate target genes. However, classic relevance score based gene regulatory network reconstruction algorithms use models do not include the TFA layer, thus missing a key regulatory element.'),
(94391, 2011, 'bmc', 'Efficient alignment of pyrosequencing reads for re-sequencing applications', 'Fernandes, Francisco|da Fonseca, Paulo G S|Russo, Luis M S|Oliveira, Arlindo L|Freitas, Ana T', 'Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento, R. Alves Redol 9, 1000-029 Lisboa, Portugal.|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento, R. Alves Redol 9, 1000-029 Lisboa, Portugal.|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento, R. Alves Redol 9, 1000-029 Lisboa, Portugal.|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento, R. Alves Redol 9, 1000-029 Lisboa, Portugal.|Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento, R. Alves Redol 9, 1000-029 Lisboa, Portugal.', 'Portugal|Portugal|Portugal|Portugal|Portugal', 0, 'Algorithms|Animals|Base Sequence|High-Throughput Nucleotide Sequencing|Humans|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-163', '21672185', 'Over the past few years, new massively parallel DNA sequencing technologies have emerged. These platforms generate massive amounts of data per run, greatly reducing the cost of DNA sequencing. However, these techniques also raise important computational difficulties mostly due to the huge volume of data produced, but also because of some of their specific characteristics such as read length and sequencing errors. Among the most critical problems is that of efficiently and accurately mapping reads to a reference genome in the context of re-sequencing projects.'),
(94392, 2011, 'bmc', 'PI: an open-source software package for validation of the SEQUEST result and visualization of mass spectrum', 'Qiao, Yantao|Zhang, Hong|Bu, Dongbo|Sun, Shiwei', 'Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.|Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.', 'China|China|China|China', 2, 'Algorithms|Peptides|Proteins|Proteomics|Software|Tandem Mass Spectrometry', 'Journal Article', '10.1186/1471-2105-12-234', '21672262', 'Tandem mass spectrometry (MS/MS) has emerged as the leading method for high- throughput protein identification in proteomics. Recent technological breakthroughs have dramatically increased the efficiency of MS/MS data generation. Meanwhile, sophisticated algorithms have been developed for identifying proteins from peptide MS/MS data by searching available protein sequence databases for the peptide that is most likely to have produced the observed spectrum. The popular SEQUEST algorithm relies on the cross-correlation between the experimental mass spectrum and the theoretical spectrum of a peptide. It utilizes a simplified fragmentation model that assigns a fixed and identical intensity for all major ions and fixed and lower intensity for their neutral losses. In this way, the common issues involved in predicting theoretical spectra are circumvented. In practice, however, an experimental spectrum is usually not similar to its SEQUEST -predicted theoretical one, and as a result, incorrect identifications are often generated.'),
(94393, 2011, 'bmc', 'Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography-mass spectrometry', 'Kim, Seongho|Koo, Imhoi|Fang, Aiqin|Zhang, Xiang', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA. s0kim023@louisville.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Animals|Gas Chromatography-Mass Spectrometry|Metabolomics|Mice|Plasma', 'Journal Article', '10.1186/1471-2105-12-235', '21676240', 'Comprehensive two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS) is a powerful technique which has gained increasing attention over the last two decades. The GC × GC-MS provides much increased separation capacity, chemical selectivity and sensitivity for complex sample analysis and brings more accurate information about compound retention times and mass spectra. Despite these advantages, the retention times of the resolved peaks on the two-dimensional gas chromatographic columns are always shifted due to experimental variations, introducing difficulty in the data processing for metabolomics analysis. Therefore, the retention time variation must be adjusted in order to compare multiple metabolic profiles obtained from different conditions.'),
(94394, 2011, 'bmc', 'FFCA: a feasibility-based method for flux coupling analysis of metabolic networks', 'David, Laszlo|Marashi, Sayed-Amir|Larhlimi, Abdelhalim|Mieth, Bettina|Bockmayr, Alexander', 'DFG-Research Center Matheon, Berlin, Germany.|DFG-Research Center Matheon, Berlin, Germany.|DFG-Research Center Matheon, Berlin, Germany.|DFG-Research Center Matheon, Berlin, Germany.|DFG-Research Center Matheon, Berlin, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Escherichia coli|Helicobacter pylori|Metabolic Networks and Pathways|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1186/1471-2105-12-236', '21676263', 'Flux coupling analysis (FCA) is a useful method for finding dependencies between fluxes of a metabolic network at steady-state. FCA classifies reactions into subsets (called coupled reaction sets) in which activity of one reaction implies activity of another reaction. Several approaches for FCA have been proposed in the literature.'),
(94395, 2011, 'bmc', 'Semi-automatic segmentation of multiple mouse embryos in MR images', 'Baghdadi, Leila|Zamyadi, Mojdeh|Sled, John G|Schneider, Jürgen E|Bhattacharya, Shuomo|Henkelman, R Mark|Lerch, Jason P', 'Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca|Mouse Imaging Centre, The Hospital for Sick Children, Toronto, Canada. baghdadi@phenogenomics.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Animals|Embryo, Mammalian|Imaging, Three-Dimensional|Magnetic Resonance Imaging|Mice|Software', 'Journal Article', '10.1186/1471-2105-12-237', '21679425', 'The motivation behind this paper is to aid the automatic phenotyping of mouse embryos, wherein multiple embryos embedded within a single tube were scanned using Magnetic Resonance Imaging (MRI).'),
(94396, 2011, 'bmc', 'MotifClick: prediction of cis-regulatory binding sites via merging cliques', 'Zhang, Shaoqiang|Li, Shan|Niu, Meng|Pham, Phuc T|Su, Zhengchang', 'Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 28223, USA.|Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 28223, USA.|Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 28223, USA.|Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 28223, USA.|Department of Bioinformatics and Genomics, Center for Bioinformatics Research, the University of North Carolina at Charlotte, 28223, USA.', 'United States|United States|United States|United States|United States', 7, 'Algorithms|Animals|Base Sequence|Binding Sites|DNA|Drosophila melanogaster|Escherichia coli|Saccharomyces cerevisiae|Transcription Factors', 'Journal Article', '10.1186/1471-2105-12-238', '21679436', 'Although dozens of algorithms and tools have been developed to find a set of cis-regulatory binding sites called a motif in a set of intergenic sequences using various approaches, most of these tools focus on identifying binding sites that are significantly different from their background sequences. However, some motifs may have a similar nucleotide distribution to that of their background sequences. Therefore, such binding sites can be missed by these tools.'),
(94397, 2011, 'bmc', 'Noise reduction in protein-protein interaction graphs by the implementation of a novel weighting scheme', 'Kritikos, George D|Moschopoulos, Charalampos|Vazirgiannis, Michalis|Kossida, Sophia', 'Bioinformatics & Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, Athens, Soranou Efesiou 4, GR-11527, Greece.|Bioinformatics & Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, Athens, Soranou Efesiou 4, GR-11527, Greece.|Bioinformatics & Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, Athens, Soranou Efesiou 4, GR-11527, Greece.|Bioinformatics & Medical Informatics Team, Biomedical Research Foundation of the Academy of Athens, Athens, Soranou Efesiou 4, GR-11527, Greece.', 'Greece|Greece|Greece|Greece', 0, 'Algorithms|Cluster Analysis|Databases, Protein|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-239', '21679454', 'Recent technological advances applied to biology such as yeast-two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of protein interaction networks. These interaction networks represent a rich, yet noisy, source of data that could be used to extract meaningful information, such as protein complexes. Several interaction network weighting schemes have been proposed so far in the literature in order to eliminate the noise inherent in interactome data. In this paper, we propose a novel weighting scheme and apply it to the S. cerevisiae interactome. Complex prediction rates are improved by up to 39%, depending on the clustering algorithm applied.'),
(94398, 2011, 'bmc', 'LAVA: an open-source approach to designing LAMP (loop-mediated isothermal amplification) DNA signatures', 'Torres, Clinton|Vitalis, Elizabeth A|Baker, Brian R|Gardner, Shea N|Torres, Marisa W|Dzenitis, John M', 'Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov|Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov|Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov|Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov|Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov|Lawrence Livermore National Laboratory, Livermore, California, USA. clinton.torres@llnl.gov', 'United States|United States|United States|United States|United States|United States', 30, 'Base Sequence|DNA Primers|Nucleic Acid Amplification Techniques|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-240', '21679460', 'We developed an extendable open-source Loop-mediated isothermal AMPlification (LAMP) signature design program called LAVA (LAMP Assay Versatile Analysis). LAVA was created in response to limitations of existing LAMP signature programs.'),
(94399, 2011, 'bmc', 'PeptX: using genetic algorithms to optimize peptides for MHC binding', 'Knapp, Bernhard|Giczi, Verena|Ribarics, Reiner|Schreiner, Wolfgang', 'Center for Medical Statistics, Informatics and Intelligent Systems, Department for Biosimulation and Bioinformatics, Medical University of Vienna, Austria. bernhard.knapp@meduniwien.ac.at|Center for Medical Statistics, Informatics and Intelligent Systems, Department for Biosimulation and Bioinformatics, Medical University of Vienna, Austria. bernhard.knapp@meduniwien.ac.at|Center for Medical Statistics, Informatics and Intelligent Systems, Department for Biosimulation and Bioinformatics, Medical University of Vienna, Austria. bernhard.knapp@meduniwien.ac.at|Center for Medical Statistics, Informatics and Intelligent Systems, Department for Biosimulation and Bioinformatics, Medical University of Vienna, Austria. bernhard.knapp@meduniwien.ac.at', 'Austria|Austria|Austria|Austria', 0, 'Algorithms|Animals|Artificial Intelligence|Genes, MHC Class I|Humans|Major Histocompatibility Complex|Peptides|Protein Binding', 'Journal Article', '10.1186/1471-2105-12-241', '21679477', 'The binding between the major histocompatibility complex and the presented peptide is an indispensable prerequisite for the adaptive immune response. There is a plethora of different in silico techniques for the prediction of the peptide binding affinity to major histocompatibility complexes. Most studies screen a set of peptides for promising candidates to predict possible T cell epitopes. In this study we ask the question vice versa: Which peptides do have highest binding affinities to a given major histocompatibility complex according to certain in silico scoring functions?'),
(94400, 2011, 'bmc', 'Querying large read collections in main memory: a versatile data structure', 'Philippe, Nicolas|Salson, Mikaël|Lecroq, Thierry|Léonard, Martine|Commes, Thérèse|Rivals, Eric', 'LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.|LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.|LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.|LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.|LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.|LIRMM, UMR 5506, CNRS and Université de Montpellier 2, CC 477, 161 rue Ada, 34095 Montpellier, France.', 'France|France|France|France|France|France', 0, 'Algorithms|Computational Biology|Computers|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1186/1471-2105-12-242', '21682852', 'High Throughput Sequencing (HTS) is now heavily exploited for genome (re-) sequencing, metagenomics, epigenomics, and transcriptomics and requires different, but computer intensive bioinformatic analyses. When a reference genome is available, mapping reads on it is the first step of this analysis. Read mapping programs owe their efficiency to the use of involved genome indexing data structures, like the Burrows-Wheeler transform. Recent solutions index both the genome, and the k-mers of the reads using hash-tables to further increase efficiency and accuracy. In various contexts (e.g. assembly or transcriptome analysis), read processing requires to determine the sub-collection of reads that are related to a given sequence, which is done by searching for some k-mers in the reads. Currently, many developments have focused on genome indexing structures for read mapping, but the question of read indexing remains broadly unexplored. However, the increase in sequence throughput urges for new algorithmic solutions to query large read collections efficiently.'),
(94401, 2011, 'bmc', 'RegNetB: predicting relevant regulator-gene relationships in localized prostate tumor samples', 'Alvarez, Angel|Woolf, Peter J', 'Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.|Department of Chemical Engineering, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States', 0, 'Acid Phosphatase|Bayes Theorem|Carcinoma|DNA-Binding Proteins|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Homeodomain Proteins|Humans|Male|Paired Box Transcription Factors|Prostate|Prostatic Neoplasms|Protein Tyrosine Phosphatases|Transcription Factor TFIID|Transcription Factors', 'Journal Article', '10.1186/1471-2105-12-243', '21682879', 'A central question in cancer biology is what changes cause a healthy cell to form a tumor. Gene expression data could provide insight into this question, but it is difficult to distinguish between a gene that causes a change in gene expression from a gene that is affected by this change. Furthermore, the proteins that regulate gene expression are often themselves not regulated at the transcriptional level. Here we propose a Bayesian modeling framework we term RegNetB that uses mechanistic information about the gene regulatory network to distinguish between factors that cause a change in expression and genes that are affected by the change. We test this framework using human gene expression data describing localized prostate cancer progression.'),
(94402, 2011, 'bmc', 'HomPPI: a class of sequence homology based protein-protein interface prediction methods', 'Xue, Li C|Dobbs, Drena|Honavar, Vasant', 'Department of Computer Science, Iowa State University, Ames, IA 50011, USA. me.lixue@gmail.com|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. me.lixue@gmail.com|Department of Computer Science, Iowa State University, Ames, IA 50011, USA. me.lixue@gmail.com', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Humans|Proteins|Sequence Analysis, Protein|Sequence Homology|Software', 'Journal Article', '10.1186/1471-2105-12-244', '21682895', 'Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94403, 2011, 'bmc', 'In-silico prediction of disorder content using hybrid sequence representation', 'Mizianty, Marcin J|Zhang, Tuo|Xue, Bin|Zhou, Yaoqi|Dunker, A Keith|Uversky, Vladimir N|Kurgan, Lukasz', 'Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Alberta T6G 2V4, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 32, 'Amino Acid Sequence|Cell Physiological Phenomena|Humans|Protein Folding|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1186/1471-2105-12-245', '21682902', 'Intrinsically disordered proteins play important roles in various cellular activities and their prevalence was implicated in a number of human diseases. The knowledge of the content of the intrinsic disorder in proteins is useful for a variety of studies including estimation of the abundance of disorder in protein families, classes, and complete proteomes, and for the analysis of disorder-related protein functions. The above investigations currently utilize the disorder content derived from the per-residue disorder predictions. We show that these predictions may over-or under-predict the overall amount of disorder, which motivates development of novel tools for direct and accurate sequence-based prediction of the disorder content.'),
(94404, 2011, 'bmc', 'Enhancements to the ADMIXTURE algorithm for individual ancestry estimation', 'Alexander, David H|Lange, Kenneth', 'Department of Biomathematics, UCLA, Los Angeles, California, USA. dalexander@ucla.edu|Department of Biomathematics, UCLA, Los Angeles, California, USA. dalexander@ucla.edu', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Gene Frequency|Genetics, Population|Genome, Human|Humans|Likelihood Functions|Polymorphism, Single Nucleotide|Population Groups|Software', 'Journal Article', '10.1186/1471-2105-12-246', '21682921', 'The estimation of individual ancestry from genetic data has become essential to applied population genetics and genetic epidemiology. Software programs for calculating ancestry estimates have become essential tools in the geneticists analytic arsenal.'),
(94405, 2011, 'bmc', 'MLPAstats: an R GUI package for the integrated analysis of copy number alterations using MLPA data', 'Cáceres, Alejandro|Armengol, Lluís|Villatoro, Sergi|González, Juan R', 'Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. acaceres@creal.cat|Center for Research in Environmental Epidemiology, Doctor Aiguader 88, Barcelona 08003, Spain. acaceres@creal.cat', 'Spain|Spain|Spain|Spain', 0, 'Breast Neoplasms|DNA Copy Number Variations|Humans|Nucleic Acid Amplification Techniques|Software', 'Journal Article', '10.1186/1471-2105-12-147', '21682923', 'Multiplex-Dependent Probe Amplification (MLPA) is a cost-effective experimental method for candidate gene studies, aimed at the identification of copy number alterations. The analysis of such genetic variants, from electropherogram peak intensities, involves two main stages. First, peak normalization for each probe is required to remove the contribution of probe size to peak intensity. Second, the statistical significance of peak alteration between case and control samples is estimated. A number of methods have been proposed in each step with varying levels of complexity and precision. However, there is no single framework from which the results of each method and possible combinations at each step can be assessed.'),
(94406, 2011, 'bmc', 'Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs', 'Regad, Leslie|Martin, Juliette|Camproux, Anne-Claude', 'INSERM, U973, Paris F-75013, France.|INSERM, U973, Paris F-75013, France.|INSERM, U973, Paris F-75013, France.', 'France|France|France', 0, 'Amino Acid Motifs|Databases, Protein|Ligands|Markov Chains|Models, Molecular|Molecular Sequence Annotation|Protein Binding|Protein Structure, Secondary|Proteins', 'Journal Article', '10.1186/1471-2105-12-247', '21689388', 'One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function.'),
(94407, 2011, 'bmc', 'PhyloMap: an algorithm for visualizing relationships of large sequence data sets and its application to the influenza A virus genome', 'Zhang, Jiajie|Mamlouk, Amir Madany|Martinetz, Thomas|Chang, Suhua|Wang, Jing|Hilgenfeld, Rolf', 'Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.|Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.|Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.|Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.|Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.|Institute of Biochemistry, Center for Structural and Cell Biology in Medicine, University of Lübeck, Ratzeburger Allee 160, 23538 Lübeck, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Genome, Viral|Influenza A virus|Phylogeny', 'Journal Article', '10.1186/1471-2105-12-248', '21689434', 'Results of phylogenetic analysis are often visualized as phylogenetic trees. Such a tree can typically only include up to a few hundred sequences. When more than a few thousand sequences are to be included, analyzing the phylogenetic relationships among them becomes a challenging task. The recent frequent outbreaks of influenza A viruses have resulted in the rapid accumulation of corresponding genome sequences. Currently, there are more than 7500 influenza A virus genomes in the database. There are no efficient ways of representing this huge data set as a whole, thus preventing a further understanding of the diversity of the influenza A virus genome.'),
(94408, 2011, 'bmc', 'Deregulation upon DNA damage revealed by joint analysis of context-specific perturbation data', 'Szczurek, Ewa|Markowetz, Florian|Gat-Viks, Irit|Biecek, Przemysxc5x82aw|Tiuryn, Jerzy|Vingron, Martin', 'Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de|Computational Molecular Biology Department, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. szczurek@molgen.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 1, 'DNA Damage|DNA Repair|Disease|Gene Expression Profiling|Gene Expression Regulation|Humans|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-12-249', '21693013', 'Deregulation between two different cell populations manifests itself in changing gene expression patterns and changing regulatory interactions. Accumulating knowledge about biological networks creates an opportunity to study these changes in their cellular context.'),
(94409, 2011, 'bmc', 'NORMA-Gene: a simple and robust method for qPCR normalization based on target gene data', 'Heckmann, Lars-Henrik|Sørensen, Peter B|Krogh, Paul Henning|Sørensen, Jesper G', 'National Environmental Research Institute, Aarhus University, Department of Terrestrial Ecology, Vejlsøvej 25, DK-8600 Silkeborg, Denmark.|National Environmental Research Institute, Aarhus University, Department of Terrestrial Ecology, Vejlsøvej 25, DK-8600 Silkeborg, Denmark.|National Environmental Research Institute, Aarhus University, Department of Terrestrial Ecology, Vejlsøvej 25, DK-8600 Silkeborg, Denmark.|National Environmental Research Institute, Aarhus University, Department of Terrestrial Ecology, Vejlsøvej 25, DK-8600 Silkeborg, Denmark.', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Gene Expression|Gene Expression Profiling|Polymerase Chain Reaction', 'Journal Article', '10.1186/1471-2105-12-250', '21693017', 'Normalization of target gene expression, measured by real-time quantitative PCR (qPCR), is a requirement for reducing experimental bias and thereby improving data quality. The currently used normalization approach is based on using one or more reference genes. Yet, this approach extends the experimental work load and suffers from assumptions that may be difficult to meet and to validate.'),
(94410, 2011, 'bmc', 'Determinants of antigenicity and specificity in immune response for protein sequences', 'Wang, Yulong|Wu, Wenjun|Negre, Nicolas N|White, Kevin P|Li, Cheng|Shah, Parantu K', 'Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com|Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute & Harvard School of Public Health, Boston 02115 MA, USA. parantu.shah@gmail.com', 'United States|United States|United States|United States|United States|United States', 0, 'Animals|Antigens|Artificial Intelligence|Drosophila melanogaster|Epitopes, B-Lymphocyte|Humans', 'Journal Article', '10.1186/1471-2105-12-251', '21693021', 'Target specific antibodies are pivotal for the design of vaccines, immunodiagnostic tests, studies on proteomics for cancer biomarker discovery, identification of protein-DNA and other interactions, and small and large biochemical assays. Therefore, it is important to understand the properties of protein sequences that are important for antigenicity and to identify small peptide epitopes and large regions in the linear sequence of the proteins whose utilization result in specific antibodies.'),
(94411, 2011, 'bmc', 'Computational study of noise in a large signal transduction network', 'Intosalmi, Jukka|Manninen, Tiina|Ruohonen, Keijo|Linne, Marja-Leena', 'Department of Mathematics, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. jukka.intosalmi@tut.fi|Department of Mathematics, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. jukka.intosalmi@tut.fi|Department of Mathematics, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. jukka.intosalmi@tut.fi|Department of Mathematics, Tampere University of Technology, P.O. Box 553, 33101 Tampere, Finland. jukka.intosalmi@tut.fi', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Computer Simulation|Models, Biological|Monte Carlo Method|Protein Kinases|Signal Transduction', 'Journal Article', '10.1186/1471-2105-12-252', '21693049', 'Biochemical systems are inherently noisy due to the discrete reaction events that occur in a random manner. Although noise is often perceived as a disturbing factor, the system might actually benefit from it. In order to understand the role of noise better, its quality must be studied in a quantitative manner. Computational analysis and modeling play an essential role in this demanding endeavor.'),
(94412, 2011, 'bmc', 'Sparse PLS discriminant analysis: biologically relevant feature selection and graphical displays for multiclass problems', 'Lê Cao, Kim-Anh|Boitard, Simon|Besse, Philippe', 'Queensland Facility for Advanced Bioinformatics, University of Queensland, 4072 St Lucia, QLD, Australia. k.lecao@uq.edu.au|Queensland Facility for Advanced Bioinformatics, University of Queensland, 4072 St Lucia, QLD, Australia. k.lecao@uq.edu.au|Queensland Facility for Advanced Bioinformatics, University of Queensland, 4072 St Lucia, QLD, Australia. k.lecao@uq.edu.au', 'Australia|Australia|Australia', 282, 'Artificial Intelligence|Discriminant Analysis|Gene Expression Profiling|Humans|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-12-253', '21693065', 'Variable selection on high throughput biological data, such as gene expression or single nucleotide polymorphisms (SNPs), becomes inevitable to select relevant information and, therefore, to better characterize diseases or assess genetic structure. There are different ways to perform variable selection in large data sets. Statistical tests are commonly used to identify differentially expressed features for explanatory purposes, whereas Machine Learning wrapper approaches can be used for predictive purposes. In the case of multiple highly correlated variables, another option is to use multivariate exploratory approaches to give more insight into cell biology, biological pathways or complex traits.'),
(94413, 2011, 'bmc', 'Fusion of metabolomics and proteomics data for biomarkers discovery: case study on the experimental autoimmune encephalomyelitis', 'Blanchet, Lionel|Smolinska, Agnieszka|Attali, Amos|Stoop, Marcel P|Ampt, Kirsten A M|van Aken, Hans|Suidgeest, Ernst|Tuinstra, Tinka|Wijmenga, Sybren S|Luider, Theo|Buydens, Lutgarde M C', 'Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl|Radboud University Nijmegen, Institute for Molecules and Materials, Heyendaalseweg, The Netherlands. l.blanchet@science.ru.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 49, 'Animals|Biomarkers|Cerebrospinal Fluid|Encephalomyelitis, Autoimmune, Experimental|Male|Metabolomics|Nuclear Magnetic Resonance, Biomolecular|Proteomics|Rats|Rats, Inbred Lew', 'Journal Article', '10.1186/1471-2105-12-254', '21696593', 'Analysis of Cerebrospinal Fluid (CSF) samples holds great promise to diagnose neurological pathologies and gain insight into the molecular background of these pathologies. Proteomics and metabolomics methods provide invaluable information on the biomolecular content of CSF and thereby on the possible status of the central nervous system, including neurological pathologies. The combined information provides a more complete description of CSF content. Extracting the full combined information requires a combined analysis of different datasets i.e. fusion of the data.'),
(94414, 2011, 'bmc', 'Study of large and highly stratified population datasets by combining iterative pruning principal component analysis and structure', 'Limpiti, Tulaya|Intarapanich, Apichart|Assawamakin, Anunchai|Shaw, Philip J|Wangkumhang, Pongsakorn|Piriyapongsa, Jittima|Ngamphiw, Chumpol|Tongsima, Sissades', 'Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.|Faculty of Engineering, King Mongkuts Institute of Technology Ladkrabang, Bangkok, Thailand.', 'Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand', 0, 'Algorithms|Animals|Artificial Intelligence|Cattle|Genetics, Population|Genome, Human|Haplotypes|Humans|Population Groups|Principal Component Analysis', 'Journal Article', '10.1186/1471-2105-12-255', '21699684', 'The ever increasing sizes of population genetic datasets pose great challenges for population structure analysis. The Tracy-Widom (TW) statistical test is widely used for detecting structure. However, it has not been adequately investigated whether the TW statistic is susceptible to type I error, especially in large, complex datasets. Non-parametric, Principal Component Analysis (PCA) based methods for resolving structure have been developed which rely on the TW test. Although PCA-based methods can resolve structure, they cannot infer ancestry. Model-based methods are still needed for ancestry analysis, but they are not suitable for large datasets. We propose a new structure analysis framework for large datasets. This includes a new heuristic for detecting structure and incorporation of the structure patterns inferred by a PCA method to complement STRUCTURE analysis.'),
(94415, 2011, 'bmc', 'Semantic inference using chemogenomics data for drug discovery', 'Zhu, Qian|Sun, Yuyin|Challa, Sashikiran|Ding, Ying|Lajiness, Michael S|Wild, David J', 'School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu|School of Informatics and Computing, Indiana University, Bloomington, USA. qianzhu@indiana.edu', 'India|India|India|India|India|India', 0, 'Algorithms|Drug Design|Drug Discovery|Drug Therapy|Humans|Pharmacogenetics|Semantics', 'Journal Article', '10.1186/1471-2105-12-256', '21699718', 'Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network) based on semantically marked-up versions of these evidence paths, rule-sets and inference engines.'),
(94416, 2011, 'bmc', 'BioAssay Ontology (BAO): a semantic description of bioassays and high-throughput screening results', 'Visser, Ubbo|Abeyruwan, Saminda|Vempati, Uma|Smith, Robin P|Lemmon, Vance|Schürer, Stephan C', 'Department of Computer Science, University of Miami, Coral Gables, FL, USA.|Department of Computer Science, University of Miami, Coral Gables, FL, USA.|Department of Computer Science, University of Miami, Coral Gables, FL, USA.|Department of Computer Science, University of Miami, Coral Gables, FL, USA.|Department of Computer Science, University of Miami, Coral Gables, FL, USA.|Department of Computer Science, University of Miami, Coral Gables, FL, USA.', 'United States|United States|United States|United States|United States|United States', 78, 'Biological Assay|Databases, Factual|High-Throughput Screening Assays|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-12-257', '21702939', 'High-throughput screening (HTS) is one of the main strategies to identify novel entry points for the development of small molecule chemical probes and drugs and is now commonly accessible to public sector research. Large amounts of data generated in HTS campaigns are submitted to public repositories such as PubChem, which is growing at an exponential rate. The diversity and quantity of available HTS assays and screening results pose enormous challenges to organizing, standardizing, integrating, and analyzing the datasets and thus to maximize the scientific and ultimately the public health impact of the huge investments made to implement public sector HTS capabilities. Novel approaches to organize, standardize and access HTS data are required to address these challenges.'),
(94417, 2011, 'bmc', 'Cell subset prediction for blood genomic studies', 'Bolen, Christopher R|Uduman, Mohamed|Kleinstein, Steven H', 'Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA.|Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut 06511, USA.', 'United States|United States|United States', 0, 'Computational Biology|Gene Expression Profiling|Hepatitis C, Chronic|Humans|Leukocytes, Mononuclear|Polymorphism, Single Nucleotide', 'Journal Article', '10.1186/1471-2105-12-258', '21702940', 'Genome-wide transcriptional profiling of patient blood samples offers a powerful tool to investigate underlying disease mechanisms and personalized treatment decisions. Most studies are based on analysis of total peripheral blood mononuclear cells (PBMCs), a mixed population. In this case, accuracy is inherently limited since cell subset-specific differential expression of gene signatures will be diluted by RNA from other cells. While using specific PBMC subsets for transcriptional profiling would improve our ability to extract knowledge from these data, it is rarely obvious which cell subset(s) will be the most informative.'),
(94418, 2011, 'bmc', 'AMDORAP: non-targeted metabolic profiling based on high-resolution LC-MS', 'Takahashi, Hiroki|Morimoto, Takuya|Ogasawara, Naotake|Kanaya, Shigehiko', 'Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan.|Graduate School of Information Science, Nara Institute of Science and Technology, 8916-5 Takayama, Ikoma, Nara 630-0192, Japan.', 'Japan|Japan|Japan|Japan', 12, 'Bacillus subtilis|Chromatography, Liquid|Mass Spectrometry|Metabolome|Metabolomics', 'Journal Article', '10.1186/1471-2105-12-259', '21702951', 'Liquid chromatography-mass spectrometry (LC-MS) utilizing the high-resolution power of an orbitrap is an important analytical technique for both metabolomics and proteomics. Most important feature of the orbitrap is excellent mass accuracy. Thus, it is necessary to convert raw data to accurate and reliable m/z values for metabolic fingerprinting by high-resolution LC-MS.'),
(94419, 2011, 'bmc', 'Computable visually observed phenotype ontological framework for plants', 'Harnsomburana, Jaturon|Green, Jason M|Barb, Adrian S|Schaeffer, Mary|Vincent, Leszek|Shyu, Chi-Ren', 'Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.|Department of Computer Science, University of Missouri, 201 EBW, Columbia, MO 65211, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Databases, Genetic|Fruit|Genomics|Genotype|Phenotype|Plants|Semantics|Vocabulary, Controlled|Zea mays', 'Journal Article', '10.1186/1471-2105-12-260', '21702966', 'The ability to search for and precisely compare similar phenotypic appearances within and across species has vast potential in plant science and genetic research. The difficulty in doing so lies in the fact that many visual phenotypic data, especially visually observed phenotypes that often times cannot be directly measured quantitatively, are in the form of text annotations, and these descriptions are plagued by semantic ambiguity, heterogeneity, and low granularity. Though several bio-ontologies have been developed to standardize phenotypic (and genotypic) information and permit comparisons across species, these semantic issues persist and prevent precise analysis and retrieval of information. A framework suitable for the modeling and analysis of precise computable representations of such phenotypic appearances is needed.'),
(94420, 2011, 'bmc', 'PlantPhos: using maximal dependence decomposition to identify plant phosphorylation sites with substrate site specificity', 'Lee, Tzong-Yi|Bretaña, Neil Arvin|Lu, Cheng-Tsung', 'Department of Computer Science and Engineering, Yuan Ze University, Chungli 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chungli 320, Taiwan. francis@saturn.yzu.edu.tw|Department of Computer Science and Engineering, Yuan Ze University, Chungli 320, Taiwan. francis@saturn.yzu.edu.tw', '-|-|-', 0, 'Amino Acid Motifs|Arabidopsis|Arabidopsis Proteins|Databases, Protein|Markov Chains|Phosphorylation|Phosphotransferases|Protein Structure, Tertiary|Substrate Specificity', 'Journal Article', '10.1186/1471-2105-12-261', '21703007', 'Protein phosphorylation catalyzed by kinases plays crucial regulatory roles in intracellular signal transduction. Due to the difficulty in performing high-throughput mass spectrometry-based experiment, there is a desire to predict phosphorylation sites using computational methods. However, previous studies regarding in silico prediction of plant phosphorylation sites lack the consideration of kinase-specific phosphorylation data. Thus, we are motivated to propose a new method that investigates different substrate specificities in plant phosphorylation sites.'),
(94421, 2011, 'bmc', 'A mutation degree model for the identification of transcriptional regulatory elements', 'Zhang, Changqing|Wang, Jin|Hua, Xu|Fang, Jinggui|Zhu, Huaiqiu|Gao, Xiang', 'State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.', 'China|China|China|China|China|China', 0, 'Algorithms|Arabidopsis|Computational Biology|DNA, Plant|Mutation|Phylogeny|Regulatory Elements, Transcriptional', 'Journal Article', '10.1186/1471-2105-12-262', '21708002', 'Current approaches for identifying transcriptional regulatory elements are mainly via the combination of two properties, the evolutionary conservation and the overrepresentation of functional elements in the promoters of co-regulated genes. Despite the development of many motif detection algorithms, the discovery of conserved motifs in a wide range of phylogenetically related promoters is still a challenge, especially for the short motifs embedded in distantly related gene promoters or very closely related promoters, or in the situation that there are not enough orthologous genes available.'),
(94422, 2011, 'bmc', 'Characterization of a Bayesian genetic clustering algorithm based on a Dirichlet process prior and comparison among Bayesian clustering methods', 'Onogi, Akio|Nurimoto, Masanobu|Morita, Mitsuo', 'Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc., 316 Kanamaru, Maebashi, Gunma, 371-0121, Japan. onogi@liaj.or.jp|Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc., 316 Kanamaru, Maebashi, Gunma, 371-0121, Japan. onogi@liaj.or.jp|Maebashi Institute of Animal Science, Livestock Improvement Association of Japan, Inc., 316 Kanamaru, Maebashi, Gunma, 371-0121, Japan. onogi@liaj.or.jp', 'Japan|Japan|Japan', 13, 'Algorithms|Bayes Theorem|Cluster Analysis|Computer Simulation|Gene Frequency|Genetics, Population|Humans|Markov Chains|Software', 'Journal Article', '10.1186/1471-2105-12-263', '21708038', 'A Bayesian approach based on a Dirichlet process (DP) prior is useful for inferring genetic population structures because it can infer the number of populations and the assignment of individuals simultaneously. However, the properties of the DP prior method are not well understood, and therefore, the use of this method is relatively uncommon. We characterized the DP prior method to increase its practical use.'),
(94423, 2011, 'bmc', 'MAVENs: motion analysis and visualization of elastic networks and structural ensembles', 'Zimmermann, Michael T|Kloczkowski, Andrzej|Jernigan, Robert L', 'LH Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA.|LH Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA.|LH Baker Center for Bioinformatics and Biological Statistics, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States', 31, 'Models, Molecular|Molecular Conformation|Molecular Dynamics Simulation|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-264', '21711533', 'The ability to generate, visualize, and analyze motions of biomolecules has made a significant impact upon modern biology. Molecular Dynamics has gained substantial use, but remains computationally demanding and difficult to setup for many biologists. Elastic network models (ENMs) are an alternative and have been shown to generate the dominant equilibrium motions of biomolecules quickly and efficiently. These dominant motions have been shown to be functionally relevant and also to indicate the likely direction of conformational changes. Most structures have a small number of dominant motions. Comparing computed motions to the structures conformational ensemble derived from a collection of static structures or frames from an MD trajectory is an important way to understand functional motions as well as evaluate the models. Modes of motion computed from ENMs can be visualized to gain functional and mechanistic understanding and to compute useful quantities such as average positional fluctuations, internal distance changes, collectiveness of motions, and directional correlations within the structure.'),
(94424, 2011, 'bmc', 'phenosim--A software to simulate phenotypes for testing in genome-wide association studies', 'Günther, Torsten|Gawenda, Inka|Schmid, Karl J', 'Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany. torsten.guenther@uni-hohenheim.de|Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany. torsten.guenther@uni-hohenheim.de|Institute of Plant Breeding, Seed Science and Population Genetics, University of Hohenheim, Stuttgart, Germany. torsten.guenther@uni-hohenheim.de', 'Germany|Germany|Germany', 0, 'Arabidopsis|Computer Simulation|Genetics, Population|Genome-Wide Association Study|Genotype|Humans|Phenotype|Software', 'Journal Article', '10.1186/1471-2105-12-265', '21714868', 'There is a great interest in understanding the genetic architecture of complex traits in natural populations. Genome-wide association studies (GWAS) are becoming routine in human, animal and plant genetics to understand the connection between naturally occurring genotypic and phenotypic variation. Coalescent simulations are commonly used in population genetics to simulate genotypes under different parameters and demographic models.'),
(94425, 2011, 'bmc', 'DOSim: an R package for similarity between diseases based on Disease Ontology', 'Li, Jiang|Gong, Binsheng|Chen, Xi|Liu, Tao|Wu, Chao|Zhang, Fan|Li, Chunquan|Li, Xiang|Rao, Shaoqi|Li, Xia', 'College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.|College of Bioinformatics Science and Technology, Harbin Medical University, 194 Xuefu Road, Harbin 150081, China.', 'China|China|China|China|China|China|China|China|China|China', 52, 'Computational Biology|Databases, Genetic|Disease|Humans|Neoplasms|Obesity|Semantics|Software|Vocabulary, Controlled', 'Journal Article', '10.1186/1471-2105-12-266', '21714896', 'The construction of the Disease Ontology (DO) has helped promote the investigation of diseases and disease risk factors. DO enables researchers to analyse disease similarity by adopting semantic similarity measures, and has expanded our understanding of the relationships between different diseases and to classify them. Simultaneously, similarities between genes can also be analysed by their associations with similar diseases. As a result, disease heterogeneity is better understood and insights into the molecular pathogenesis of similar diseases have been gained. However, bioinformatics tools that provide easy and straight forward ways to use DO to study disease and gene similarity simultaneously are required.'),
(94426, 2011, 'bmc', 'SeqGene: a comprehensive software solution for mining exome- and transcriptome- sequencing data', 'Deng, Xutao', 'Bioinformatics Core Facility, Department of Molecular Medicine, Beckman Research Institute, City of Hope Medical Center, Duarte, CA 91010, USA. xutaodeng@gmail.com', 'United States', 37, 'DNA Copy Number Variations|Data Mining|Gene Expression Profiling|Genome|Humans|Leukemia, Myeloid, Acute|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Sequence Analysis, DNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-267', '21714929', 'The popularity of massively parallel exome and transcriptome sequencing projects demands new data mining tools with a comprehensive set of features to support a wide range of analysis tasks.'),
(94427, 2011, 'bmc', 'New words in human mutagenesis', 'Panchin, Alexander Y|Mitrofanov, Sergey I|Alexeevski, Andrei V|Spirin, Sergey A|Panchin, Yuri V', 'Department of Bioengineering and Bioinformatics, Moscow State University, Vorbyevy Gory 1-73, Moscow, 119992, Russian Federation. alexpanchin@yahoo.com|Department of Bioengineering and Bioinformatics, Moscow State University, Vorbyevy Gory 1-73, Moscow, 119992, Russian Federation. alexpanchin@yahoo.com|Department of Bioengineering and Bioinformatics, Moscow State University, Vorbyevy Gory 1-73, Moscow, 119992, Russian Federation. alexpanchin@yahoo.com|Department of Bioengineering and Bioinformatics, Moscow State University, Vorbyevy Gory 1-73, Moscow, 119992, Russian Federation. alexpanchin@yahoo.com|Department of Bioengineering and Bioinformatics, Moscow State University, Vorbyevy Gory 1-73, Moscow, 119992, Russian Federation. alexpanchin@yahoo.com', 'Russian Federation|Russian Federation|Russian Federation|Russian Federation|Russian Federation', 0, 'Animals|CpG Islands|Genome, Human|Humans|Pan troglodytes|Point Mutation|Polymorphism, Single Nucleotide|Pongo|Primates|Selection, Genetic', 'Journal Article', '10.1186/1471-2105-12-268', '21718472', 'The substitution rates within different nucleotide contexts are subject to varying levels of bias. The most well known example of such bias is the excess of C to T (C > T) mutations in CpG (CG) dinucleotides. The molecular mechanisms underlying this bias are important factors in human genome evolution and cancer development. The discovery of other nucleotide contexts that have profound effects on substitution rates can improve our understanding of how mutations are acquired, and why mutation hotspots exist.'),
(94428, 2011, 'bmc', 'Network-based group variable selection for detecting expression quantitative trait loci (eQTL)', 'Wang, Weichen|Zhang, Xuegong', 'Mathematics and Physics, School of Sciences, Tsinghua University, Beijing 100084, China. wwc07@mails.tsinghua.edu.cn|Mathematics and Physics, School of Sciences, Tsinghua University, Beijing 100084, China. wwc07@mails.tsinghua.edu.cn', 'China|China', 0, 'Animals|Crosses, Genetic|Diabetes Complications|Gene Expression Profiling|Gene Regulatory Networks|Linkage Disequilibrium|Mice|Mice, Inbred C57BL|Mice, Obese|Models, Genetic|Obesity|Polymorphism, Single Nucleotide|Quantitative Trait Loci', 'Journal Article', '10.1186/1471-2105-12-269', '21718480', 'Analysis of expression quantitative trait loci (eQTL) aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD) structure between loci in high-noise background.'),
(94429, 2011, 'bmc', 'Predicting mutually exclusive spliced exons based on exon length, splice site and reading frame conservation, and exon sequence homology', 'Pillmann, Holger|Hatje, Klas|Odronitz, Florian|Hammesfahr, Björn|Kollmar, Martin', 'Abteilung NMR basierte Strukturbiologie, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, D-37077 Göttingen, Germany.|Abteilung NMR basierte Strukturbiologie, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, D-37077 Göttingen, Germany.|Abteilung NMR basierte Strukturbiologie, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, D-37077 Göttingen, Germany.|Abteilung NMR basierte Strukturbiologie, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, D-37077 Göttingen, Germany.|Abteilung NMR basierte Strukturbiologie, Max-Planck-Institut für Biophysikalische Chemie, Am Fassberg 11, D-37077 Göttingen, Germany.', 'Germany|Germany|Germany|Germany|Germany', 19, 'Algorithms|Alternative Splicing|Amino Acid Sequence|Animals|Base Sequence|Drosophila Proteins|Drosophila melanogaster|Exons|Introns|Molecular Sequence Data|RNA Splice Sites|Reading Frames|X Chromosome', 'Journal Article', '10.1186/1471-2105-12-270', '21718515', 'Alternative splicing of pre-mature RNA is an important process eukaryotes utilize to increase their repertoire of different protein products. Several types of different alternative splice forms exist including exon skipping, differential splicing of exons at their 3- or 5-end, intron retention, and mutually exclusive splicing. The latter term is used for clusters of internal exons that are spliced in a mutually exclusive manner.'),
(94430, 2011, 'bmc', 'DNACLUST: accurate and efficient clustering of phylogenetic marker genes', 'Ghodsi, Mohammadreza|Liu, Bo|Pop, Mihai', 'Department of Computer Science, University of Maryland, College Park, MD 20742, USA.|Department of Computer Science, University of Maryland, College Park, MD 20742, USA.|Department of Computer Science, University of Maryland, College Park, MD 20742, USA.', 'United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Genetic Markers|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-271', '21718538', 'Clustering is a fundamental operation in the analysis of biological sequence data. New DNA sequencing technologies have dramatically increased the rate at which we can generate data, resulting in datasets that cannot be efficiently analyzed by traditional clustering methods.This is particularly true in the context of taxonomic profiling of microbial communities through direct sequencing of phylogenetic markers (e.g. 16S rRNA) - the domain that motivated the work described in this paper. Many analysis approaches rely on an initial clustering step aimed at identifying sequences that belong to the same operational taxonomic unit (OTU). When defining OTUs (which have no universally accepted definition), scientists must balance a trade-off between computational efficiency and biological accuracy, as accurately estimating an environments phylogenetic composition requires computationally-intensive analyses. We propose that efficient and mathematically well defined clustering methods can benefit existing taxonomic profiling approaches in two ways: (i) the resulting clusters can be substituted for OTUs in certain applications, and (ii) the clustering effectively reduces the size of the data-sets that need to be analyzed by complex phylogenetic pipelines (e.g., only one sequence per cluster needs to be provided to downstream analyses).'),
(94431, 2011, 'bmc', 'Improving pan-genome annotation using whole genome multiple alignment', 'Angiuoli, Samuel V|Dunning Hotopp, Julie C|Salzberg, Steven L|Tettelin, Hervé', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. angiuoli@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. angiuoli@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. angiuoli@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, MD 20742, USA. angiuoli@umiacs.umd.edu', 'United States|United States|United States|United States', 0, 'Bacteria|Chromosome Mapping|Genome, Bacterial|Molecular Sequence Annotation|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-272', '21718539', 'Rapid annotation and comparisons of genomes from multiple isolates (pan-genomes) is becoming commonplace due to advances in sequencing technology. Genome annotations can contain inconsistencies and errors that hinder comparative analysis even within a single species. Tools are needed to compare and improve annotation quality across sets of closely related genomes.'),
(94432, 2011, 'bmc', 'Gene set analysis for longitudinal gene expression data', 'Zhang, Ke|Wang, Haiyan|Bathke, Arne C|Harrar, Solomon W|Piepho, Hans-Peter|Deng, Youping', 'School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu|School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu|School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu|School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu|School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu|School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND 58202, USA. ke.zhang@med.und.edu', 'United States|United States|United States|United States|United States|United States', 10, 'Animals|Gene Expression Profiling|Interleukin-2|Longitudinal Studies|Mice|North Dakota|Oligonucleotide Array Sequence Analysis|T-Lymphocytes', 'Journal Article', '10.1186/1471-2105-12-273', '21722407', 'Gene set analysis (GSA) has become a successful tool to interpret gene expression profiles in terms of biological functions, molecular pathways, or genomic locations. GSA performs statistical tests for independent microarray samples at the level of gene sets rather than individual genes. Nowadays, an increasing number of microarray studies are conducted to explore the dynamic changes of gene expression in a variety of species and biological scenarios. In these longitudinal studies, gene expression is repeatedly measured over time such that a GSA needs to take into account the within-gene correlations in addition to possible between-gene correlations.'),
(94433, 2011, 'bmc', 'Detection of lineage-specific evolutionary changes among primate species', 'Pertea, Mihaela|Pertea, Geo M|Salzberg, Steven L', 'Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. mpertea@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. mpertea@umiacs.umd.edu|Center for Bioinformatics and Computational Biology, University of Maryland, College Park, Maryland, USA. mpertea@umiacs.umd.edu', 'United States|United States|United States', 0, 'Animals|Biological Evolution|Genome|Genome, Human|Humans|Phylogeny|Primates|Software', 'Journal Article', '10.1186/1471-2105-12-274', '21726447', 'Comparison of the human genome with other primates offers the opportunity to detect evolutionary events that created the diverse phenotypes among the primate species. Because the primate genomes are highly similar to one another, methods developed for analysis of more divergent species do not always detect signs of evolutionary selection.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94434, 2011, 'bmc', 'AlignHUSH: alignment of HMMs using structure and hydrophobicity information', 'Krishnadev, Oruganty|Srinivasan, Narayanaswamy', 'Molecular Biophysics Unit Indian Institute of Science, Bangalore 560012, India.|Molecular Biophysics Unit Indian Institute of Science, Bangalore 560012, India.', 'India|India', 9, 'Algorithms|Amino Acid Sequence|Humans|Hydrophobic and Hydrophilic Interactions|Markov Chains|Models, Molecular|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-275', '21729312', 'Sensitive remote homology detection and accurate alignments especially in the midnight zone of sequence similarity are needed for better function annotation and structural modeling of proteins. An algorithm, AlignHUSH for HMM-HMM alignment has been developed which is capable of recognizing distantly related domain families The method uses structural information, in the form of predicted secondary structure probabilities, and hydrophobicity of amino acids to align HMMs of two sets of aligned sequences. The effect of using adjoining column(s) information has also been investigated and is found to increase the sensitivity of HMM-HMM alignments and remote homology detection.'),
(94435, 2011, 'bmc', 'Quantitative characterization and analysis of the dynamic NF-xcexbaB response in microglia', 'Sheppard, Patrick W|Sun, Xiaoyun|Emery, John F|Giffard, Rona G|Khammash, Mustafa', 'Department of Mechanical Engineering, University of California, Santa Barbara, Engineering II Bldg,, Santa Barbara, CA 93106-5070, USA.|Department of Mechanical Engineering, University of California, Santa Barbara, Engineering II Bldg,, Santa Barbara, CA 93106-5070, USA.|Department of Mechanical Engineering, University of California, Santa Barbara, Engineering II Bldg,, Santa Barbara, CA 93106-5070, USA.|Department of Mechanical Engineering, University of California, Santa Barbara, Engineering II Bldg,, Santa Barbara, CA 93106-5070, USA.|Department of Mechanical Engineering, University of California, Santa Barbara, Engineering II Bldg,, Santa Barbara, CA 93106-5070, USA.', 'United States|United States|United States|United States|United States', 12, 'Animals|Brain Ischemia|Cell Line|Cytokines|Gene Expression Regulation|I-kappa B Kinase|Inflammation|Mice|Microglia|NF-kappa B|Signal Transduction|Transcription Factor RelA|Tumor Necrosis Factor-alpha', 'Journal Article', '10.1186/1471-2105-12-276', '21729324', 'Activation of the NF-xcexbaB transcription factor and its associated gene expression in microglia is a key component in the response to brain injury. Its activation is dynamic and is part of a network of biochemical species with multiple feedback regulatory mechanisms. Mathematical modeling, which has been instrumental for understanding the NF-xcexbaB response in other cell types, offers a valuable tool to investigate the regulation of NF-xcexbaB activation in microglia at a systems level.'),
(94436, 2011, 'bmc', 'An integrated ChIP-seq analysis platform with customizable workflows', 'Giannopoulou, Eugenia G|Elemento, Olivier', 'HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY 10021, USA.|HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY 10021, USA.', 'United States|United States', 67, 'Chromatin Immunoprecipitation|Chromosome Mapping|Enhancer Elements, Genetic|High-Throughput Nucleotide Sequencing|Histone Code|Humans|Jurkat Cells|Proto-Oncogene Protein c-ets-1|Software|Workflow', 'Journal Article', '10.1186/1471-2105-12-277', '21736739', 'Chromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks.'),
(94437, 2011, 'bmc', 'ReadDB provides efficient storage for mapped short reads', 'Rolfe, P Alexander|Gifford, David K', 'Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. dkg@mit.edu|Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02139, USA. dkg@mit.edu', 'United States|United States', 0, 'Algorithms|Databases, Genetic|Genome|High-Throughput Nucleotide Sequencing|Humans|Software', 'Journal Article', '10.1186/1471-2105-12-278', '21736741', 'The advent of high-throughput sequencing has enabled sequencing based measurements of cellular function, with an individual measurement potentially consisting of more than 108 reads. While tools are available for aligning sets of reads to genomes and interpreting the results, fewer tools have been developed to address the storage and retrieval requirements of large collections of aligned datasets. We present ReadDB, a network accessible column store database system for aligned high-throughput read datasets.'),
(94438, 2011, 'bmc', 'Detection of fused genes in eukaryotic genomes using gene deFuser: analysis of the Tetrahymena thermophila genome', 'Salim, Hannah M W|Koire, Amanda M|Stover, Nicholas A|Cavalcanti, Andre R O', 'Department of Biology, Pomona College, Claremont, California 91711, USA.|Department of Biology, Pomona College, Claremont, California 91711, USA.|Department of Biology, Pomona College, Claremont, California 91711, USA.|Department of Biology, Pomona College, Claremont, California 91711, USA.', 'United States|United States|United States|United States', 10, 'Algorithms|Genes, Protozoan|Genome, Protozoan|Molecular Sequence Annotation|Molecular Sequence Data|Software|Tetrahymena thermophila', 'Journal Article', '10.1186/1471-2105-12-279', '21745395', 'Fused genes are important sources of data for studies of evolution and protein function. To date no service has been made available online to aid in the large-scale identification of fused genes in sequenced genomes. We have developed a program, Gene deFuser, that analyzes uploaded protein sequence files for characteristics of gene fusion events and presents the results in a convenient web interface.'),
(94439, 2011, 'bmc', 'DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking', 'Liu, Shiyong|Vakser, Ilya A', 'Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.|Biomolecular Physics and Modeling Group, Department of Physics, Huazhong University of Science and Technology, Wuhan 430074, Hubei, China.', 'China|China', 38, 'Artificial Intelligence|Humans|Knowledge Bases|Models, Molecular|Protein Binding|Protein Interaction Domains and Motifs|Protein Structure, Secondary|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-280', '21745398', 'Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom) pairs in the non-interaction state.'),
(94440, 2011, 'bmc', 'A novel method to identify cooperative functional modules: study of module coordination in the Saccharomyces cerevisiae cell cycle', 'Hsu, Jeh-Ting|Peng, Chien-Hua|Hsieh, Wen-Ping|Lan, Chung-Yu|Tang, Chuan Yi', 'Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.|Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.|Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.|Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.|Department of Computer Science, National Tsing Hua University, Hsinchu 30013, Taiwan.', '-|-|-|-|-', 7, 'Cell Cycle|Gene Expression Profiling|Gene Expression Regulation, Fungal|Mitosis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Journal Article', '10.1186/1471-2105-12-281', '21749690', 'Identifying key components in biological processes and their associations is critical for deciphering cellular functions. Recently, numerous gene expression and molecular interaction experiments have been reported in Saccharomyces cerevisiae, and these have enabled systematic studies. Although a number of approaches have been used to predict gene functions and interactions, tools that analyze the essential coordination of functional components in cellular processes still need to be developed.'),
(94441, 2011, 'bmc', 'Algal Functional Annotation Tool: a web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data', 'Lopez, David|Casero, David|Cokus, Shawn J|Merchant, Sabeeha S|Pellegrini, Matteo', 'Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.|Department of Molecular, Cell, and Developmental Biology, University of California, Los Angeles, CA, USA.', 'United States|United States|United States|United States|United States', 60, 'Arabidopsis|Chlamydomonas reinhardtii|Databases, Genetic|Eukaryota|Gene Expression|Genomics|Internet|Software', 'Journal Article', '10.1186/1471-2105-12-282', '21749710', 'Progress in genome sequencing is proceeding at an exponential pace, and several new algal genomes are becoming available every year. One of the challenges facing the community is the association of protein sequences encoded in the genomes with biological function. While most genome assembly projects generate annotations for predicted protein sequences, they are usually limited and integrate functional terms from a limited number of databases. Another challenge is the use of annotations to interpret large lists of interesting genes generated by genome-scale datasets. Previously, these gene lists had to be analyzed across several independent biological databases, often on a gene-by-gene basis. In contrast, several annotation databases, such as DAVID, integrate data from multiple functional databases and reveal underlying biological themes of large gene lists. While several such databases have been constructed for animals, none is currently available for the study of algae. Due to renewed interest in algae as potential sources of biofuels and the emergence of multiple algal genome sequences, a significant need has arisen for such a database to process the growing compendiums of algal genomic data.'),
(94442, 2011, 'bmc', 'Improving the performance of xcexb2-turn prediction using predicted shape strings and a two-layer support vector machine model', 'Tang, Zehui|Li, Tonghua|Liu, Rida|Xiong, Wenwei|Sun, Jiangming|Zhu, Yaojuan|Chen, Guanyan', 'Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.|Department of Chemistry, Tongji University, Shanghai, 200092, China.', 'China|China|China|China|China|China|China', 15, 'Algorithms|Humans|Position-Specific Scoring Matrices|Protein Structure, Secondary|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1186/1471-2105-12-283', '21749732', 'The xcexb2-turn is a secondary protein structure type that plays an important role in protein configuration and function. Development of accurate prediction methods to identify xcexb2-turns in protein sequences is valuable. Several methods for xcexb2-turn prediction have been developed, however, the prediction quality is still a challenge and there is substantial room for improvement. Innovations of the proposed method focus on discovering effective features, and constructing a new architectural model.'),
(94443, 2011, 'bmc', 'Modeling measurement error in tumor characterization studies', 'Rakovski, Cyril|Weisenberger, Daniel J|Marjoram, Paul|Laird, Peter W|Siegmund, Kimberly D', 'Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California 90089-9176, USA.|Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California 90089-9176, USA.|Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California 90089-9176, USA.|Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California 90089-9176, USA.|Department of Preventive Medicine, USC Keck School of Medicine, Los Angeles, California 90089-9176, USA.', 'United States|United States|United States|United States|United States', 3, 'Adaptor Proteins, Signal Transducing|Alu Elements|Colonic Neoplasms|Computer Simulation|DNA Methylation|DNA Mutational Analysis|Female|Humans|Least-Squares Analysis|Linear Models|Male|MutL Protein Homolog 1|Nuclear Proteins|Regression Analysis', 'Journal Article', '10.1186/1471-2105-12-284', '21752297', 'Etiologic studies of cancer increasingly use molecular features such as gene expression, DNA methylation and sequence mutation to subclassify the cancer type. In large population-based studies, the tumor tissues available for study are archival specimens that provide variable amounts of amplifiable DNA for molecular analysis. As molecular features measured from small amounts of tumor DNA are inherently noisy, we propose a novel approach to improve statistical efficiency when comparing groups of samples. We illustrate the phenomenon using the MethyLight technology, applying our proposed analysis to compare MLH1 DNA methylation levels in males and females studied in the Colon Cancer Family Registry.'),
(94444, 2011, 'bmc', 'S3QL: a distributed domain specific language for controlled semantic integration of life sciences data', 'Deus, Helena F|Correa, Miriã C|Stanislaus, Romesh|Miragaia, Maria|Maass, Wolfgang|de Lencastre, Hermínia|Fox, Ronan|Almeida, Jonas S', 'Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org|Digital Enterprise Research Institute, National University of Ireland at Galway, IDA Business Park, Lower Dangan, Galway, Ireland. helena.deus@deri.org', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland', 11, 'Biology|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Internet|Programming Languages|Semantics|Software', 'Journal Article', '10.1186/1471-2105-12-285', '21756325', 'The value and usefulness of data increases when it is explicitly interlinked with related data. This is the core principle of Linked Data. For life sciences researchers, harnessing the power of Linked Data to improve biological discovery is still challenged by a need to keep pace with rapidly evolving domains and requirements for collaboration and control as well as with the reference semantic web ontologies and standards. Knowledge organization systems (KOSs) can provide an abstraction for publishing biological discoveries as Linked Data without complicating transactions with contextual minutia such as provenance and access control.We have previously described the Simple Sloppy Semantic Database (S3DB) as an efficient model for creating knowledge organization systems using Linked Data best practices with explicit distinction between domain and instantiation and support for a permission control mechanism that automatically migrates between the two. In this report we present a domain specific language, the S3DB query language (S3QL), to operate on its underlying core model and facilitate management of Linked Data.'),
(94445, 2011, 'bmc', 'Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview', 'Skinner, Jeff|Kotliarov, Yuri|Varma, Sudhir|Mine, Karina L|Yambartsev, Anatoly|Simon, Richard|Huyen, Yentram|Morgun, Andrey', 'Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.|Bioinformatics and Computational Biosciences Branch (BCBB), Office of Cyber Infrastructure and Computational Biology (OCICB), National Institute of Allergy and Infectious Disease (NIAID), National Institutes if Health (NIH), Bethesda, Maryland, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 14, 'Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Regulatory Networks|Glioma|Humans|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-286', '21756334', 'DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes.'),
(94446, 2011, 'bmc', 'Statistical mutation calling from sequenced overlapping DNA pools in TILLING experiments', 'Missirian, Victor|Comai, Luca|Filkov, Vladimir', 'Department of Computer Science, UC Davis, 1 Shields Ave., Davis, CA 95616, USA.|Department of Computer Science, UC Davis, 1 Shields Ave., Davis, CA 95616, USA.|Department of Computer Science, UC Davis, 1 Shields Ave., Davis, CA 95616, USA.', 'United States|United States|United States', 28, 'Bayes Theorem|DNA, Plant|Genome, Plant|Genomics|High-Throughput Nucleotide Sequencing|Mutagenesis|Mutation|Oryza|Sensitivity and Specificity|Sequence Analysis, DNA|Triticum', 'Evaluation Studies', '10.1186/1471-2105-12-287', '21756356', 'TILLING (Targeting induced local lesions IN genomes) is an efficient reverse genetics approach for detecting induced mutations in pools of individuals. Combined with the high-throughput of next-generation sequencing technologies, and the resolving power of overlapping pool design, TILLING provides an efficient and economical platform for functional genomics across thousands of organisms.'),
(94447, 2011, 'bmc', 'Reporting FDR analogous confidence intervals for the log fold change of differentially expressed genes', 'Jung, Klaus|Friede, Tim|Beissbarth, Tim', 'Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany. Klaus.Jung@ams.med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany. Klaus.Jung@ams.med.uni-goettingen.de|Department of Medical Statistics, University Medical Center Göttingen, D-37099 Göttingen, Germany. Klaus.Jung@ams.med.uni-goettingen.de', 'Germany|Germany|Germany', 20, 'Adenocarcinoma|Algorithms|Confidence Intervals|Gene Expression Profiling|Humans|Lung Neoplasms|Oligonucleotide Array Sequence Analysis|Rectal Neoplasms', 'Journal Article', '10.1186/1471-2105-12-288', '21756370', 'Gene expression experiments are common in molecular biology, for example in order to identify genes which play a certain role in a specified biological framework. For that purpose expression levels of several thousand genes are measured simultaneously using DNA microarrays. Comparing two distinct groups of tissue samples to detect those genes which are differentially expressed one statistical test per gene is performed, and resulting p-values are adjusted to control the false discovery rate. In addition, the expression change of each gene is quantified by some effect measure, typically the log fold change. In certain cases, however, a gene with a significant p-value can have a rather small fold change while in other cases a non-significant gene can have a rather large fold change. The biological relevance of the change of gene expression can be more intuitively judged by a fold change then merely by a p-value. Therefore, confidence intervals for the log fold change which accompany the adjusted p-values are desirable.'),
(94448, 2011, 'bmc', 'Bio::Homology::InterologWalk--a Perl module to build putative protein-protein interaction networks through interolog mapping', 'Gallone, Giuseppe|Simpson, T Ian|Armstrong, J Douglas|Jarman, Andrew P', 'Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK. G.Gallone@sms.ed.ac.uk|Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK. G.Gallone@sms.ed.ac.uk|Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK. G.Gallone@sms.ed.ac.uk|Centre for Integrative Physiology, University of Edinburgh, Hugh Robson Building, George Square, Edinburgh EH8 9XD, UK. G.Gallone@sms.ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Animals|Drosophila Proteins|Drosophila melanogaster|Genome, Insect|Protein Interaction Mapping|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-12-289', '21767381', 'Protein-protein interaction (PPI) data are widely used to generate network models that aim to describe the relationships between proteins in biological systems. The fidelity and completeness of such networks is primarily limited by the paucity of protein interaction information and by the restriction of most of these data to just a few widely studied experimental organisms. In order to extend the utility of existing PPIs, computational methods can be used that exploit functional conservation between orthologous proteins across taxa to predict putative PPIs or interologs. To date most interolog prediction efforts have been restricted to specific biological domains with fixed underlying data sources and there are no software tools available that provide a generalised framework for on-the-fly interolog prediction.'),
(94449, 2011, 'bmc', 'Bias detection and correction in RNA-Sequencing data', 'Zheng, Wei|Chung, Lisa M|Zhao, Hongyu', 'Biostatistics Resource, Keck Laboratory, Yale University, 300 George Street, New Haven, Connecticut, 06510, USA.|Biostatistics Resource, Keck Laboratory, Yale University, 300 George Street, New Haven, Connecticut, 06510, USA.|Biostatistics Resource, Keck Laboratory, Yale University, 300 George Street, New Haven, Connecticut, 06510, USA.', 'United States|United States|United States', 96, 'Gene Expression Profiling|Humans|Meta-Analysis as Topic|RNA|Sequence Analysis, RNA|Yeasts', 'Journal Article', '10.1186/1471-2105-12-290', '21771300', 'High throughput sequencing technology provides us unprecedented opportunities to study transcriptome dynamics. Compared to microarray-based gene expression profiling, RNA-Seq has many advantages, such as high resolution, low background, and ability to identify novel transcripts. Moreover, for genes with multiple isoforms, expression of each isoform may be estimated from RNA-Seq data. Despite these advantages, recent work revealed that base level read counts from RNA-Seq data may not be randomly distributed and can be affected by local nucleotide composition. It was not clear though how the base level read count bias may affect gene level expression estimates.'),
(94450, 2011, 'bmc', 'Inferring signalling networks from longitudinal data using sampling based approaches in the R-package ddepn', 'Bender, Christian|Heyde, Silvia vd|Henjes, Frauke|Wiemann, Stefan|Korf, Ulrike|Beissbarth, Tim', 'German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de|German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de|German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de|German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de|German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de|German Cancer Research Center (DKFZ), Division of Molecular Genome Analysis, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. c.bender@dkfz-heidelberg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Breast Neoplasms|Cell Line, Tumor|Humans|Longitudinal Studies|Markov Chains|Models, Biological|Monte Carlo Method|Signal Transduction|Software', 'Journal Article', '10.1186/1471-2105-12-291', '21771315', 'Network inference from high-throughput data has become an important means of current analysis of biological systems. For instance, in cancer research, the functional relationships of cancer related proteins, summarised into signalling networks are of central interest for the identification of pathways that influence tumour development. Cancer cell lines can be used as model systems to study the cellular response to drug treatments in a time-resolved way. Based on these kind of data, modelling approaches for the signalling relationships are needed, that allow to generate hypotheses on potential interference points in the networks.'),
(94451, 2011, 'bmc', 'Unraveling gene regulatory networks from time-resolved gene expression data - a measures comparison study', 'Hempel, Sabrina|Koseska, Aneta|Nikoloski, Zoran|Kurths, Jürgen', 'Interdisciplinary Center for Dynamics of Complex Systems, University of Potsdam, Campus Golm, Karl-Liebknecht-Str. 24, D-14476 Potsdam, Germany. sabrina.donner@pik-potsdam.de|Interdisciplinary Center for Dynamics of Complex Systems, University of Potsdam, Campus Golm, Karl-Liebknecht-Str. 24, D-14476 Potsdam, Germany. sabrina.donner@pik-potsdam.de|Interdisciplinary Center for Dynamics of Complex Systems, University of Potsdam, Campus Golm, Karl-Liebknecht-Str. 24, D-14476 Potsdam, Germany. sabrina.donner@pik-potsdam.de|Interdisciplinary Center for Dynamics of Complex Systems, University of Potsdam, Campus Golm, Karl-Liebknecht-Str. 24, D-14476 Potsdam, Germany. sabrina.donner@pik-potsdam.de', 'Germany|Germany|Germany|Germany', 33, 'Algorithms|Computational Biology|Escherichia coli|Gene Expression|Gene Expression Regulation|Gene Regulatory Networks|Genes, Bacterial|Humans', 'Comparative Study', '10.1186/1471-2105-12-292', '21771321', 'Inferring regulatory interactions between genes from transcriptomics time-resolved data, yielding reverse engineered gene regulatory networks, is of paramount importance to systems biology and bioinformatics studies. Accurate methods to address this problem can ultimately provide a deeper insight into the complexity, behavior, and functions of the underlying biological systems. However, the large number of interacting genes coupled with short and often noisy time-resolved read-outs of the system renders the reverse engineering a challenging task. Therefore, the development and assessment of methods which are computationally efficient, robust against noise, applicable to short time series data, and preferably capable of reconstructing the directionality of the regulatory interactions remains a pressing research problem with valuable applications.'),
(94452, 2011, 'bmc', 'FAAST: Flow-space Assisted Alignment Search Tool', 'Lysholm, Fredrik|Andersson, Björn|Persson, Bengt', 'IFM Bioinformatics and SeRC (Swedish e-Science Research Centre), Linköping University, S-581 83 Linköping, Sweden. frely@ifm.liu.se|IFM Bioinformatics and SeRC (Swedish e-Science Research Centre), Linköping University, S-581 83 Linköping, Sweden. frely@ifm.liu.se|IFM Bioinformatics and SeRC (Swedish e-Science Research Centre), Linköping University, S-581 83 Linköping, Sweden. frely@ifm.liu.se', 'Sweden|Sweden|Sweden', 8, 'Algorithms|Search Engine|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-293', '21771335', 'High throughput pyrosequencing (454 sequencing) is the major sequencing platform for producing long read high throughput data. While most other sequencing techniques produce reading errors mainly comparable with substitutions, pyrosequencing produce errors mainly comparable with gaps. These errors are less efficiently detected by most conventional alignment programs and may produce inaccurate alignments.'),
(94453, 2011, 'bmc', 'Multi-target QSAR modelling in the analysis and design of HIV-HCV co-inhibitors: an in-silico study', 'Liu, Qi|Zhou, Han|Liu, Lin|Chen, Xi|Zhu, Ruixin|Cao, Zhiwei', 'College of Life Science and Biotechnology, Tongji University, 200092, China.|College of Life Science and Biotechnology, Tongji University, 200092, China.|College of Life Science and Biotechnology, Tongji University, 200092, China.|College of Life Science and Biotechnology, Tongji University, 200092, China.|College of Life Science and Biotechnology, Tongji University, 200092, China.|College of Life Science and Biotechnology, Tongji University, 200092, China.', 'China|China|China|China|China|China', 0, 'Anti-HIV Agents|Antiviral Agents|Coinfection|Drug Design|HIV|HIV Infections|Hepacivirus|Hepatitis C|Humans|Models, Biological|Quantitative Structure-Activity Relationship', 'Journal Article', '10.1186/1471-2105-12-294', '21774796', 'HIV and HCV infections have become the leading global public-health threats. Even more remarkable, HIV-HCV co-infection is rapidly emerging as a major cause of morbidity and mortality throughout the world, due to the common rapid mutation characteristics of the two viruses as well as their similar complex influence to immunology system. Although considerable progresses have been made on the study of the infection of HIV and HCV respectively, few researches have been conducted on the investigation of the molecular mechanism of their co-infection and designing of the multi-target co-inhibitors for the two viruses simultaneously.'),
(94454, 2011, 'bmc', 'ADAM: analysis of discrete models of biological systems using computer algebra', 'Hinkelmann, Franziska|Brandon, Madison|Guang, Bonny|McNeill, Rustin|Blekherman, Grigoriy|Veliz-Cuba, Alan|Laubenbacher, Reinhard', 'Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Tech, Washington Street, MC 0477, Blacksburg, VA 24061, USA.', 'United States|United States|United States|United States|United States|United States|United States', 46, 'Algorithms|Models, Biological|Software|Systems Biology|Systems Theory', 'Journal Article', '10.1186/1471-2105-12-295', '21774817', 'Many biological systems are modeled qualitatively with discrete models, such as probabilistic Boolean networks, logical models, Petri nets, and agent-based models, to gain a better understanding of them. The computational complexity to analyze the complete dynamics of these models grows exponentially in the number of variables, which impedes working with complex models. There exist software tools to analyze discrete models, but they either lack the algorithmic functionality to analyze complex models deterministically or they are inaccessible to many users as they require understanding the underlying algorithm and implementation, do not have a graphical user interface, or are hard to install. Efficient analysis methods that are accessible to modelers and easy to use are needed.'),
(94455, 2011, 'bmc', 'Differential C3NET reveals disease networks of direct physical interactions', 'Altay, Gökmen|Asim, Mohammad|Markowetz, Florian|Neal, David E', 'Department of Oncology, University of Cambridge, Cambridge Research Institute, CB2 0RE, Cambridge, UK. ga303@cam.ac.uk|Department of Oncology, University of Cambridge, Cambridge Research Institute, CB2 0RE, Cambridge, UK. ga303@cam.ac.uk|Department of Oncology, University of Cambridge, Cambridge Research Institute, CB2 0RE, Cambridge, UK. ga303@cam.ac.uk|Department of Oncology, University of Cambridge, Cambridge Research Institute, CB2 0RE, Cambridge, UK. ga303@cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 27, 'Algorithms|DNA Repair Enzymes|DNA-Binding Proteins|Disease|Follow-Up Studies|Gene Regulatory Networks|Humans|Male|Prostatic Neoplasms|Telomeric Repeat Binding Protein 2', 'Journal Article', '10.1186/1471-2105-12-296', '21777411', 'Genes might have different gene interactions in different cell conditions, which might be mapped into different networks. Differential analysis of gene networks allows spotting condition-specific interactions that, for instance, form disease networks if the conditions are a disease, such as cancer, and normal. This could potentially allow developing better and subtly targeted drugs to cure cancer. Differential network analysis with direct physical gene interactions needs to be explored in this endeavour.'),
(94456, 2011, 'bmc', 'BioIMAX: a Web 20 approach for easy exploratory and collaborative access to multivariate bioimage data', 'Loyek, Christian|Rajpoot, Nasir M|Khan, Michael|Nattkemper, Tim W', 'Biodata Mining Group, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany. cloyek@techfak.uni-bielefeld.de|Biodata Mining Group, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany. cloyek@techfak.uni-bielefeld.de|Biodata Mining Group, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany. cloyek@techfak.uni-bielefeld.de|Biodata Mining Group, Faculty of Technology, Bielefeld University, Universitätsstraße 25, 33615 Bielefeld, Germany. cloyek@techfak.uni-bielefeld.de', 'Germany|Germany|Germany|Germany', 9, 'Computer-Assisted Instruction|Cooperative Behavior|Diagnostic Imaging|Image Processing, Computer-Assisted|Internet|Software', 'Journal Article', '10.1186/1471-2105-12-297', '21777450', 'Innovations in biological and biomedical imaging produce complex high-content and multivariate image data. For decision-making and generation of hypotheses, scientists need novel information technology tools that enable them to visually explore and analyze the data and to discuss and communicate results or findings with collaborating experts from various places.'),
(94457, 2011, 'bmc', 'GPS-Prot: a web-based visualization platform for integrating host-pathogen interaction data', 'Fahey, Marie E|Bennett, Melanie J|Mahon, Cathal|Jäger, Stefanie|Pache, Lars|Kumar, Dhiraj|Shapiro, Alex|Rao, Kanury|Chanda, Sumit K|Craik, Charles S|Frankel, Alan D|Krogan, Nevan J', 'Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, USA.|Department of Cellular and Molecular Pharmacology, University of California San Francisco, 1700 4th Street, San Francisco, CA 94158, 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', 0, 'HIV Infections|HIV-1|Host-Pathogen Interactions|Humans|Internet|Protein Interaction Mapping|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-12-298', '21777475', 'The increasing availability of HIV-host interaction datasets, including both physical and genetic interactions, has created a need for software tools to integrate and visualize the data. Because these host-pathogen interactions are extensive and interactions between human proteins are found within many different databases, it is difficult to generate integrated HIV-human interaction networks.'),
(94458, 2011, 'bmc', 'Ranking insertion, deletion and nonsense mutations based on their effect on genetic information', 'Zia, Amin|Moses, Alan M', 'Department of Cell & Systems Biology, University of Toronto, 25 Willcocks Street, Toronto, Ontario, M5S 3B2, Canada.|Department of Cell & Systems Biology, University of Toronto, 25 Willcocks Street, Toronto, Ontario, M5S 3B2, Canada.', 'Canada|Canada', 17, 'Codon, Nonsense|Computational Biology|Disease|Genetics, Medical|Humans|INDEL Mutation|Mutagenesis, Insertional|Mutation|Yeasts', 'Journal Article', '10.1186/1471-2105-12-299', '21781308', 'Genetic variations contribute to normal phenotypic differences as well as diseases, and new sequencing technologies are greatly increasing the capacity to identify these variations. Given the large number of variations now being discovered, computational methods to prioritize the functional importance of genetic variations are of growing interest. Thus far, the focus of computational tools has been mainly on the prediction of the effects of amino acid changing single nucleotide polymorphisms (SNPs) and little attention has been paid to indels or nonsense SNPs that result in premature stop codons.'),
(94459, 2011, 'bmc', 'miRTar: an integrated system for identifying miRNA-target interactions in human', 'Hsu, Justin Bo-Kai|Chiu, Chih-Min|Hsu, Sheng-Da|Huang, Wei-Yun|Chien, Chia-Hung|Lee, Tzong-Yi|Huang, Hsien-Da', 'Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.|Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsin-Chu 300, Taiwan.', '-|-|-|-|-|-|-', 0, '3 Untranslated Regions|5 Untranslated Regions|Gene Expression Regulation|Humans|MicroRNAs|Protein Biosynthesis|RNA, Messenger', 'Journal Article', '10.1186/1471-2105-12-300', '21791068', 'MicroRNAs (miRNAs) are small non-coding RNA molecules that are ~22-nt-long sequences capable of suppressing protein synthesis. Previous research has suggested that miRNAs regulate 30% or more of the human protein-coding genes. The aim of this work is to consider various analyzing scenarios in the identification of miRNA-target interactions, as well as to provide an integrated system that will aid in facilitating investigation on the influence of miRNA targets by alternative splicing and the biological function of miRNAs in biological pathways.'),
(94460, 2011, 'bmc', 'Deterministic and stochastic population-level simulations of an artificial lac operon genetic network', 'Stamatakis, Michail|Zygourakis, Kyriacos', 'Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA. mstam@alumni.rice.edu|Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX 77005, USA. mstam@alumni.rice.edu', 'United States|United States', 0, 'Computer Simulation|Escherichia coli|Feedback|Gene Expression Regulation|Gene Regulatory Networks|Humans|Lac Operon|Monte Carlo Method|Stochastic Processes', 'Journal Article', '10.1186/1471-2105-12-301', '21791088', 'The lac operon genetic switch is considered as a paradigm of genetic regulation. This system has a positive feedback loop due to the LacY permease boosting its own production by the facilitated transport of inducer into the cell and the subsequent de-repression of the lac operon genes. Previously, we have investigated the effect of stochasticity in an artificial lac operon network at the single cell level by comparing corresponding deterministic and stochastic kinetic models.'),
(94461, 2011, 'bmc', 'Bayesian semi-supervised classification of bacterial samples using MLST databases', 'Cheng, Lu|Connor, Thomas R|Aanensen, David M|Spratt, Brian G|Corander, Jukka', 'Department of Mathematics and statistics, P,O,Box 68, University of Helsinki, 00014, Finland.|Department of Mathematics and statistics, P,O,Box 68, University of Helsinki, 00014, Finland.|Department of Mathematics and statistics, P,O,Box 68, University of Helsinki, 00014, Finland.|Department of Mathematics and statistics, P,O,Box 68, University of Helsinki, 00014, Finland.|Department of Mathematics and statistics, P,O,Box 68, University of Helsinki, 00014, Finland.', 'Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Bacteria|Bayes Theorem|Databases, Genetic|Humans|Multilocus Sequence Typing|Software', 'Journal Article', '10.1186/1471-2105-12-302', '21791094', 'Worldwide effort on sampling and characterization of molecular variation within a large number of human and animal pathogens has lead to the emergence of multi-locus sequence typing (MLST) databases as an important tool for studying the epidemiology and evolution of pathogens. Many of these databases are currently harboring several thousands of multi-locus DNA sequence types (STs) enriched with metadata over traits such as serotype, antibiotic resistance, host organism etc of the isolates. Curators of the databases have thus the possibility of dividing the pathogen populations into subsets representing different evolutionary lineages, geographically associated groups, or other subpopulations, which are defined in terms of molecular similarities and dissimilarities residing within a database. When combined with the existing metadata, such subsets may provide invaluable information for assessing the position of a new set of isolates in relation to the whole pathogen population.'),
(94462, 2011, 'bmc', 'Prototype semantic infrastructure for automated small molecule classification and annotation in lipidomics', 'Chepelev, Leonid L|Riazanov, Alexandre|Kouznetsov, Alexandre|Low, Hong Sang|Dumontier, Michel|Baker, Christopher J O', 'Department of Biology, Carleton University, Ottawa, Canada.|Department of Biology, Carleton University, Ottawa, Canada.|Department of Biology, Carleton University, Ottawa, Canada.|Department of Biology, Carleton University, Ottawa, Canada.|Department of Biology, Carleton University, Ottawa, Canada.|Department of Biology, Carleton University, Ottawa, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada', 20, 'Databases, Factual|Humans|Lipid Metabolism|Lipids|Proteins|Semantics', 'Journal Article', '10.1186/1471-2105-12-303', '21791100', 'The development of high-throughput experimentation has led to astronomical growth in biologically relevant lipids and lipid derivatives identified, screened, and deposited in numerous online databases. Unfortunately, efforts to annotate, classify, and analyze these chemical entities have largely remained in the hands of human curators using manual or semi-automated protocols, leaving many novel entities unclassified. Since chemical function is often closely linked to structure, accurate structure-based classification and annotation of chemical entities is imperative to understanding their functionality.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(94463, 2011, 'bmc', 'Applications of the pipeline environment for visual informatics and genomics computations', 'Dinov, Ivo D|Torri, Federica|Macciardi, Fabio|Petrosyan, Petros|Liu, Zhizhong|Zamanyan, Alen|Eggert, Paul|Pierce, Jonathan|Genco, Alex|Knowles, James A|Clark, Andrew P|Van Horn, John D|Ames, Joseph|Kesselman, Carl|Toga, Arthur W', 'Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, USA.|Laboratory of Neuro Imaging (LONI), University of California, Los Angeles, Los Angeles, CA 90095, 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|United States|United States|United States', 0, 'Computational Biology|Genomics|Informatics|Medical Informatics Applications|Software', 'Journal Article', '10.1186/1471-2105-12-304', '21791102', 'Contemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data analysis protocols.'),
(94464, 2011, 'bmc', 'IsoformEx: isoform level gene expression estimation using weighted non-negative least squares from mRNA-Seq data', 'Kim, Hyunsoo|Bi, Yingtao|Pal, Sharmistha|Gupta, Ravi|Davuluri, Ramana V', 'Center for Systems and Computational Biology, The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104-4268, USA.|Center for Systems and Computational Biology, The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104-4268, USA.|Center for Systems and Computational Biology, The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104-4268, USA.|Center for Systems and Computational Biology, The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104-4268, USA.|Center for Systems and Computational Biology, The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104-4268, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Cell Line, Tumor|Exons|Gene Expression Profiling|Humans|Least-Squares Analysis|Protein Isoforms|RNA, Messenger|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-305', '21794104', 'mRNA-Seq technology has revolutionized the field of transcriptomics for identification and quantification of gene transcripts not only at gene level but also at isoform level. Estimating the expression levels of transcript isoforms from mRNA-Seq data is a challenging problem due to the presence of constitutive exons.'),
(94465, 2011, 'bmc', 'Expression cartography of human tissues using self organizing maps', 'Wirth, Henry|Löffler, Markus|von Bergen, Martin|Binder, Hans', 'Interdisciplinary Centre for Bioinformatics of Leipzig University, D-4107 Leipzig, Härtelstr. 16-18, Germany. henry.wirth@ufz.de|Interdisciplinary Centre for Bioinformatics of Leipzig University, D-4107 Leipzig, Härtelstr. 16-18, Germany. henry.wirth@ufz.de|Interdisciplinary Centre for Bioinformatics of Leipzig University, D-4107 Leipzig, Härtelstr. 16-18, Germany. henry.wirth@ufz.de|Interdisciplinary Centre for Bioinformatics of Leipzig University, D-4107 Leipzig, Härtelstr. 16-18, Germany. henry.wirth@ufz.de', 'Germany|Germany|Germany|Germany', 49, 'Algorithms|Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Genome, Human|Humans|Organ Specificity|Time Factors', 'Journal Article', '10.1186/1471-2105-12-306', '21794127', 'Parallel high-throughput microarray and sequencing experiments produce vast quantities of multidimensional data which must be arranged and analyzed in a concerted way. One approach to addressing this challenge is the machine learning technique known as self organizing maps (SOMs). SOMs enable a parallel sample- and gene-centered view of genomic data combined with strong visualization and second-level analysis capabilities. The paper aims at bridging the gap between the potency of SOM-machine learning to reduce dimension of high-dimensional data on one hand and practical applications with special emphasis on gene expression analysis on the other hand.'),
(94466, 2011, 'bmc', 'The projection score--an evaluation criterion for variable subset selection in PCA visualization', 'Fontes, Magnus|Soneson, Charlotte', 'Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. fontes@maths.lth.se|Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. fontes@maths.lth.se', 'Sweden|Sweden', 9, 'Algorithms|Gene Expression Profiling|Humans|Leukemia|Lung Neoplasms|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Software', 'Journal Article', '10.1186/1471-2105-12-307', '21798031', 'In many scientific domains, it is becoming increasingly common to collect high-dimensional data sets, often with an exploratory aim, to generate new and relevant hypotheses. The exploratory perspective often makes statistically guided visualization methods, such as Principal Component Analysis (PCA), the methods of choice. However, the clarity of the obtained visualizations, and thereby the potential to use them to formulate relevant hypotheses, may be confounded by the presence of the many non-informative variables. For microarray data, more easily interpretable visualizations are often obtained by filtering the variable set, for example by removing the variables with the smallest variances or by only including the variables most highly related to a specific response. The resulting visualization may depend heavily on the inclusion criterion, that is, effectively the number of retained variables. To our knowledge, there exists no objective method for determining the optimal inclusion criterion in the context of visualization.'),
(94467, 2011, 'bmc', 'Visualizing meta-features in proteomic maps', 'Giannopoulou, Eugenia G|Lepouras, George|Manolakos, Elias S', 'HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY 10021, USA. eug2002@med.cornell.edu|HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY 10021, USA. eug2002@med.cornell.edu|HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY 10021, USA. eug2002@med.cornell.edu', 'United States|United States|United States', 1, 'Mass Spectrometry|Phosphorylation|Protein Processing, Post-Translational|Proteins|Proteomics|Software', 'Journal Article', '10.1186/1471-2105-12-308', '21798033', 'The steps of a high-throughput proteomics experiment include the separation, differential expression and mass spectrometry-based identification of proteins. However, the last and more challenging step is inferring the biological role of the identified proteins through their association with interaction networks, biological pathways, analysis of the effect of post-translational modifications, and other protein-related information.'),
(94468, 2011, 'bmc', 'Application of an efficient Bayesian discretization method to biomedical data', 'Lustgarten, Jonathan L|Visweswaran, Shyam|Gopalakrishnan, Vanathi|Cooper, Gregory F', 'Department of Biomedical Informatics and the Intelligent Systems Program, University of Pittsburgh, Suite M-183 Vale, Parkvale Building, 200 Meyran Avenue, Pittsburgh, PA 15260, USA.|Department of Biomedical Informatics and the Intelligent Systems Program, University of Pittsburgh, Suite M-183 Vale, Parkvale Building, 200 Meyran Avenue, Pittsburgh, PA 15260, USA.|Department of Biomedical Informatics and the Intelligent Systems Program, University of Pittsburgh, Suite M-183 Vale, Parkvale Building, 200 Meyran Avenue, Pittsburgh, PA 15260, USA.|Department of Biomedical Informatics and the Intelligent Systems Program, University of Pittsburgh, Suite M-183 Vale, Parkvale Building, 200 Meyran Avenue, Pittsburgh, PA 15260, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Bayes Theorem|Data Mining|Gene Expression Profiling|Proteomics', 'Journal Article', '10.1186/1471-2105-12-309', '21798039', 'Several data mining methods require data that are discrete, and other methods often perform better with discrete data. We introduce an efficient Bayesian discretization (EBD) method for optimal discretization of variables that runs efficiently on high-dimensional biomedical datasets. The EBD method consists of two components, namely, a Bayesian score to evaluate discretizations and a dynamic programming search procedure to efficiently search the space of possible discretizations. We compared the performance of EBD to Fayyad and Iranis (FI) discretization method, which is commonly used for discretization.'),
(94469, 2011, 'bmc', 'Consistent metagenes from cancer expression profiles yield agent specific predictors of chemotherapy response', 'Li, Qiyuan|Eklund, Aron C|Birkbak, Nicolai J|Desmedt, Christine|Haibe-Kains, Benjamin|Sotiriou, Christos|Symmans, W Fraser|Pusztai, Lajos|Brunak, Søren|Richardson, Andrea L|Szallasi, Zoltan', 'Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.|Center for Biological Sequence Analysis, Department of Systems Biolology, Technical University of Denmark, 2800 Lyngby, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 2, 'Adenocarcinoma|Adenocarcinoma of Lung|Antineoplastic Agents|Biomarkers, Tumor|Breast Neoplasms|Cohort Studies|Estrogen Receptor alpha|Female|Gene Expression Profiling|Humans|Lung Neoplasms|Neoadjuvant Therapy|Neoplasms|Ovarian Neoplasms|Prognosis|Receptor, ErbB-2', 'Journal Article', '10.1186/1471-2105-12-310', '21798043', 'Genome scale expression profiling of human tumor samples is likely to yield improved cancer treatment decisions. However, identification of clinically predictive or prognostic classifiers can be challenging when a large number of genes are measured in a small number of tumors.'),
(94470, 2011, 'bmc', 'Rigorous assessment and integration of the sequence and structure based features to predict hot spots', 'Chen, Ruoying|Chen, Wenjing|Yang, Sixiao|Wu, Di|Wang, Yong|Tian, Yingjie|Shi, Yong', '1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.|1College of Life Sciences, Graduate University of Chinese Academy ofSciences, Beijing 100049, China.', 'China|China|China|China|China|China|China', 8, 'Amino Acid Sequence|Animals|Artificial Intelligence|Databases, Protein|Evolution, Molecular|Hydrogen Bonding|Mice|Models, Molecular|Protein Binding|Proteins|Software|Support Vector Machine', 'Journal Article', '10.1186/1471-2105-12-311', '21798070', 'Systematic mutagenesis studies have shown that only a few interface residues termed hot spots contribute significantly to the binding free energy of protein-protein interactions. Therefore, hot spots prediction becomes increasingly important for well understanding the essence of proteins interactions and helping narrow down the search space for drug design. Currently many computational methods have been developed by proposing different features. However comparative assessment of these features and furthermore effective and accurate methods are still in pressing need.'),
(94471, 2011, 'bmc', 'Comprehensive, atomic-level characterization of structurally characterized protein-protein interactions: the PICCOLO database', 'Bickerton, George R|Higueruelo, Alicia P|Blundell, Tom L', 'Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK. grbickerton@dundee.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK. grbickerton@dundee.ac.uk|Department of Biochemistry, University of Cambridge, Cambridge, CB2 1GA, UK. grbickerton@dundee.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 44, 'Databases, Protein|Humans|Models, Molecular|Protein Interaction Mapping|Proteins|Software', 'Journal Article', '10.1186/1471-2105-12-313', '21801404', 'Structural studies are increasingly providing huge amounts of information on multi-protein assemblies. Although a complete understanding of cellular processes will be dependent on an explicit characterization of the intermolecular interactions that underlie these assemblies and mediate molecular recognition, these are not well described by standard representations.'),
(94472, 2011, 'bmc', 'Open-target sparse sensing of biological agents using DNA microarray', 'Mohtashemi, Mojdeh|Walburger, David K|Peterson, Matthew W|Sutton, Felicia N|Skaer, Haley B|Diggans, James C', 'Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org|Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org|Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org|Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org|Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org|Emerging & Disruptive Technologies, The MITRE Corporation, McLean, Virginia, USA. mojdeh@mitre.org', 'United States|United States|United States|United States|United States|United States', 1, 'Bacteria|Computer Simulation|Least-Squares Analysis|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Regression Analysis|Sensitivity and Specificity', 'Journal Article', '10.1186/1471-2105-12-314', '21801424', 'Current biosensors are designed to target and react to specific nucleic acid sequences or structural epitopes. These target-specific platforms require creation of new physical capture reagents when new organisms are targeted. An open-target approach to DNA microarray biosensing is proposed and substantiated using laboratory generated data. The microarray consisted of 12,900 25 bp oligonucleotide capture probes derived from a statistical model trained on randomly selected genomic segments of pathogenic prokaryotic organisms. Open-target detection of organisms was accomplished using a reference library of hybridization patterns for three test organisms whose DNA sequences were not included in the design of the microarray probes.'),
(94473, 2011, 'bmc', 'Link-based quantitative methods to identify differentially coexpressed genes and gene pairs', 'Yu, Hui|Liu, Bao-Hong|Ye, Zhi-Qiang|Li, Chun|Li, Yi-Xue|Li, Yuan-Yuan', 'Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.|Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.|Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.|Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.|Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.|Bioinformatics Center, Key Laboratory of Systems Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 320 Yueyang Road, Shanghai 200031, P.R. China.', 'China|China|China|China|China|China', 66, 'Algorithms|Diabetes Mellitus, Type 2|Expressed Sequence Tags|Gene Expression Profiling|Gene Expression Regulation|Humans|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-12-315', '21806838', 'Differential coexpression analysis (DCEA) is increasingly used for investigating the global transcriptional mechanisms underlying phenotypic changes. Current DCEA methods mostly adopt a gene connectivity-based strategy to estimate differential coexpression, which is characterized by comparing the numbers of gene neighbors in different coexpression networks. Although it simplifies the calculation, this strategy mixes up the identities of different coexpression neighbors of a gene, and fails to differentiate significant differential coexpression changes from those trivial ones. Especially, the correlation-reversal is easily missed although it probably indicates remarkable biological significance.'),
(94474, 2011, 'bmc', 'GSV: a web-based genome synteny viewer for customized data', 'Revanna, Kashi V|Chiu, Chi-Chen|Bierschank, Ezekiel|Dong, Qunfeng', 'Department of Biological Sciences, University of North Texas, Denton, Texas 76203, USA.|Department of Biological Sciences, University of North Texas, Denton, Texas 76203, USA.|Department of Biological Sciences, University of North Texas, Denton, Texas 76203, USA.|Department of Biological Sciences, University of North Texas, Denton, Texas 76203, USA.', 'United States|United States|United States|United States', 31, 'Genome|Genomics|Internet|Sequence Analysis, DNA|Software|Synteny|User-Computer Interface', 'Journal Article', '10.1186/1471-2105-12-316', '21810250', 'The analysis of genome synteny is a common practice in comparative genomics. With the advent of DNA sequencing technologies, individual biologists can rapidly produce their genomic sequences of interest. Although web-based synteny visualization tools are convenient for biologists to use, none of the existing ones allow biologists to upload their own data for analysis.'),
(94475, 2011, 'bmc', 'NoD: a Nucleolar localization sequence detector for eukaryotic and viral proteins', 'Scott, Michelle S|Troshin, Peter V|Barton, Geoffrey J', 'Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. michelle@compbio.dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. michelle@compbio.dundee.ac.uk|Division of Biological Chemistry and Drug Discovery, College of Life Sciences, University of Dundee, Dow Street, Dundee DD1 5EH, UK. michelle@compbio.dundee.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 70, 'Amino Acid Motifs|Amino Acid Sequence|Animals|Cell Nucleolus|Humans|Neural Networks (Computer)|Nuclear Proteins|Proteomics|Regulatory Sequences, Nucleic Acid|Viral Proteins', 'Journal Article', '10.1186/1471-2105-12-317', '21812952', 'Nucleolar localization sequences (NoLSs) are short targeting sequences responsible for the localization of proteins to the nucleolus. Given the large number of proteins experimentally detected in the nucleolus and the central role of this subnuclear compartment in the cell, NoLSs are likely to be important regulatory elements controlling cellular traffic. Although many proteins have been reported to contain NoLSs, the systematic characterization of this group of targeting motifs has only recently been carried out.'),
(94476, 2011, 'bmc', 'Mining for genotype-phenotype relations in Saccharomyces using partial least squares', 'Mehmood, Tahir|Martens, Harald|Saebø, Solve|Warringer, Jonas|Snipen, Lars', 'Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no|Biostatistics, Department of Chemistry, Biotechnology and Food Sciences, Norwegian University of Life Sciences, Norway. tahir.mehmood@umb.no', 'Norway|Norway|Norway|Norway|Norway', 18, 'Evolution, Molecular|Genomics|Genotype|Least-Squares Analysis|Phenotype|Phylogeny|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-318', '21812956', 'Multivariate approaches are important due to their versatility and applications in many fields as it provides decisive advantages over univariate analysis in many ways. Genome wide association studies are rapidly emerging, but approaches in hand pay less attention to multivariate relation between genotype and phenotype. We introduce a methodology based on a BLAST approach for extracting information from genomic sequences and Soft- Thresholding Partial Least Squares (ST-PLS) for mapping genotype-phenotype relations.'),
(94477, 2011, 'bmc', 'RNAexinv: An extended inverse RNA folding from shape and physical attributes to sequences', 'Avihoo, Assaf|Churkin, Alexander|Barash, Danny', 'Department of Computer Science, Ben-Gurion University, 84105 Beer Sheva, Israel.|Department of Computer Science, Ben-Gurion University, 84105 Beer Sheva, Israel.|Department of Computer Science, Ben-Gurion University, 84105 Beer Sheva, Israel.', 'Israel|Israel|Israel', 27, 'Algorithms|Base Sequence|Molecular Sequence Data|Nucleic Acid Conformation|RNA|RNA Folding|Software|Thermodynamics', 'Journal Article', '10.1186/1471-2105-12-319', '21813013', 'RNAexinv is an interactive java application that performs RNA sequence design, constrained to yield a specific RNA shape and physical attributes. It is an extended inverse RNA folding program with the rationale behind that the generated sequences should not only fold into a desired structure, but they should also exhibit favorable attributes such as thermodynamic stability and mutational robustness. RNAexinv considers not only the secondary structure in order to design sequences, but also the mutational robustness and the minimum free energy. The sequences that are generated may not fully conform with the given RNA secondary structure, but they will strictly conform with the RNA shape of the given secondary structure and thereby take into consideration the recommended values of thermodynamic stability and mutational robustness that are provided.'),
(94478, 2011, 'bmc', 'The volatile compound BinBase mass spectral database', 'Skogerson, Kirsten|Wohlgemuth, Gert|Barupal, Dinesh K|Fiehn, Oliver', 'Genome Center, University of California, Davis, CA 95616, USA.|Genome Center, University of California, Davis, CA 95616, USA.|Genome Center, University of California, Davis, CA 95616, USA.|Genome Center, University of California, Davis, CA 95616, USA.', 'United States|United States|United States|United States', 101, 'Algorithms|Databases, Factual|Gas Chromatography-Mass Spectrometry|Mass Spectrometry|Oils, Volatile|Plant Oils|Plants|Software|User-Computer Interface|Volatile Organic Compounds', 'Journal Article', '10.1186/1471-2105-12-321', '21816034', 'Volatile compounds comprise diverse chemical groups with wide-ranging sources and functions. These compounds originate from major pathways of secondary metabolism in many organisms and play essential roles in chemical ecology in both plant and animal kingdoms. In past decades, sampling methods and instrumentation for the analysis of complex volatile mixtures have improved, however, design and implementation of database tools to process and store the complex datasets have lagged behind.'),
(94479, 2011, 'bmc', 'Strategies for aggregating gene expression data: the collapseRows R function', 'Miller, Jeremy A|Cai, Chaochao|Langfelder, Peter|Geschwind, Daniel H|Kurian, Sunil M|Salomon, Daniel R|Horvath, Steve', 'Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.|Interdepartmental Program for Neuroscience, UCLA, Los Angeles, California, USA.', 'United States|United States|United States|United States|United States|United States|United States', 179, 'Animals|Blood|Brain|Gene Expression Profiling|Gene Expression Regulation|Humans|Meta-Analysis as Topic|Mice|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1186/1471-2105-12-322', '21816037', 'Genomic and other high dimensional analyses often require one to summarize multiple related variables by a single representative. This task is also variously referred to as collapsing, combining, reducing, or aggregating variables. Examples include summarizing several probe measurements corresponding to a single gene, representing the expression profiles of a co-expression module by a single expression profile, and aggregating cell-type marker information to de-convolute expression data. Several standard statistical summary techniques can be used, but network methods also provide useful alternative methods to find representatives. Currently few collapsing functions are developed and widely applied.'),
(94480, 2011, 'bmc', 'RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome', 'Li, Bo|Dewey, Colin N', 'Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA.|Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI, USA.', 'United States|United States', 6078, 'Animals|Computer Simulation|Gene Expression Profiling|Humans|Mice|Protein Isoforms|RNA|Sequence Analysis, RNA|Software', 'Journal Article', '10.1186/1471-2105-12-323', '21816040', 'RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments.'),
(94481, 2011, 'bmc', 'rapmad: Robust analysis of peptide microarray data', 'Renard, Bernhard Y|Löwer, Martin|Kühne, Yvonne|Reimer, Ulf|Rothermel, Andrée|Türeci, Ozlem|Castle, John C|Sahin, Ugur', 'The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.|The Institute for Translational Oncology and Immunology (TrOn), 55131 Mainz, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 14, 'Algorithms|Biomarkers, Tumor|Humans|Neoplasms|Protein Array Analysis|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-12-324', '21816082', 'Peptide microarrays offer an enormous potential as a screening tool for peptidomics experiments and have recently seen an increased field of application ranging from immunological studies to systems biology. By allowing the parallel analysis of thousands of peptides in a single run they are suitable for high-throughput settings. Since data characteristics of peptide microarrays differ from DNA oligonucleotide microarrays, computational methods need to be tailored to these specifications to allow a robust and automated data analysis. While follow-up experiments can ensure the specificity of results, sensitivity cannot be recovered in later steps. Providing sensitivity is thus a primary goal of data analysis procedures. To this end we created rapmad (Robust Alignment of Peptide MicroArray Data), a novel computational tool implemented in R.'),
(94482, 2011, 'bmc', 'A regression system for estimation of errors introduced by confocal imaging into gene expression data in situ', 'Myasnikova, Ekaterina|Surkova, Svetlana|Stein, Grigory|Pisarev, Andrei|Samsonova, Maria', 'Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia. myasnikova@spbcas.ru|Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia. myasnikova@spbcas.ru|Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia. myasnikova@spbcas.ru|Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia. myasnikova@spbcas.ru|Department of Computational Biology, Center for Advanced Studies, St.Petersburg State Polytechnical University, St.Petersburg, 195251, Russia. myasnikova@spbcas.ru', '-|-|-|-|-', 2, 'Animals|Blastoderm|Drosophila Proteins|Drosophila melanogaster|Gene Expression Profiling|Microscopy, Confocal|Regression Analysis|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-12-320', '21816093', 'Accuracy of the data extracted from two-dimensional confocal images is limited due to experimental errors that arise in course of confocal scanning. The common way to reduce the noise in images is sequential scanning of the same specimen several times with the subsequent averaging of multiple frames. Attempts to increase the dynamical range of an image by setting too high values of microscope PMT parameters may cause clipping of single frames and introduce errors into the data extracted from the averaged images. For the estimation and correction of this kind of errors a method based on censoring technique (Myasnikova et al., 2009) is used. However, the method requires the availability of all the confocal scans along with the averaged image, which is normally not provided by the standard scanning procedure.'),
(94483, 2011, 'bmc', 'How the gene ontology evolves', 'Leonelli, Sabina|Diehl, Alexander D|Christie, Karen R|Harris, Midori A|Lomax, Jane', 'ESRC Centre for Genomics in Society, University of Exeter, EX4 4PJ Exeter, UK. s.leonelli@exeter.ac.uk|ESRC Centre for Genomics in Society, University of Exeter, EX4 4PJ Exeter, UK. s.leonelli@exeter.ac.uk|ESRC Centre for Genomics in Society, University of Exeter, EX4 4PJ Exeter, UK. s.leonelli@exeter.ac.uk|ESRC Centre for Genomics in Society, University of Exeter, EX4 4PJ Exeter, UK. s.leonelli@exeter.ac.uk|ESRC Centre for Genomics in Society, University of Exeter, EX4 4PJ Exeter, UK. s.leonelli@exeter.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 30, 'Genes|Genetics|Knowledge Bases|Terminology as Topic', 'Journal Article', '10.1186/1471-2105-12-325', '21819553', 'Maintaining a bio-ontology in the long term requires improving and updating its contents so that it adequately captures what is known about biological phenomena. This paper illustrates how these processes are carried out, by studying the ways in which curators at the Gene Ontology have hitherto incorporated new knowledge into their resource.'),
(94484, 2011, 'bmc', 'Domain architecture conservation in orthologs', 'Forslund, Kristoffer|Pekkari, Isabella|Sonnhammer, Erik L L', 'Stockholm Bioinformatics Centre, Science for Life Laboratory, Box 1031, Solna, 17121 Sweden.|Stockholm Bioinformatics Centre, Science for Life Laboratory, Box 1031, Solna, 17121 Sweden.|Stockholm Bioinformatics Centre, Science for Life Laboratory, Box 1031, Solna, 17121 Sweden.', 'Sweden|Sweden|Sweden', 30, 'Amino Acid Sequence|Animals|Conserved Sequence|Evolution, Molecular|Humans|Protein Structure, Tertiary|Proteins', 'Journal Article', '10.1186/1471-2105-12-326', '21819573', 'As orthologous proteins are expected to retain function more often than other homologs, they are often used for functional annotation transfer between species. However, ortholog identification methods do not take into account changes in domain architecture, which are likely to modify a proteins function. By domain architecture we refer to the sequential arrangement of domains along a protein sequence.To assess the level of domain architecture conservation among orthologs, we carried out a large-scale study of such events between human and 40 other species spanning the entire evolutionary range. We designed a score to measure domain architecture similarity and used it to analyze differences in domain architecture conservation between orthologs and paralogs relative to the conservation of primary sequence. We also statistically characterized the extents of different types of domain swapping events across pairs of orthologs and paralogs.'),
(94485, 2011, 'bmc', 'NETGEM: Network Embedded Temporal GEnerative Model for gene expression data', 'Jethava, Vinay|Bhattacharyya, Chiranjib|Dubhashi, Devdatt|Vemuri, Goutham N', 'Department of Computer Science and Engineering, Chalmers University ofTechnology, Göteborg, Sweden.|Department of Computer Science and Engineering, Chalmers University ofTechnology, Göteborg, Sweden.|Department of Computer Science and Engineering, Chalmers University ofTechnology, Göteborg, Sweden.|Department of Computer Science and Engineering, Chalmers University ofTechnology, Göteborg, Sweden.', 'Sweden|Sweden|Sweden|Sweden', 8, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Models, Statistical|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-327', '21824426', 'Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation.'),
(94486, 2011, 'bmc', 'Development of a classification scheme for disease-related enzyme information', 'Söhngen, Carola|Chang, Antje|Schomburg, Dietmar', 'Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry Langer Kamp 19 B, 38106 Braunschweig, Germany.|Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry Langer Kamp 19 B, 38106 Braunschweig, Germany.|Technische Universität Braunschweig, Department of Bioinformatics and Biochemistry Langer Kamp 19 B, 38106 Braunschweig, Germany.', 'Germany|Germany|Germany', 13, 'Artificial Intelligence|Data Mining|Databases, Protein|Disease|HIV Infections|Humans|Neoplasms|PubMed', 'Journal Article', '10.1186/1471-2105-12-329', '21827651', 'BRENDA (BRaunschweig ENzyme DAtabase, http://www.brenda-enzymes.org) is a major resource for enzyme related information. First and foremost, it provides data which are manually curated from the primary literature. DRENDA (Disease RElated ENzyme information DAtabase) complements BRENDA with a focus on the automatic search and categorization of enzyme and disease related information from title and abstracts of primary publications. In a two-step procedure DRENDA makes use of text mining and machine learning methods.'),
(94487, 2011, 'bmc', 'Randomization techniques for assessing the significance of gene periodicity results', 'Kallio, Aleksi|Vuokko, Niko|Ojala, Markus|Haiminen, Niina|Mannila, Heikki', 'Research Environment Services, CSC-IT Center for Science Ltd, P.O. Box 405, Espoo 02101, Finland. aleksi.kallio@helsinki.fi|Research Environment Services, CSC-IT Center for Science Ltd, P.O. Box 405, Espoo 02101, Finland. aleksi.kallio@helsinki.fi|Research Environment Services, CSC-IT Center for Science Ltd, P.O. Box 405, Espoo 02101, Finland. aleksi.kallio@helsinki.fi|Research Environment Services, CSC-IT Center for Science Ltd, P.O. Box 405, Espoo 02101, Finland. aleksi.kallio@helsinki.fi|Research Environment Services, CSC-IT Center for Science Ltd, P.O. Box 405, Espoo 02101, Finland. aleksi.kallio@helsinki.fi', 'Finland|Finland|Finland|Finland|Finland', 7, 'Circadian Clocks|Cluster Analysis|Data Mining|Gene Expression Profiling|Gene Expression Regulation|Oligonucleotide Array Sequence Analysis|Periodicity', 'Journal Article', '10.1186/1471-2105-12-330', '21827656', 'Modern high-throughput measurement technologies such as DNA microarrays and next generation sequencers produce extensive datasets. With large datasets the emphasis has been moving from traditional statistical tests to new data mining methods that are capable of detecting complex patterns, such as clusters, regulatory networks, or time series periodicity. Study of periodic gene expression is an interesting research question that also is a good example of challenges involved in the analysis of high-throughput data in general. Unlike for classical statistical tests, the distribution of test statistic for data mining methods cannot be derived analytically.'),
(94488, 2011, 'bmc', 'Genome-wide algorithm for detecting CNV associations with diseases', 'Xu, Yaji|Peng, Bo|Fu, Yunxin|Amos, Christopher I', 'Department of Epidemiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St,, Houston, Texas 77030, USA.|Department of Epidemiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St,, Houston, Texas 77030, USA.|Department of Epidemiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St,, Houston, Texas 77030, USA.|Department of Epidemiology, The University of Texas MD Anderson Cancer Center, 1155 Pressler St,, Houston, Texas 77030, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|DNA Copy Number Variations|Disease|Genome, Human|Genome-Wide Association Study|Humans|Melanoma|Models, Statistical|Polymorphism, Single Nucleotide|Regression Analysis|Sensitivity and Specificity|Software', 'Journal Article', '10.1186/1471-2105-12-331', '21827692', 'SNP genotyping arrays have been developed to characterize single-nucleotide polymorphisms (SNPs) and DNA copy number variations (CNVs). Nonparametric and model-based statistical algorithms have been developed to detect CNVs from SNP data using the marker intensities. However, these algorithms lack specificity to detect small CNVs owing to the high false positive rate when calling CNVs based on the intensity values. Therefore, the resulting association tests lack power even if the CNVs affecting disease risk are common. An alternative procedure called PennCNV uses information from both the marker intensities as well as the genotypes and therefore has increased sensitivity.'),
(94489, 2011, 'bmc', 'Classifying short genomic fragments from novel lineages using composition and homology', 'Parks, Donovan H|MacDonald, Norman J|Beiko, Robert G', 'Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, Nova Scotia, Canada.|Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, Nova Scotia, Canada.|Faculty of Computer Science, Dalhousie University, 6050 University Avenue, Halifax, Nova Scotia, Canada.', 'Canada|Canada|Canada', 0, 'Algorithms|Archaea|Bacteria|Base Composition|Bayes Theorem|Ice Cover|Metagenomics|Sensitivity and Specificity|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1186/1471-2105-12-328', '21827705', 'The assignment of taxonomic attributions to DNA fragments recovered directly from the environment is a vital step in metagenomic data analysis. Assignments can be made using rank-specific classifiers, which assign reads to taxonomic labels from a predetermined level such as named species or strain, or rank-flexible classifiers, which choose an appropriate taxonomic rank for each sequence in a data set. The choice of rank typically depends on the optimal model for a given sequence and on the breadth of taxonomic groups seen in a set of close-to-optimal models. Homology-based (e.g., LCA) and composition-based (e.g., PhyloPythia, TACOA) rank-flexible classifiers have been proposed, but there is at present no hybrid approach that utilizes both homology and composition.'),
(94490, 2011, 'bmc', 'ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs', 'Sanders, Marijn P A|Fleuren, Wilco W M|Verhoeven, Stefan|van den Beld, Sven|Alkema, Wynand|de Vlieg, Jacob|Klomp, Jan P G', 'Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.|Computational Drug Discovery Group, Radboud University NijmegenMedical Centre, Geert Grooteplein, Nijmegen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 16, 'Animals|Entropy|Humans|Ligands|Models, Molecular|Protein Binding|Receptors, G-Protein-Coupled|Sequence Alignment', 'Journal Article', '10.1186/1471-2105-12-332', '21831265', 'G-protein coupled receptors (GPCRs) are involved in many different physiological processes and their function can be modulated by small molecules which bind in the transmembrane (TM) domain. Because of their structural and sequence conservation, the TM domains are often used in bioinformatics approaches to first create a multiple sequence alignment (MSA) and subsequently identify ligand binding positions. So far methods have been developed to predict the common ligand binding residue positions for class A GPCRs.'),
(94491, 2011, 'bmc', 'Efficient counting of k-mers in DNA sequences using a bloom filter', 'Melsted, Páll|Pritchard, Jonathan K', 'Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA. pmelsted@gmail.com|Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA. pmelsted@gmail.com', 'United States|United States', 0, 'Algorithms|Computational Biology|Computers|HapMap Project|Humans|Probability|Sequence Analysis, DNA|Software', 'Journal Article', '10.1186/1471-2105-12-333', '21831268', 'Counting k-mers (substrings of length k in DNA sequence data) is an essential component of many methods in bioinformatics, including for genome and transcriptome assembly, for metagenomic sequencing, and for error correction of sequence reads. Although simple in principle, counting k-mers in large modern sequence data sets can easily overwhelm the memory capacity of standard computers. In current data sets, a large fraction-often more than 50%-of the storage capacity may be spent on storing k-mers that contain sequencing errors and which are typically observed only a single time in the data. These singleton k-mers are uninformative for many algorithms without some kind of error correction.'),
(94492, 2011, 'bmc', 'Implementation of 3D spatial indexing and compression in a large-scale molecular dynamics simulation database for rapid atomic contact detection', 'Toofanny, Rudesh D|Simms, Andrew M|Beck, David A C|Daggett, Valerie', 'Department of Bioengineering, University of Washington, Seattle, Washington 98195-5013, USA.|Department of Bioengineering, University of Washington, Seattle, Washington 98195-5013, USA.|Department of Bioengineering, University of Washington, Seattle, Washington 98195-5013, USA.|Department of Bioengineering, University of Washington, Seattle, Washington 98195-5013, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Data Compression|Databases, Protein|Molecular Dynamics Simulation|Proteins|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1186/1471-2105-12-334', '21831299', 'Molecular dynamics (MD) simulations offer the ability to observe the dynamics and interactions of both whole macromolecules and individual atoms as a function of time. Taken in context with experimental data, atomic interactions from simulation provide insight into the mechanics of protein folding, dynamics, and function. The calculation of atomic interactions or contacts from an MD trajectory is computationally demanding and the work required grows exponentially with the size of the simulation system. We describe the implementation of a spatial indexing algorithm in our multi-terabyte MD simulation database that significantly reduces the run-time required for discovery of contacts. The approach is applied to the Dynameomics project data. Spatial indexing, also known as spatial hashing, is a method that divides the simulation space into regular sized bins and attributes an index to each bin. Since, the calculation of contacts is widely employed in the simulation field, we also use this as the basis for testing compression of data tables. We investigate the effects of compression of the trajectory coordinate tables with different options of data and index compression within MS SQL SERVER 2008.');
