INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73670, 2007, 'bio', 'Intersession reproducibility of mass spectrometry profiles and its effect on accuracy of multivariate classification models', 'Pelikan, Richard|Bigbee, William L|Malehorn, David|Lyons-Weiler, James|Hauskrecht, Milos', 'Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.|Department of Computer Science, Intelligent Systems Program, University of Pittsburgh Cancer Institute and Genomics and Proteomics Core Laboratories, University of Pittsburgh, Pittsburgh, PA 15260, USA.', 'United States|United States|United States|United States|United States', 11, 'Adult|Aged|Aged, 80 and over|Biomarkers, Tumor|Blood Chemical Analysis|Cluster Analysis|Female|Humans|Lung Neoplasms|Male|Mass Spectrometry|Middle Aged|Multivariate Analysis|Neoplasm Proteins|Peptide Mapping|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm415', '17766268', 'The reproducibility of mass spectrometry proteomic profiling has become an intensely controversial topic. The mere mention of concern over the reproducibility of data generated from any particular platform can lead to the anxiety over the generalizability of its results and its role in the future of discovery proteomics. In this study, we examine the reproducibility of proteomic profiles generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) across multiple data-generation sessions. We analyze the problem in terms of the reproducibility of signals, reproducibility of discriminative features and reproducibility of multivariate classification models on profiles for serum samples from early lung cancer and healthy control subjects.'),
(73671, 2007, 'bio', 'Mining biological networks for unknown pathways', 'Cakmak, Ali|Ozsoyoglu, Gultekin', 'Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. ali.cakmak@case.edu|Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH 44106, USA. ali.cakmak@case.edu', 'United States|United States', 0, 'Algorithms|Bacterial Physiological Phenomena|Bacterial Proteins|Computer Simulation|Information Storage and Retrieval|Models, Biological|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm409', '17766269', 'Biological pathways provide significant insights on the interaction mechanisms of molecules. Presently, many essential pathways still remain unknown or incomplete for newly sequenced organisms. Moreover, experimental validation of enormous numbers of possible pathway candidates in a wet-lab environment is time- and effort-extensive. Thus, there is a need for comparative genomics tools that help scientists predict pathways in an organisms biological network.'),
(73672, 2007, 'bio', 'Optimization of primer design for the detection of variable genomic lesions in cancer', 'Bashir, Ali|Liu, Yu-Tsueng|Raphael, Benjamin J|Carson, Dennis|Bafna, Vineet', 'Bioinformatics Program, University of California, San Diego, CA, USA. abashir@ucsd.edu|Bioinformatics Program, University of California, San Diego, CA, USA. abashir@ucsd.edu|Bioinformatics Program, University of California, San Diego, CA, USA. abashir@ucsd.edu|Bioinformatics Program, University of California, San Diego, CA, USA. abashir@ucsd.edu|Bioinformatics Program, University of California, San Diego, CA, USA. abashir@ucsd.edu', 'United States|United States|United States|United States|United States', 16, 'Chromosome Mapping|Cyclin-Dependent Kinase Inhibitor p16|DNA Mutational Analysis|DNA Primers|DNA, Neoplasm|Genetic Variation|Humans|Neoplasms|Polymerase Chain Reaction|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm390', '17766270', 'Primer approximation multiplex PCR (PAMP) is a new experimental protocol for efficiently assaying structural variation in genomes. PAMP is particularly suited to cancer genomes where the precise breakpoints of alterations such as deletions or translocations vary between patients. The design of PCR primer sets for PAMP is challenging because a large number of primer pairs are required to detect alterations in the hundreds of kilobases range that can occur in cancer. These sets of primers must achieve high coverage of the region of interest, while avoiding primer dimers and satisfying the physico-chemical constraints of good PCR primers. We describe a natural formulation of these constraints as a combinatorial optimization problem. We show that the PAMP primer design problem is NP-hard, and design algorithms based on simulated annealing and integer programming, that provide good solutions to this problem in practice. The algorithms are applied to a test region around the known CDKN2A deletion, which show excellent results even in a 1:49 mixture of mutated:wild-type cells. We use these test results to help set design parameters for larger problems. We can achieve near-optimal designs for regions close to 1 Mb.'),
(73673, 2008, 'bio', 'AWTY (are we there yet?): a system for graphical exploration of MCMC convergence in Bayesian phylogenetics', 'Nylander, Johan A A|Wilgenbusch, James C|Warren, Dan L|Swofford, David L', 'School of Computational Sciences, Florida State University, Tallahassee, Florida 32306, USA.|School of Computational Sciences, Florida State University, Tallahassee, Florida 32306, USA.|School of Computational Sciences, Florida State University, Tallahassee, Florida 32306, USA.|School of Computational Sciences, Florida State University, Tallahassee, Florida 32306, USA.', 'United States|United States|United States|United States', 1132, 'Bayes Theorem|Computational Biology|Computer Graphics|Markov Chains|Monte Carlo Method|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btm388', '17766271', 'A key element to a successful Markov chain Monte Carlo (MCMC) inference is the programming and run performance of the Markov chain. However, the explicit use of quality assessments of the MCMC simulations-convergence diagnostics-in phylogenetics is still uncommon. Here, we present a simple tool that uses the output from MCMC simulations and visualizes a number of properties of primary interest in a Bayesian phylogenetic analysis, such as convergence rates of posterior split probabilities and branch lengths. Graphical exploration of the output from phylogenetic MCMC simulations gives intuitive and often crucial information on the success and reliability of the analysis. The tool presented here complements convergence diagnostics already available in other software packages primarily designed for other applications of MCMC. Importantly, the common practice of using trace-plots of a single parameter or summary statistic, such as the likelihood score of sampled trees, can be misleading for assessing the success of a phylogenetic MCMC simulation.'),
(73674, 2007, 'bio', 'PepSplice: cache-efficient search algorithms for comprehensive identification of tandem mass spectra', 'Roos, Franz F|Jacob, Riko|Grossmann, Jonas|Fischer, Bernd|Buhmann, Joachim M|Gruissem, Wilhelm|Baginsky, Sacha|Widmayer, Peter', 'Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.|Institute of Theoretical Computer Science, Institute of Plant Science, Institute of Computational Science, ETH Zurich, CH-8092 Zurich, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Pattern Recognition, Automated|Peptide Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm417', '17768164', 'Tandem mass spectrometry allows for high-throughput identification of complex protein samples. Searching tandem mass spectra against sequence databases is the main analysis method nowadays. Since many peptide variations are possible, including them in the search space seems only logical. However, the search space usually grows exponentially with the number of independent variations and may therefore overwhelm computational resources.'),
(73675, 2007, 'bio', 'An error model for protein quantification', 'Kreutz, C|Bartolome Rodriguez, M M|Maiwald, T|Seidl, M|Blum, H E|Mohr, L|Timmer, J', 'Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de|Freiburg Center for Data Analysis and Modeling FDM, Eckerstrasse 1, Freiburg, Germany. ckreutz@fdm.uni-freiburg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Immunoblotting|Immunoprecipitation|Models, Biological|Models, Statistical|Proteins|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm397', '17768165', 'Quantitative experimental data is the critical bottleneck in the modeling of dynamic cellular processes in systems biology. Here, we present statistical approaches improving reproducibility of protein quantification by immunoprecipitation and immunoblotting.'),
(73676, 2007, 'bio', 'Simulating association studies: a data-based resampling method for candidate regions or whole genome scans', 'Wright, Fred A|Huang, Hanwen|Guan, Xiaojun|Gamiel, Kevin|Jeffries, Clark|Barry, William T|de Villena, Fernando Pardo-Manuel|Sullivan, Patrick F|Wilhelmsen, Kirk C|Zou, Fei', 'Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu|Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA. fwright@bios.unc.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 47, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Genetic Variation|Information Storage and Retrieval|Molecular Sequence Data|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Sample Size|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btm386', '17785348', 'Reductions in genotyping costs have heightened interest in performing whole genome association scans and in the fine mapping of candidate regions. Improvements in study design and analytic techniques will require the simulation of datasets with realistic patterns of linkage disequilibrium and allele frequencies for typed SNPs.'),
(73677, 2007, 'bio', 'MSQT for choosing SNP assays from multiple DNA alignments', 'Warthmann, Norman|Fitz, Joffrey|Weigel, Detlef', 'Max Planck Institute for Developmental Biology, Department of Molecular Biology, 72076 Tübingen, Germany.|Max Planck Institute for Developmental Biology, Department of Molecular Biology, 72076 Tübingen, Germany.|Max Planck Institute for Developmental Biology, Department of Molecular Biology, 72076 Tübingen, Germany.', 'Germany|Germany|Germany', 0, 'Base Sequence|Chromosome Mapping|Database Management Systems|Databases, Genetic|Genetic Markers|Information Storage and Retrieval|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm428', '17785349', 'One challenging aspect of genotyping and association mapping projects is often the identification of markers that are informative between groups of individuals and to convert these into genotyping assays.'),
(73678, 2007, 'bio', 'A syntactic model to design and verify synthetic genetic constructs derived from standard biological parts', 'Cai, Yizhi|Hartnett, Brian|Gustafsson, Claes|Peccoud, Jean', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Washington Street, MC 0477, Blacksburg VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Washington Street, MC 0477, Blacksburg VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Washington Street, MC 0477, Blacksburg VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Washington Street, MC 0477, Blacksburg VA 24061, USA.', 'United States|United States|United States|United States', 70, 'Chromosome Mapping|Computer Simulation|DNA|Genetic Code|Genetic Engineering|Genomic Islands|Models, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/btm446', '17804435', 'The sequence of artificial genetic constructs is composed of multiple functional fragments, or genetic parts, involved in different molecular steps of gene expression mechanisms. Biologists have deciphered structural rules that the design of genetic constructs needs to follow in order to ensure a successful completion of the gene expression process, but these rules have not been formalized, making it challenging for non-specialists to benefit from the recent progress in gene synthesis.'),
(73679, 2007, 'bio', 'Structure-based calculation of drug efficiency indices', 'Hetényi, Csaba|Maran, Uko|García-Sosa, Alfonso T|Karelson, Mati', 'Institute of Chemical Physics, University of Tartu, 2 Jakobi Street, 51014 Tartu, Estonia. csabahete@yahoo.com|Institute of Chemical Physics, University of Tartu, 2 Jakobi Street, 51014 Tartu, Estonia. csabahete@yahoo.com|Institute of Chemical Physics, University of Tartu, 2 Jakobi Street, 51014 Tartu, Estonia. csabahete@yahoo.com|Institute of Chemical Physics, University of Tartu, 2 Jakobi Street, 51014 Tartu, Estonia. csabahete@yahoo.com', 'Estonia|Estonia|Estonia|Estonia', 23, 'Binding Sites|Computer Simulation|Drug Design|Drug Evaluation, Preclinical|Models, Chemical|Models, Molecular|Pharmaceutical Preparations|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/btm431', '17804436', 'The efficiency indices (EIs) have been derived from the experimental binding affinities of drug candidates to macromolecules. These two-in-one measures include information on both pharmacodynamics and pharmacokinetics of the candidate molecules. The time-consuming experimental measurement of binding affinities of extensive molecule libraries may become a bottle-neck of large scale generation and application of EIs.'),
(73680, 2007, 'bio', 'Identification of potential HIV-1 targets of minocycline', 'Jenwitheesuk, Ekachai|Samudrala, Ram', 'National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, 113 Thailand Science Park, Pahonyothin Road, Klong 1, Klongluang, Pathumtani 12120, Thailand.|National Center for Genetic Engineering and Biotechnology, National Science and Technology Development Agency, 113 Thailand Science Park, Pahonyothin Road, Klong 1, Klongluang, Pathumtani 12120, Thailand.', 'Thailand|Thailand', 0, 'Anti-HIV Agents|Binding Sites|Computer Simulation|Drug Delivery Systems|HIV-1|Minocycline|Models, Chemical|Models, Molecular|Protein Binding|Protein Interaction Mapping|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/btm424', '17804437', 'Minocycline, a broad spectrum antibiotic, has been discovered to have inhibitory activity against HIV-1 in vitro, but the targets inhibited are unknown. We used a docking with dynamics protocol developed by us to predict the binding affinities of minocycline against seven active sites of five HIV-1 proteins to putatively identify the potential target(s) of minocycline. The results indicate that minocycline has the highest predicted binding affinity against HIV-1 integrase.'),
(73681, 2007, 'bio', 'Multiple spaced seeds for homology search', 'Ilie, Lucian|Ilie, Silvana', 'Department of Computer Science, University of Western Ontario, N6A 5B7, London, Ontario, Canada.|Department of Computer Science, University of Western Ontario, N6A 5B7, London, Ontario, Canada.', 'Canada|Canada', 11, 'Algorithms|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Journal Article', '10.1093/bioinformatics/btm422', '17804438', 'Homology search finds similar segments between two biological sequences, such as DNA or protein sequences. The introduction of optimal spaced seeds in PatternHunter has increased both the sensitivity and the speed of homology search, and it has been adopted by many alignment programs such as BLAST. With the further improvement provided by multiple spaced seeds in PatternHunterII, Smith-Waterman sensitivity is approached at BLASTn speed. However, computing optimal multiple spaced seeds was proved to be NP-hard and current heuristic algorithms are all very slow (exponential).'),
(73682, 2007, 'bio', 'Phylocomposer and phylodirector: analysis and visualization of transducer indel models', 'Holmes, Ian', 'Department of Bioengineering, University of California, Berkeley, CA, USA. ihh@berkeley.edu', 'United States', 5, 'Algorithms|Base Sequence|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|INDEL Mutation|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Transducers|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm432', '17804439', 'Finite-state string transducers are probabilistic tools similar to Hidden Markov Models that can be systematically extended to large number of sequences related by indel and substitution processes on phylogenetic trees. The number of states in such models grows exponentially with the number of nodes in the tree, with the consequence that even quite small trees can be difficult to analyze or visualize. Here, we present two tools, phylocomposer and phylodirector, for working with string transducers. The former tool implements previously described composition algorithms for extending transducers to arbitrary tree topologies, while the latter generates short animations for arbitrary input alignments and phylogenetic trees, illustrating the state path through the composed transducer.'),
(73683, 2007, 'bio', 'Transducers: an emerging probabilistic framework for modeling indels on trees', 'Bradley, Robert K|Holmes, Ian', 'Department of Bioengineering, University of California, Berkeley, CA, USA. ihh@berkeley.edu|Department of Bioengineering, University of California, Berkeley, CA, USA. ihh@berkeley.edu', 'United States|United States', 26, 'Algorithms|Base Sequence|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|INDEL Mutation|Models, Genetic|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Transducers', 'Letter', '10.1093/bioinformatics/btm402', '17804440', '-'),
(73684, 2007, 'bio', 'Comparative protein structure modeling by combining multiple templates and optimizing sequence-to-structure alignments', 'Fernandez-Fuentes, Narcis|Rai, Brajesh K|Madrid-Aliste, Carlos J|Fajardo, J Eduardo|Fiser, András', 'Department of Biochemistry and Seaver Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.|Department of Biochemistry and Seaver Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.|Department of Biochemistry and Seaver Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.|Department of Biochemistry and Seaver Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.|Department of Biochemistry and Seaver Center for Bioinformatics, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA.', 'United States|United States|United States|United States|United States', 67, 'Algorithms|Cluster Analysis|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/btm377', '17823132', 'Two major bottlenecks in advancing comparative protein structure modeling are the efficient combination of multiple template structures and the generation of a correct input target-template alignment.'),
(73685, 2007, 'bio', 'Medline search engine for finding genetic markers with biological significance', 'Xuan, Weijian|Wang, Pinglang|Watson, Stanley J|Meng, Fan', 'Molecular and Behavioral Neuroscience Institute and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109, USA.|Molecular and Behavioral Neuroscience Institute and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109, USA.|Molecular and Behavioral Neuroscience Institute and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109, USA.|Molecular and Behavioral Neuroscience Institute and Department of Psychiatry, University of Michigan, Ann Arbor, Michigan 48109, USA.', 'United States|United States|United States|United States', 12, 'Chromosome Mapping|Database Management Systems|Genetic Markers|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Polymorphism, Single Nucleotide|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm375', '17823133', 'Genome-wide high density SNP association studies are expected to identify various SNP alleles associated with different complex disorders. Understanding the biological significance of these SNP alleles in the context of existing literature is a major challenge since existing search engines are not designed to search literature for SNPs or other genetic markers. The literature mining of gene and protein functions has received significant attention and effort while similar work on genetic markers and their related diseases is still in its infancy. Our goal is to develop a web-based tool that facilitates the mining of Medline literature related to genetic studies and gene/protein function studies. Our solution consists of four main function modules for (1) identification of different types of genetic markers or genetic variations in Medline records (2) distinguishing positive versus negative linkage or association between genetic markers and diseases (3) integrating marker genomic location data from different databases to enable the retrieval of Medline records related to markers in the same linkage disequilibrium region (4) and a web interface called MarkerInfoFinder to search, display, sort and download Medline citation results. Tests using published data suggest MarkerInfoFinder can significantly increase the efficiency of finding genetic disorders and their underlying molecular mechanisms. The functions we developed will also be used to build a knowledge base for genetic markers and diseases.'),
(73686, 2007, 'bio', 'The global trace graph, a novel paradigm for searching protein sequence databases', 'Heger, Andreas|Mallick, Swapan|Wilton, Christopher|Holm, Liisa', 'Institute of Biotechnology, P.O. Box 56 (Viikinkaari 5), FI-00014 University of Helsinki, Finland.|Institute of Biotechnology, P.O. Box 56 (Viikinkaari 5), FI-00014 University of Helsinki, Finland.|Institute of Biotechnology, P.O. Box 56 (Viikinkaari 5), FI-00014 University of Helsinki, Finland.|Institute of Biotechnology, P.O. Box 56 (Viikinkaari 5), FI-00014 University of Helsinki, Finland.', 'Finland|Finland|Finland|Finland', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Evolution, Molecular|Information Storage and Retrieval|Molecular Sequence Data|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btm358', '17823134', 'Propagating functional annotations to sequence-similar, presumably homologous proteins lies at the heart of the bioinformatics industry. Correct propagation is crucially dependent on the accurate identification of subtle sequence motifs that are conserved in evolution. The evolutionary signal can be difficult to detect because functional sites may consist of non-contiguous residues while segments in-between may be mutated without affecting fold or function.'),
(73687, 2007, 'bio', 'Modeling protein loops with knowledge-based prediction of sequence-structure alignment', 'Peng, Hung-Pin|Yang, An-Suei', 'Genomics Research Center, Academia Sinica. 128 Academia Road, Section 2, Nankang District, Taipei 115, Taiwan, ROC.|Genomics Research Center, Academia Sinica. 128 Academia Road, Section 2, Nankang District, Taipei 115, Taiwan, ROC.', '-|-', 31, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btm456', '17827204', 'As protein structure database expands, protein loop modeling remains an important and yet challenging problem. Knowledge-based protein loop prediction methods have met with two challenges in methodology development: (1) loop boundaries in protein structures are frequently problematic in constructing length-dependent loop databases for protein loop predictions, (2) knowledge-based modeling of loops of unknown structure requires both aligning a query loop sequence to loop templates and ranking the loop sequence-template matches.'),
(73688, 2007, 'bio', 'Exploiting sample variability to enhance multivariate analysis of microarray data', 'Möller-Levet, Carla S|West, Catharine M|Miller, Crispin J', 'Paterson Institute for Cancer Research, Cancer Research UK, Manchester, M20 4BX, UK. cmoller@picr.man.ac.uk|Paterson Institute for Cancer Research, Cancer Research UK, Manchester, M20 4BX, UK. cmoller@picr.man.ac.uk|Paterson Institute for Cancer Research, Cancer Research UK, Manchester, M20 4BX, UK. cmoller@picr.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm441', '17827205', 'Biological and technical variability is intrinsic in any microarray experiment. While most approaches aim to account for this variability, they do not actively exploit it. Here, we consider a novel approach that uses the variability between arrays to provide an extra source of information that can enhance gene expression analyses.'),
(73689, 2007, 'bio', 'TAGster: efficient selection of LD tag SNPs in single or multiple populations', 'Xu, Zongli|Kaplan, Norman L|Taylor, Jack A', 'Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA.|Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA.|Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina 27709, USA.', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Expressed Sequence Tags|Genetic Markers|Genetics, Population|Linkage Disequilibrium|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btm426', '17827206', 'Genetic association studies increasingly rely on the use of linkage disequilibrium (LD) tag SNPs to reduce genotyping costs. We developed a software package TAGster to select, evaluate and visualize LD tag SNPs both for single and multiple populations. We implement several strategies to improve the efficiency of current LD tag SNP selection algorithms: (1) we modify the tag SNP selection procedure of Carlson et al. to improve selection efficiency and further generalize it to multiple populations. (2) We propose a redundant SNP elimination step to speed up the exhaustive tag SNP search algorithm proposed by Qin et al. (3) We present an additional multiple population tag SNP selection algorithm based on the framework of Howie et al., but using our modified exhaustive search procedure. We evaluate these methods using resequenced candidate gene data from the Environmental Genome Project and show improvements in both computational and tagging efficiency.'),
(73690, 2007, 'bio', 'A novel non-overlapping bi-clustering algorithm for network generation using living cell array data', 'Yang, E|Foteinou, P T|King, K R|Yarmush, M L|Androulakis, I P', 'Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.|Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.|Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.|Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.|Department of Biomedical Engineering, Rutgers University, Piscataway, NJ 08854, USA.', 'United States|United States|United States|United States|United States', 19, 'Biological Assay|Cell Physiological Phenomena|Cluster Analysis|Gene Expression Profiling|Microfluidic Analytical Techniques|Signal Transduction|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm335', '17827207', 'The living cell array quantifies the contribution of activated transcription factors upon the expression levels of their target genes. The direct manipulation of the regulatory mechanisms offers enormous possibilities for deciphering the machinery that activates and controls gene expression. We propose a novel bi-clustering algorithm for generating non-overlapping clusters of reporter genes and conditions and demonstrate how this information can be interpreted in order to assist in the construction of transcription factor interaction networks.'),
(73691, 2007, 'bio', 'Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay', 'Reiner-Benaim, Anat|Yekutieli, Daniel|Letwin, Noah E|Elmer, Gregory I|Lee, Norman H|Kafkafi, Neri|Benjamini, Yoav', 'Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.|Department of Statistics and Operation Research, Tel-Aviv University.', '-|-|-|-|-|-|-', 0, 'Animals|Behavior, Animal|Brain|Computer Simulation|Exploratory Behavior|Gene Expression|Gene Expression Profiling|Male|Mice|Models, Neurological|Nerve Tissue Proteins|Quantitative Trait, Heritable|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm300', '17827208', 'Gene expression and phenotypic functionality can best be associated when they are measured quantitatively within the same experiment. The analysis of such a complex experiment is presented, searching for associations between measures of exploratory behavior in mice and gene expression in brain regions. The analysis of such experiments raises several methodological problems. First and foremost, the size of the pool of potential discoveries being screened is enormous yet only few biologically relevant findings are expected, making the problem of multiple testing especially severe. We present solutions based on screening by testing related hypotheses, then testing the hypotheses of interest. In one variant the subset is selected directly, in the other one a tree of hypotheses is tested hierarchical, both variants control the False Discovery Rate (FDR). Other problems in such experiments are in the fact that the level of data aggregation may be different for the quantitative traits (one per animal) and gene expression measurements (pooled across animals), in that the association may not be linear, and in the resolution of interest only few replications exist. We offer solutions to these problems as well. The hierarchical FDR testing strategies presented here can serve beyond the structure of our motivating example study to any complex microarray study.'),
(73692, 2007, 'bio', 'A genotype calling algorithm for the Illumina BeadArray platform', 'Teo, Yik Y|Inouye, Michael|Small, Kerrin S|Gwilliam, Rhian|Deloukas, Panagiotis|Kwiatkowski, Dominic P|Clark, Taane G', 'Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk|Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK. teo@well.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Chromosome Mapping|Cluster Analysis|Genotype|In Situ Hybridization, Fluorescence|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm443', '17846035', 'Large-scale genotyping relies on the use of unsupervised automated calling algorithms to assign genotypes to hybridization data. A number of such calling algorithms have been recently established for the Affymetrix GeneChip genotyping technology. Here, we present a fast and accurate genotype calling algorithm for the Illumina BeadArray genotyping platforms. As the technology moves towards assaying millions of genetic polymorphisms simultaneously, there is a need for an integrated and easy-to-use software for calling genotypes.'),
(73693, 2007, 'bio', 'Clustal W and Clustal X version 20', 'Larkin, M A|Blackshields, G|Brown, N P|Chenna, R|McGettigan, P A|McWilliam, H|Valentin, F|Wallace, I M|Wilm, A|Lopez, R|Thompson, J D|Gibson, T J|Higgins, D G', 'The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.|The Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Belfield, Dublin 4, Ireland.', 'Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Ireland|Irel', 0, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Computer Graphics|Molecular Sequence Data|Programming Languages|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm404', '17846036', 'The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems.'),
(73694, 2007, 'bio', 'Context-dependent clustering for dynamic cellular state modeling of microarray gene expression', 'Yuan, Shinsheng|Li, Ker-Chau', 'Institute of Statistical Science, Acadmia Sinica, 128, Section 2, Academia Road, Nankang, Taipei 115, Taiwan, ROC.|Institute of Statistical Science, Acadmia Sinica, 128, Section 2, Academia Road, Nankang, Taipei 115, Taiwan, ROC.', '-|-', 0, 'Cluster Analysis|Computer Simulation|Gene Expression Profiling|Models, Biological|Multigene Family|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm457', '17846037', 'High-throughput expression profiling allows researchers to study gene activities globally. Genes with similar expression profiles are likely to encode proteins that may participate in a common structural complex, metabolic pathway or biological process. Many clustering, classification and dimension reduction approaches, powerful in elucidating the expression data, are based on this rationale. However, the converse of this common perception can be misleading. In fact, many biologically related genes turn out uncorrelated in expression.'),
(73695, 2007, 'bio', '2D NMR metabonomic analysis: a novel method for automated peak alignment', 'Zheng, Ming|Lu, Peng|Liu, Yanzhou|Pease, Joseph|Usuka, Jonathan|Liao, Guochun|Peltz, Gary', 'Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.|Department of Genetics & Genomics, Roche Palo Alto LLC, Palo Alto, CA 94304, USA.', 'United States|United States|United States|United States|United States|United States|United States', 20, 'Algorithms|Amino Acid Sequence|Gene Expression Profiling|Magnetic Resonance Spectroscopy|Molecular Sequence Data|Peptide Mapping|Proteome|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btm427', '17846038', 'Comparative metabolic profiling by nuclear magnetic resonance (NMR) is showing increasing promise for identifying inter-individual differences to drug response. Two dimensional (2D) (1)H (13)C NMR can reduce spectral overlap, a common problem of 1D (1)H NMR. However, the peak alignment tools for 1D NMR spectra are not well suited for 2D NMR. An automated and statistically robust method for aligning 2D NMR peaks is required to enable comparative metabonomic analysis using 2D NMR.'),
(73696, 2007, 'bio', 'Construction of a reference gene association network from multiple profiling data: application to data analysis', 'Ucar, Duygu|Neuhaus, Isaac|Ross-MacDonald, Petra|Tilford, Charles|Parthasarathy, Srinivasan|Siemers, Nathan|Ji, Rui-Ru', 'Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.|Computer Science and Engineering, The Ohio State University, Columbus, OH 43210, USA.', 'United States|United States|United States|United States|United States|United States|United States', 9, 'Algorithms|Computer Simulation|Databases, Protein|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome|Reference Values|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm423', '17846039', 'Gene expression profiling is an important tool for gaining insight into biology. Novel strategies are required to analyze the growing archives of microarray data and extract useful information from them. One area of interest is in the construction of gene association networks from collections of profiling data. Various approaches have been proposed to construct gene networks using profiling data, and these networks have been used in functional inference as well as in data visualization. Here, we investigated a non-parametric approach to translate profiling data into a gene network. We explored the characteristics and utility of the resulting network and investigated the use of network information in analysis of variance models and hypothesis testing.'),
(73697, 2007, 'bio', 'Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis', 'Grossmann, Steffen|Bauer, Sebastian|Robinson, Peter N|Vingron, Martin', 'Max-Planck-Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Max-Planck-Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.', 'Germany|Germany|Germany|Germany', 211, 'Algorithms|Gene Expression Profiling|Genes|Oligonucleotide Array Sequence Analysis|Phylogeny|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm440', '17848398', 'High-throughput experiments such as microarray hybridizations often yield long lists of genes found to share a certain characteristic such as differential expression. Exploring Gene Ontology (GO) annotations for such lists of genes has become a widespread practice to get first insights into the potential biological meaning of the experiment. The standard statistical approach to measuring overrepresentation of GO terms cannot cope with the dependencies resulting from the structure of GO because they analyze each term in isolation. Especially the fact that annotations are inherited from more specific descendant terms can result in certain types of false-positive results with potentially misleading biological interpretation, a phenomenon which we term the inheritance problem.'),
(73698, 2007, 'bio', 'Functional profiling of microarray experiments using text-mining derived bioentities', 'Minguez, Pablo|Al-Shahrour, Fátima|Montaner, David|Dopazo, Joaquín', 'Department of Bioinformatics and Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain.|Department of Bioinformatics and Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain.|Department of Bioinformatics and Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain.|Department of Bioinformatics and Functional Genomics Node, (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, E46013, Spain.', 'Spain|Spain|Spain|Spain', 15, 'Artificial Intelligence|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Proteins|Research Design|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm445', '17855415', 'The increasing use of microarray technologies brought about a parallel demand in methods for the functional interpretation of the results. Beyond the conventional functional annotations for genes, such as gene ontology, pathways, etc. other sources of information are still to be exploited. Text-mining methods allow extracting informative terms (bioentities) with different functional, chemical, clinical, etc. meanings, that can be associated to genes. We show how to use these associations within an appropriate statistical framework and how to apply them through easy-to-use, web-based environments to the functional interpretation of microarray experiments. Functional enrichment and gene set enrichment tests using bioentities are presented.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73699, 2007, 'bio', 'RagPools: RNA-As-Graph-Pools--a web server for assisting the design of structured RNA pools for in vitro selection', 'Kim, Namhee|Shin, Jin Sup|Elmetwaly, Shereef|Gan, Hin Hark|Schlick, Tamar', 'Department of Chemistry, New York University, 100 Washington Square East, New York 10003, USA.|Department of Chemistry, New York University, 100 Washington Square East, New York 10003, USA.|Department of Chemistry, New York University, 100 Washington Square East, New York 10003, USA.|Department of Chemistry, New York University, 100 Washington Square East, New York 10003, USA.|Department of Chemistry, New York University, 100 Washington Square East, New York 10003, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Internet|Molecular Sequence Data|RNA Probes|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm439', '17855416', 'Our RNA-As-Graph-Pools (RagPools) web server offers a theoretical companion tool for RNA in vitro selection and related problems. Specifically, it suggests how to construct RNA sequence/structure pools with user-specified properties and assists in analyzing resulting distributions. This utility follows our recently developed approach for engineering sequence pools that links RNA sequence space regions with corresponding structural distributions via a mixing matrix approach combined with a graph theory analysis of RNA secondary-structure space, the mixing matrix specifies nucleotide transition rates, and graph theory links sequences to simple graphical objects representing RNA motifs. The companion RagPools web server (Designer component) provides optimized starting sequences, mixing matrices and associated weights in response to a user-specified target pool structure distribution. In addition, RagPools (Analyzer component) analyzes the motif distribution of pools generated from user-specified starting sequences and mixing matrices. Thus, RagPools serves as a guide to researchers who aim to synthesize RNA pools with desired properties and/or experiment in silico with various designs by our approach.'),
(73700, 2007, 'bio', 'Evolutionary analysis of enzymes using Chisel', 'Rodriguez, Alexis A|Bompada, Tanuja|Syed, Mustafa|Shah, Parantu K|Maltsev, Natalia', 'Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA.|Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA.|Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA.|Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA.|Mathematics and Computer Science Division, Argonne National Laboratory, 9700 S. Cass Ave., Argonne, IL 60439, USA.', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Enzymes|Evolution, Molecular|Genetic Variation|Molecular Sequence Data|Multigene Family|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm421', '17855417', 'Availability of large volumes of genomic and enzymatic data for taxonomically and phenotypically diverse organisms allows for exploration of the adaptive mechanisms that led to diversification of enzymatic functions. We present Chisel, a computational framework and a pipeline for an automated, high-resolution analysis of evolutionary variations of enzymes. Chisel allows automatic as well as interactive identification, and characterization of enzymatic sequences. Such knowledge can be utilized for comparative genomics, microbial diagnostics, metabolic engineering, drug design and analysis of metagenomes.'),
(73701, 2007, 'bio', 'Cyto-Sim: a formal language model and stochastic simulator of membrane-enclosed biochemical processes', 'Sedwards, Sean|Mazza, Tommaso', 'Microsoft Research-University of Trento Centre for Computational & Systems Biology, Italy.|Microsoft Research-University of Trento Centre for Computational & Systems Biology, Italy.', 'Italy|Italy', 20, 'Biochemistry|Cell Membrane|Computer Simulation|Membrane Proteins|Models, Biological|Models, Chemical|Models, Statistical|Programming Languages|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btm416', '17855418', 'Compartments and membranes are the basis of cell topology and more than 30% of the human genome codes for membrane proteins. While it is possible to represent compartments and membrane proteins in a nominal way with many mathematical formalisms used in systems biology, few, if any, explicitly model the topology of the membranes themselves. Discrete stochastic simulation potentially offers the most accurate representation of cell dynamics. Since the details of every molecular interaction in a pathway are often not known, the relationship between chemical species in not necessarily best described at the lowest level, i.e. by mass action. Simulation is a form of computer-aided analysis, relying on human interpretation to derive meaning. To improve efficiency and gain meaning in an automatic way, it is necessary to have a formalism based on a model which has decidable properties.'),
(73702, 2007, 'bio', 'Accurate prediction of deleterious protein kinase polymorphisms', 'Torkamani, Ali|Schork, Nicholas J', 'Department of Medicine, Center for Human Genetics and Genomics, The Scripps Research Institute, University of California, San Diego, La Jolla, CA 92093, USA.|Department of Medicine, Center for Human Genetics and Genomics, The Scripps Research Institute, University of California, San Diego, La Jolla, CA 92093, USA.', 'United States|United States', 0, 'Animals|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Genetic Predisposition to Disease|Humans|Molecular Sequence Data|Polymorphism, Single Nucleotide|Protein Kinases|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm437', '17855419', 'Contemporary, high-throughput sequencing efforts have identified a rich source of naturally occurring single nucleotide polymorphisms (SNPs), a subset of which occur in the coding region of genes and result in a change in the encoded amino acid sequence (non-synonymous coding SNPs or nsSNPs). It is hypothesized that a subset of these nsSNPs may underlie common human disease. Testing all these polymorphisms for disease association would be time consuming and expensive. Thus, computational methods have been developed to both prioritize candidate nsSNPs and make sense of their likely molecular physiologic impact.'),
(73703, 2007, 'bio', 'AVIS: AJAX viewer of interactive signaling networks', 'Berger, Seth I|Iyengar, Ravi|Maayan, Avi', 'Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, 1425 Madison Avenue, New York 10029, USA.|Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, 1425 Madison Avenue, New York 10029, USA.|Department of Pharmacology and Systems Therapeutics, Mount Sinai School of Medicine, 1425 Madison Avenue, New York 10029, USA.', 'United States|United States|United States', 24, 'Computer Graphics|Computer Simulation|Internet|Models, Biological|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm444', '17855420', 'Increasing complexity of cell signaling network maps requires sophisticated visualization technologies. Simple web-based visualization tools can allow for improved data presentation and collaboration. Researchers studying cell signaling would benefit from having the ability to embed dynamic cell signaling maps in web pages.'),
(73704, 2007, 'bio', 'FIST: a sensory domain for diverse signal transduction pathways in prokaryotes and ubiquitin signaling in eukaryotes', 'Borziak, Kirill|Zhulin, Igor B', 'Joint Institute for Computational Sciences, The University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, TN 37831-6173, USA.|Joint Institute for Computational Sciences, The University of Tennessee - Oak Ridge National Laboratory, Oak Ridge, TN 37831-6173, USA.', 'United States|United States', 15, 'Amino Acid Sequence|Animals|Bacterial Physiological Phenomena|Evolution, Molecular|Humans|Membrane Proteins|Molecular Sequence Data|Protein Structure, Tertiary|Signal Transduction|Ubiquitin', 'Journal Article', '10.1093/bioinformatics/btm384', '17855421', 'Sensory domains that are conserved among Bacteria, Archaea and Eucarya are important detectors of common signals detected by living cells. Due to their high sequence divergence, sensory domains are difficult to identify. We systematically look for novel sensory domains using sensitive profile-based searches initiated with regions of signal transduction proteins where no known domains can be identified by current domain models.'),
(73705, 2007, 'bio', 'Graph-based consensus clustering for class discovery from gene expression data', 'Yu, Zhiwen|Wong, Hau-San|Wang, Hongqiang', 'Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong. yuzhiwen@cs.cityu.edu.hk|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong. yuzhiwen@cs.cityu.edu.hk|Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong. yuzhiwen@cs.cityu.edu.hk', 'Hong Kong|Hong Kong|Hong Kong', 122, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm463', '17872912', 'Consensus clustering, also known as cluster ensemble, is one of the important techniques for microarray data analysis, and is particularly useful for class discovery from microarray data. Compared with traditional clustering algorithms, consensus clustering approaches have the ability to integrate multiple partitions from different cluster solutions to improve the robustness, stability, scalability and parallelization of the clustering algorithms. By consensus clustering, one can discover the underlying classes of the samples in gene expression data.'),
(73706, 2007, 'bio', 'EGEETomo: a user-friendly, fault-tolerant and grid-enabled application for 3D reconstruction in electron tomography', 'Bilbao-Castro, J R|García, I|Fernández, J J', 'Department of Computer Architecture and Electronics, University of Almería, 04120 Almería, Spain. jrbcast@ace.ual.es|Department of Computer Architecture and Electronics, University of Almería, 04120 Almería, Spain. jrbcast@ace.ual.es|Department of Computer Architecture and Electronics, University of Almería, 04120 Almería, Spain. jrbcast@ace.ual.es', 'Spain|Spain|Spain', 2, 'Algorithms|Image Enhancement|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Internet|Microscopy, Electron|Software|Tomography', 'Journal Article', '10.1093/bioinformatics/btm459', '17872913', 'Electron tomography is the leading technique to elucidate the structure of complex biological specimens. Due to the resolution needs, huge reconstructions are required. Grid computing has the potential to face the significant computational demands involved. However, there are a number of key issues, such as stability or difficult user-grid interaction, that currently preclude fully exploitation of its potential. EGEETomo is a user-friendly application that facilitates the interaction with the grid for the non-specialized user and automates job submission and supervision. In addition, EGEETomo is supplied with an automated fault recovery mechanism, which is key to make all the work transparent to the user. EGEETomo significantly accelerates tomographic reconstruction by exploiting the computational resources in the EGEE grid with minimal user intervention.'),
(73707, 2007, 'bio', 'IGG: A tool to integrate GeneChips for genetic studies', 'Li, M-X|Jiang, L|Ho, S-L|Song, Y-Q|Sham, P-C', 'Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong and Hunan Business College, Changsha, Hunan 410205, China. limx54@yahoo.com|Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong and Hunan Business College, Changsha, Hunan 410205, China. limx54@yahoo.com|Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong and Hunan Business College, Changsha, Hunan 410205, China. limx54@yahoo.com|Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong and Hunan Business College, Changsha, Hunan 410205, China. limx54@yahoo.com|Department of Biochemistry, The University of Hong Kong, Pokfulam, Hong Kong and Hunan Business College, Changsha, Hunan 410205, China. limx54@yahoo.com', 'China|China|China|China|China', 8, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genomics|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm458', '17872914', 'To facilitate genetic studies using high-throughput genotyping technologies, we have developed an open source tool to integrate genotype data across the Affymetrix and Illumina platforms. It can efficiently integrate a large amount of data from various GeneChips, add genotypes of the HapMap Project into a specific project, flexibly trim and export the integrated data with different formats of popular genetic analysis tools, and highly control the quality of genotype data. Furthermore, this tool has sufficiently simplified its usage through its user-friendly graphic interface and is independent of third-party databases. IGG has successfully been applied to a genome-wide linkage scan in a Charcot-Marie-Tooth disease pedigree by integrating three types of GeneChips and HapMap project genotypes.'),
(73708, 2007, 'bio', 'Log-linear model-based multifactor dimensionality reduction method to detect gene gene interactions', 'Lee, Seung Yeoun|Chung, Yujin|Elston, Robert C|Kim, Youngchul|Park, Taesung', 'Department of Applied Mathematics, Sejong University, 98 Gunja-Dong Kwangjin-Gu, Seoul 143-747, Korea.|Department of Applied Mathematics, Sejong University, 98 Gunja-Dong Kwangjin-Gu, Seoul 143-747, Korea.|Department of Applied Mathematics, Sejong University, 98 Gunja-Dong Kwangjin-Gu, Seoul 143-747, Korea.|Department of Applied Mathematics, Sejong University, 98 Gunja-Dong Kwangjin-Gu, Seoul 143-747, Korea.|Department of Applied Mathematics, Sejong University, 98 Gunja-Dong Kwangjin-Gu, Seoul 143-747, Korea.', '-|-|-|-|-', 62, 'Algorithms|Alzheimer Disease|Computer Simulation|Genetic Predisposition to Disease|Humans|Models, Genetic|Multigene Family|Nerve Tissue Proteins|Protein Interaction Mapping|Risk Assessment|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btm396', '17872915', 'The identification and characterization of susceptibility genes that influence the risk of common and complex diseases remains a statistical and computational challenge in genetic association studies. This is partly because the effect of any single genetic variant for a common and complex disease may be dependent on other genetic variants (gene-gene interaction) and environmental factors (gene-environment interaction). To address this problem, the multifactor dimensionality reduction (MDR) method has been proposed by Ritchie et al. to detect gene-gene interactions or gene-environment interactions. The MDR method identifies polymorphism combinations associated with the common and complex multifactorial diseases by collapsing high-dimensional genetic factors into a single dimension. That is, the MDR method classifies the combination of multilocus genotypes into high-risk and low-risk groups based on a comparison of the ratios of the numbers of cases and controls. When a high-order interaction model is considered with multi-dimensional factors, however, there may be many sparse or empty cells in the contingency tables. The MDR method cannot classify an empty cell as high risk or low risk and leaves it as undetermined.'),
(73709, 2007, 'bio', 'oneChannelGUI: a graphical interface to Bioconductor tools, designed for life scientists who are not familiar with R language', 'Sanges, Remo|Cordero, Francesca|Calogero, Raffaele A', 'CBM (Cluster in Biomedicine) S.c.r.l., AREA Science Park, Basovizza SS 14, km 163,5 34012 Trieste, Italy.|CBM (Cluster in Biomedicine) S.c.r.l., AREA Science Park, Basovizza SS 14, km 163,5 34012 Trieste, Italy.|CBM (Cluster in Biomedicine) S.c.r.l., AREA Science Park, Basovizza SS 14, km 163,5 34012 Trieste, Italy.', 'Italy|Italy|Italy', 86, 'Algorithms|Biological Science Disciplines|Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm469', '17875544', 'OneChannelGUI is an add-on Bioconductor package providing a new set of functions extending the capability of the affylmGUI package. This library provides a graphical interface (GUI) for Bioconductor libraries to be used for quality control, normalization, filtering, statistical validation and data mining for single channel microarrays. Affymetrix 3 expression (IVT) arrays as well as the new whole transcript expression arrays, i.e. gene/exon 1.0 ST, are actually implemented. oneChannelGUI is available for most platforms on which R runs, i.e. Windows and Unix-like machines.'),
(73710, 2007, 'bio', 'A novel knowledge-based approach to design inorganic-binding peptides', 'Oren, Ersin Emre|Tamerler, Candan|Sahin, Deniz|Hnilova, Marketa|Seker, Urartu Ozgur Safak|Sarikaya, Mehmet|Samudrala, Ram', 'Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.|Materials Science and Engineering Department, University of Washington, Seattle, USA.', 'United States|United States|United States|United States|United States|United States|United States', 108, 'Amino Acid Sequence|Binding Sites|Computer Simulation|Inorganic Chemicals|Models, Chemical|Models, Molecular|Molecular Sequence Data|Peptides|Protein Binding|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm436', '17875545', 'The discovery of solid-binding peptide sequences is accelerating along with their practical applications in biotechnology and materials sciences. A better understanding of the relationships between the peptide sequences and their binding affinities or specificities will enable further design of novel peptides with selected properties of interest both in engineering and medicine.'),
(73711, 2007, 'bio', 'The DOMON domains are involved in heme and sugar recognition', 'Iyer, Lakshminarayan M|Anantharaman, Vivek|Aravind, L', 'National Center for Biotechnology Information, National Library of Medicine and National Institute of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine and National Institute of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine and National Institute of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States', 43, 'Animals|Carbohydrate Metabolism|Carbohydrates|Dopamine beta-Hydroxylase|Heme|Humans|Multigene Family|Protein Interaction Mapping|Protein Structure, Tertiary|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm411', '17878204', 'We expand the functionally uncharacterized DOMON domain superfamily to identify several novel families, including the first prokaryotic representatives. Using several computational tools we show that it is involved in ligand binding--either as heme- or sugar-binding domains. We present evidence that the DOMON domain along with the DM13 domain comprises a novel electron-transfer system potentially involved in oxidative modification of animal cell-surface proteins. Other novel versions might function as sugar sensors of histidine kinases of bacterial two component systems.'),
(73712, 2007, 'bio', 'A parsimonious threshold-independent protein feature selection method through the area under receiver operating characteristic curve', 'Wang, Zhanfeng|Chang, Yuan-chin I|Ying, Zhiliang|Zhu, Liang|Yang, Yaning', 'Department of Statistics and Finance, University of Science and Technology of China, Hefei, 230026, China.|Department of Statistics and Finance, University of Science and Technology of China, Hefei, 230026, China.|Department of Statistics and Finance, University of Science and Technology of China, Hefei, 230026, China.|Department of Statistics and Finance, University of Science and Technology of China, Hefei, 230026, China.|Department of Statistics and Finance, University of Science and Technology of China, Hefei, 230026, China.', 'China|China|China|China|China', 22, 'Artificial Intelligence|Mass Spectrometry|Pattern Recognition, Automated|Peptide Mapping|Proteome|ROC Curve|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm442', '17878205', 'Protein expression profiling for differences indicative of early cancer holds promise for improving diagnostics. Due to their high dimensionality, statistical analysis of proteomic data from mass spectrometers is challenging in many aspects such as dimension reduction, feature subset selection as well as construction of classification rules. Search of an optimal feature subset, commonly known as the feature subset selection (FSS) problem, is an important step towards disease classification/diagnostics with biomarkers.'),
(73713, 2007, 'bio', 'A semantic web approach applied to integrative bioinformatics experimentation: a biological use case with genomics data', 'Post, Lennart J G|Roos, Marco|Marshall, M Scott|van Driel, Roel|Breit, Timo M', 'Integrative Bioinformatics Unit and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM, Amsterdam, The Netherlands.|Integrative Bioinformatics Unit and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM, Amsterdam, The Netherlands.|Integrative Bioinformatics Unit and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM, Amsterdam, The Netherlands.|Integrative Bioinformatics Unit and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM, Amsterdam, The Netherlands.|Integrative Bioinformatics Unit and Nuclear Organization Group, Swammerdam Institute for Life Sciences, University of Amsterdam, 1098 SM, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 30, 'Artificial Intelligence|Computational Biology|Database Management Systems|Databases, Genetic|Genomics|Information Storage and Retrieval|Internet|Natural Language Processing|Proteins|Research Design|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm461', '17881406', 'The numerous public data resources make integrative bioinformatics experimentation increasingly important in life sciences research. However, it is severely hampered by the way the data and information are made available. The semantic web approach enhances data exchange and integration by providing standardized formats such as RDF, RDF Schema (RDFS) and OWL, to achieve a formalized computational environment. Our semantic web-enabled data integration (SWEDI) approach aims to formalize biological domains by capturing the knowledge in semantic models using ontologies as controlled vocabularies. The strategy is to build a collection of relatively small but specific knowledge and data models, which together form a personal semantic framework. This can be linked to external large, general knowledge and data models. In this way, the involved scientists are familiar with the concepts and associated relationships in their models and can create semantic queries using their own terms. We studied the applicability of our SWEDI approach in the context of a biological use case by integrating genomics data sets for histone modification and transcription factor binding sites.'),
(73714, 2007, 'bio', 'Effect of the mutation rate and background size on the quality of pathogen identification', 'Reed, Chris|Fofanov, Viacheslav|Putonti, Catherine|Chumakov, Sergei|Slezak, Tom|Fofanov, Yuriy', 'Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.|Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.|Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.|Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.|Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.|Department of Computer Science, University of Houston, 501 Philip G. Hoffman Hall, Houston, TX 77204, USA.', 'United States|United States|United States|United States|United States|United States', 0, 'Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Gene Frequency|Gene Targeting|Genetic Variation|Genome, Bacterial|Models, Genetic|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm420', '17881407', 'Genomic-based methods have significant potential for fast and accurate identification of organisms or even genes of interest in complex environmental samples (air, water, soil, food, etc.), especially when isolation of the target organism cannot be performed by a variety of reasons. Despite this potential, the presence of the unknown, variable and usually large quantities of background DNA can cause interference resulting in false positive outcomes.'),
(73715, 2007, 'bio', 'Moderated statistical tests for assessing differences in tag abundance', 'Robinson, Mark D|Smyth, Gordon K', 'Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia.|Department of Medical Biology, University of Melbourne, Parkville, Victoria, Australia.', 'Australia|Australia', 468, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Expressed Sequence Tags|Gene Expression Profiling|Likelihood Functions|Models, Genetic|Models, Statistical|Poisson Distribution|Sequence Analysis, DNA|Signal Processing, Computer-Assisted', 'Journal Article', '10.1093/bioinformatics/btm453', '17881408', 'Digital gene expression (DGE) technologies measure gene expression by counting sequence tags. They are sensitive technologies for measuring gene expression on a genomic scale, without the need for prior knowledge of the genome sequence. As the cost of sequencing DNA decreases, the number of DGE datasets is expected to grow dramatically. Various tests of differential expression have been proposed for replicated DGE data using binomial, Poisson, negative binomial or pseudo-likelihood (PL) models for the counts, but none of the these are usable when the number of replicates is very small.'),
(73716, 2007, 'bio', 'TAPPA: topological analysis of pathway phenotype association', 'Gao, Shouguo|Wang, Xujing', 'The Max McGee National Research Center for Juvenile Diabetes & The Human and Molecular Genetics Center, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA.|The Max McGee National Research Center for Juvenile Diabetes & The Human and Molecular Genetics Center, The Medical College of Wisconsin and Childrens Hospital of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA.', 'United States|United States', 0, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Programming Languages|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btm460', '17890270', 'Extracting biological insight from microarray data is important but challenging. Here we describe TAPPA, a java-based tool, for identification of phenotype-associated genetic pathways utilizing the pathway topological measures. This is achieved by first calculating a Pathway Connectivity Index (PCI) for each pathway, followed by evaluating its correlation to the phenotypic variation. Our PCI definition not only efficiently captures the contributions from genes that show subtle but consistent changes in expression, but also naturally overweighs the hub genes that interact with a large number of other genes in the pathway. TAPPA also allows evaluation of sub-modules within a pathway and their association to phenotypes.'),
(73717, 2007, 'bio', 'The K tree score: quantification of differences in the relative branch length and topology of phylogenetic trees', 'Soria-Carrasco, Víctor|Talavera, Gerard|Igea, Javier|Castresana, Jose', 'Department of Physiology and Molecular Biodiversity, Institute of Molecular Biology of Barcelona, CSIC, Jordi Girona 18, 08034 Barcelona, Spain.|Department of Physiology and Molecular Biodiversity, Institute of Molecular Biology of Barcelona, CSIC, Jordi Girona 18, 08034 Barcelona, Spain.|Department of Physiology and Molecular Biodiversity, Institute of Molecular Biology of Barcelona, CSIC, Jordi Girona 18, 08034 Barcelona, Spain.|Department of Physiology and Molecular Biodiversity, Institute of Molecular Biology of Barcelona, CSIC, Jordi Girona 18, 08034 Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 67, 'Algorithms|Chromosome Mapping|Computer Graphics|Computer Simulation|Models, Genetic|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm466', '17890735', 'We introduce a new phylogenetic comparison method that measures overall differences in the relative branch length and topology of two phylogenetic trees. To do this, the algorithm first scales one of the trees to have a global divergence as similar as possible to the other tree. Then, the branch length distance, which takes differences in topology and branch lengths into account, is applied to the two trees. We thus obtain the minimum branch length distance or K tree score. Two trees with very different relative branch lengths get a high K score whereas two trees that follow a similar among-lineage rate variation get a low score, regardless of the overall rates in both trees. There are several applications of the K tree score, two of which are explained here in more detail. First, this score allows the evaluation of the performance of phylogenetic algorithms, not only with respect to their topological accuracy, but also with respect to the reproduction of a given branch length variation. In a second example, we show how the K score allows the selection of orthologous genes by choosing those that better follow the overall shape of a given reference tree.'),
(73718, 2007, 'bio', 'Inferring transcriptional regulatory networks from high-throughput data', 'Wang, Rui-Sheng|Wang, Yong|Zhang, Xiang-Sun|Chen, Luonan', 'School of Information, Renmin University of China, Beijing 100872, China.|School of Information, Renmin University of China, Beijing 100872, China.|School of Information, Renmin University of China, Beijing 100872, China.|School of Information, Renmin University of China, Beijing 100872, China.', 'China|China|China|China', 38, 'Algorithms|Computer Simulation|Gene Expression Regulation|Models, Biological|Oligonucleotide Array Sequence Analysis|Signal Transduction|Transcription Factors|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/btm465', '17890736', 'Inferring the relationships between transcription factors (TFs) and their targets has utmost importance for understanding the complex regulatory mechanisms in cellular systems. However, the transcription factor activities (TFAs) cannot be measured directly by standard microarray experiment owing to various post-translational modifications. In particular, cooperative mechanism and combinatorial control are common in gene regulation, e.g. TFs usually recruit other proteins cooperatively to facilitate transcriptional reaction processes.'),
(73719, 2007, 'bio', 'The Poisson Index: a new probabilistic model for protein ligand binding site similarity', 'Davies, J R|Jackson, R M|Mardia, K V|Taylor, C C', 'School of Mathematics and Institute of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, UK.|School of Mathematics and Institute of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, UK.|School of Mathematics and Institute of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, UK.|School of Mathematics and Institute of Molecular and Cellular Biology, University of Leeds, Leeds LS2 9JT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Ligands|Models, Chemical|Models, Statistical|Molecular Sequence Data|Poisson Distribution|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btm470', '17893083', 'The large-scale comparison of protein-ligand binding sites is problematic, in that measures of structural similarity are difficult to quantify and are not easily understood in terms of statistical similarity that can ultimately be related to structure and function. We present a binding site matching score the Poisson Index (PI) based upon a well-defined statistical model. PI requires only the number of matching atoms between two sites and the size of the two sites-the same information used by the Tanimoto Index (TI), a comparable and widely used measure for molecular similarity. We apply PI and TI to a previously automatically extracted set of binding sites to determine the robustness and usefulness of both scores.'),
(73720, 2007, 'bio', 'Idiographica: a general-purpose web application to build idiograms on-demand for human, mouse and rat', 'Kin, Taishin|Ono, Yukiteru', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan. kin-taishin@aist.go.jp|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), 2-42 Aomi, Koto-ku, Tokyo 135-0064, Japan. kin-taishin@aist.go.jp', 'Japan|Japan', 0, 'Algorithms|Animals|Chromosome Banding|Chromosome Mapping|Computer Graphics|Humans|Internet|Mice|Rats|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm455', '17893084', 'We have launched a web server, which serves as a general-purpose idiogram rendering service, and allows users to generate high-quality idiograms with custom annotation according to their own genome-wide mapping/annotation data through an easy-to-use interface. The generated idiograms are suitable not only for visualizing summaries of genome-wide analysis but also for many types of presentation material including web pages, conference posters, oral presentations, etc.'),
(73721, 2007, 'bio', 'TreeSnatcher: coding trees from images', 'Laubach, Thomas|von Haeseler, Arndt', 'Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, Dr-Bohr-Gasse 9/6, A-1030 Vienna, Austria.|Center for Integrative Bioinformatics Vienna, Max F. Perutz Laboratories, Dr-Bohr-Gasse 9/6, A-1030 Vienna, Austria.', 'Austria|Austria', 16, 'Algorithms|Artificial Intelligence|Chromosome Mapping|Computer Simulation|Image Interpretation, Computer-Assisted|Models, Genetic|Pattern Recognition, Automated|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btm438', '17893085', 'TreeSnatcher is a GUI-driven JAVA application for the semi-automatic recognition of multifurcating phylogenetic trees in pixel images. The program accepts an image file as input and analyzes the topology and the metrics of a tree depicted. The analysis is carried out in a multiple-stage process using algorithms from image analysis. In the end, TreeSnatcher produces a Newick tree code that represents the tree structure optionally including branch lengths. TreeSnatcher can process trees with 100 leaves or more in a few seconds.'),
(73722, 2007, 'bio', 'Extending assembly of short DNA sequences to handle error', 'Jeck, William R|Reinhardt, Josephine A|Baltrus, David A|Hickenbotham, Matthew T|Magrini, Vincent|Mardis, Elaine R|Dangl, Jeffery L|Jones, Corbin D', 'Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com|Department of Biology, University of Carolina-Chapel Hill, Chapel Hill, NC 27599, USA. william.jeck@gmail.com', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artifacts|Base Sequence|Chromosome Mapping|Consensus Sequence|DNA|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm451', '17893086', 'Inexpensive de novo genome sequencing, particularly in organisms with small genomes, is now possible using several new sequencing technologies. Some of these technologies such as that from Illuminas Solexa Sequencing, produce high genomic coverage by generating a very large number of small reads ( approximately 30 bp). While prior work shows that partial assembly can be performed by k-mer extension in error-free reads, this algorithm is unsuccessful with the sequencing error rates found in practice. We present VCAKE (Verified Consensus Assembly by K-mer Extension), a modification of simple k-mer extension that overcomes error by using high depth coverage. Though it is a simple modification of a previous approach, we show significant improvements in assembly results on simulated and experimental datasets that include error.'),
(73723, 2007, 'bio', 'The high-level similarity of some disparate gene expression measures', 'Raghavan, Nandini|De Bondt, An M I M|Talloen, Willem|Moechars, Dieder|Göhlmann, Hinrich W H|Amaratunga, Dhammika', 'Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.|Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.|Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.|Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.|Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.|Nonclinical Biostatistics, Johnson & Johnson Pharmaceutical Research & Development LLC, Raritan, NJ 08869, USA.', 'United States|United States|United States|United States|United States|United States', 10, 'Algorithms|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btm448', '17893087', 'Probe-level data from Affymetrix GeneChips can be summarized in many ways to produce probe-set level gene expression measures (GEMs). Disturbingly, the different approaches not only generate quite different measures but they could also yield very different analysis results. Here, we explore the question of how much the analysis results really do differ, first at the gene level, then at the biological process level. We demonstrate that, even though the gene level results may not necessarily match each other particularly well, as long as there is reasonably strong differentiation between the groups in the data, the various GEMs do in fact produce results that are similar to one another at the biological process level. Not only that the results are biologically relevant. As the extent of differentiation drops, the degree of concurrence weakens, although the biological relevance of findings at the biological process level may yet remain.'),
(73724, 2007, 'bio', 'Efficient parameter estimation for spatio-temporal models of pattern formation: case study of Drosophila melanogaster', 'Fomekong-Nanfack, Yves|Kaandorp, Jaap A|Blom, Joke', 'Section Computational Science, Faculty of Science, University of van Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands.|Section Computational Science, Faculty of Science, University of van Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands.|Section Computational Science, Faculty of Science, University of van Amsterdam, Kruislaan 403, 1098 SJ Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Animals|Body Patterning|Computer Simulation|Drosophila Proteins|Drosophila melanogaster|Gene Expression Regulation, Developmental|Models, Biological', 'Journal Article', '10.1093/bioinformatics/btm433', '17893088', 'Diffusable and non-diffusable gene products play a major role in body plan formation. A quantitative understanding of the spatio-temporal patterns formed in body plan formation, by using simulation models is an important addition to experimental observation. The inverse modelling approach consists of describing the body plan formation by a rule-based model, and fitting the model parameters to real observed data. In body plan formation, the data are usually obtained from fluorescent immunohistochemistry or in situ hybridizations. Inferring model parameters by comparing such data to those from simulation is a major computational bottleneck. An important aspect in this process is the choice of method used for parameter estimation. When no information on parameters is available, parameter estimation is mostly done by means of heuristic algorithms.'),
(73725, 2007, 'bio', 'Construction of an open-access database that integrates cross-reference information from the transcriptome and proteome of immune cells', 'Hijikata, Atsushi|Kitamura, Hiroshi|Kimura, Yayoi|Yokoyama, Ryo|Aiba, Yuichi|Bao, Yanyuan|Fujita, Shigeharu|Hase, Koji|Hori, Shohei|Ishii, Yasuyuki|Kanagawa, Osami|Kawamoto, Hiroshi|Kawano, Kazuya|Koseki, Haruhiko|Kubo, Masato|Kurita-Miki, Ai|Kurosaki, Tomohiro|Masuda, Kyoko|Nakata, Mitsumasa|Oboki, Keisuke|Ohno, Hiroshi|Okamoto, Mariko|Okayama, Yoshimichi|O-Wang, Jiyang|Saito, Hirohisa|Saito, Takashi|Sakuma, Machie|Sato, Katsuaki|Sato, Kaori|Seino, Ken-ichiro|Setoguchi, Ruka|Tamura, Yuki|Tanaka, Masato|Taniguchi, Masaru|Taniuchi, Ichiro|Teng, Annabelle|Watanabe, Takeshi|Watarai, Hiroshi|Yamasaki, Sho|Ohara, Osamu', 'RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.|RIKEN Research Center for Allergy and Immunology, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama, Kanagawa, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japa', 69, 'Animals|Database Management Systems|Databases, Factual|Humans|Information Storage and Retrieval|Internet|Lymphocytes|Proteome|Systems Integration|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm430', '17893089', 'Although a huge amount of mammalian genomic data does become publicly available, there are still hurdles for biologists to overcome before such data can be fully exploited. One of the challenges for gaining biological insight from genomic data has been the inability to cross-reference transcriptomic and proteomic data using a single informational platform. To address this, we constructed an open-access database that enabled us to cross-reference transcriptomic and proteomic data obtained from immune cells.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73726, 2007, 'bio', 'Fun&Co: identification of key functional differences in transcriptomes', 'Gamberoni, Giacomo|Lamma, Evelina|Lodo, Gianluca|Marchesini, Jlenia|Mascellani, Nicoletta|Rossi, Simona|Storari, Sergio|Tagliavini, Luca|Volinia, Stefano', 'Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.|Data Mining for Analysis of DNA microarrays and GebbaLab, Department of Morphology and Embryology, Via Fossato di Mortara 64/b-44100 Ferrara, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Proteome|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm425', '17893090', 'Microarray and other genome-wide technologies allow a global view of gene expression that can be used in several ways and whose potential has not been yet fully discovered. Functional insight into expression profiles is routinely obtained by using gene ontology terms associated to the cellular genes. In this article, we deal with functional data mining from expression profiles, proposing a novel approach that studies the correlations between genes and their relations to Gene Ontology (GO). We implemented this approach in a public web-based application named Fun&Co. By using Fun&Co, the user dissects in a pair-wise manner gene expression patterns and links correlated pairs to gene ontology terms. The proof of principle for our study was accomplished by dissecting molecular pathways in muscles. In particular, we identified specific cellular pathways by comparing the three different types of muscle in a pairwise fashion. In fact, we were interested in the specific molecular mechanisms regulating the cardiovascular system (cardiomyocytes and smooth muscle cells).'),
(73727, 2007, 'bio', 'CREx: inferring genomic rearrangements based on common intervals', 'Bernt, Matthias|Merkle, Daniel|Ramsch, Kai|Fritzsch, Guido|Perseke, Marleen|Bernhard, Detlef|Schlegel, Martin|Stadler, Peter F|Middendorf, Martin', 'Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de|Parallel Computing and Complex Systems Group, University of Leipzig, Fraunhofer Institute IZI, Leipzig, Germany. merkle@informatik.uni-leipzig.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Computer Graphics|Gene Rearrangement|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm468', '17895271', 'We present the web-based program CREx for heuristically determining pairwise rearrangement events in unichromosomal genomes. CREx considers transpositions, reverse transpositions, reversals and tandem-duplication-random-loss (TDRL) events. It supports the user in finding parsimonious rearrangement scenarios given a phylogenetic hypothesis. CREx is based on common intervals, which reflect genes that appear consecutively in several of the input gene orders.'),
(73728, 2008, 'bio', 'SnoReport: computational identification of snoRNAs with unknown targets', 'Hertel, Jana|Hofacker, Ivo L|Stadler, Peter F', 'Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria. jana@bioinf.uni-leipzig.de|Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria. jana@bioinf.uni-leipzig.de|Institute for Theoretical Chemistry, University of Vienna, Währingerstrasse 17, A-1090 Wien, Austria. jana@bioinf.uni-leipzig.de', 'Austria|Austria|Austria', 57, 'Algorithms|Artificial Intelligence|Base Sequence|Conserved Sequence|Gene Targeting|Molecular Sequence Data|Pattern Recognition, Automated|RNA, Small Nucleolar|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm464', '17895272', 'Unlike tRNAs and microRNAs, both classes of snoRNAs, which direct two distinct types of chemical modifications of uracil residues, have proved to be surprisingly difficult to find in genomic sequences. Most computational approaches so far have explicitly used the fact that snoRNAs predominantly target ribosomal RNAs and spliceosomal RNAs. The target is specified by a short stretch of sequence complementarity between the snoRNA and its target. This sequence complementarity to known targets crucially contributes to sensitivity and specificity of snoRNA gene finding algorithms. The discovery of orphan snoRNAs, which either have no known target, or which target ordinary protein-coding mRNAs, however, begs the question whether this class of housekeeping non-coding RNAs is much more widespread and might have a diverse set of regulatory functions. In order to approach this question, we present here a combination of RNA secondary structure prediction and machine learning that is designed to recognize the two major classes of snoRNAs, box C/D and box H/ACA snoRNAs, among ncRNA candidate sequences. The snoReport approach deliberately avoids any usage of target information. We find that the combination of the conserved sequence boxes and secondary structure constraints as a pre-filter with SVM classifiers based on a small set of structural descriptors are sufficient for a reliable identification of snoRNAs. Tests of snoReport on data from several recent experimental surveys show that the approach is feasible, the application to a dataset from a large-scale comparative genomics survey for ncRNAs suggests that there are likely hundreds of previously undescribed orphan snoRNAs still hidden in the human genome.'),
(73729, 2007, 'bio', 'TandTRAQ: an open-source tool for integrated protein identification and quantitation', 'Laderas, Ted|Bystrom, Cory|McMillen, Debra|Fan, Guang|McWeeney, Shannon', 'Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu|Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu|Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu|Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu|Informatics Shared Resource, OHSU Cancer Institute, Oregon Health & Science University, Portland, Oregon 97212, USA. laderast@ohsu.edu', 'United States|United States|United States|United States|United States', 9, 'Algorithms|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm467', '17895273', 'Integrating qualitative protein identification with quantitative protein analysis is non-trivial, given incompatibility in output formats. We present TandTRAQ, a standalone utility that integrates results from i-Tracker, an open-source iTRAQ quantitation program with the search results from X?Tandem, an open-source proteome search engine. The utility runs from the command-line and can be easily integrated into a pipeline for automation.'),
(73730, 2007, 'bio', 'CellMontage: similar expression profile search server', 'Fujibuchi, Wataru|Kiseleva, Larisa|Taniguchi, Takeaki|Harada, Hajime|Horton, Paul', 'Computational Biology Research Center, AIST Waterfront Bio-IT Research Building, 2-42 Aomi Koto-ku, Tokyo, Japan.|Computational Biology Research Center, AIST Waterfront Bio-IT Research Building, 2-42 Aomi Koto-ku, Tokyo, Japan.|Computational Biology Research Center, AIST Waterfront Bio-IT Research Building, 2-42 Aomi Koto-ku, Tokyo, Japan.|Computational Biology Research Center, AIST Waterfront Bio-IT Research Building, 2-42 Aomi Koto-ku, Tokyo, Japan.|Computational Biology Research Center, AIST Waterfront Bio-IT Research Building, 2-42 Aomi Koto-ku, Tokyo, Japan.', 'Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Database Management Systems|Databases, Protein|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm462', '17895274', 'The establishment and rapid expansion of microarray databases has created a need for new search tools. Here we present CellMontage, the first server for expression profile similarity search over a large database-69 000 microarray experiments derived from NCBIs, GEO site. CellMontage provides a novel, content-based search engine for accessing gene expression data. Microarray experiments with similar overall expression to a user-provided expression profile (e.g. microarray experiment) are computed and displayed-usually within 20 s. The core search engine software is downloadable from the site.'),
(73731, 2007, 'bio', 'HAPLOPOOL: improving haplotype frequency estimation through DNA pools and phylogenetic modeling', 'Kirkpatrick, Bonnie|Armendariz, Carlos Santos|Karp, Richard M|Halperin, Eran', 'Department of Electrical Engineering and Computer Sciences, UC Berkeley, CA, , USA.|Department of Electrical Engineering and Computer Sciences, UC Berkeley, CA, , USA.|Department of Electrical Engineering and Computer Sciences, UC Berkeley, CA, , USA.|Department of Electrical Engineering and Computer Sciences, UC Berkeley, CA, , USA.', 'United States|United States|United States|United States', 18, 'Computer Simulation|DNA|Gene Frequency|Gene Pool|Genetic Variation|Haplotypes|Models, Genetic|Phylogeny|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm435', '17895275', 'The search for genetic variants that are linked to complex diseases such as cancer, Parkinsons,, or Alzheimers, disease, may lead to better treatments. Since haplotypes can serve as proxies for hidden variants, one method of finding the linked variants is to look for case-control associations between the haplotypes and disease. Finding these associations requires a high-quality estimation of the haplotype frequencies in the population. To this end, we present, HaploPool, a method of estimating haplotype frequencies from blocks of consecutive SNPs.'),
(73732, 2007, 'bio', 'meta-PPISP: a meta web server for protein-protein interaction site prediction', 'Qin, Sanbo|Zhou, Huan-Xiang', 'Institute of Molecular Biophysics, School of Computational Science, Florida State University, Tallahassee, Florida 32306, USA.|Institute of Molecular Biophysics, School of Computational Science, Florida State University, Tallahassee, Florida 32306, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Internet|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm434', '17895276', 'A number of complementary methods have been developed for predicting protein-protein interaction sites. We sought to increase prediction robustness and accuracy by combining results from different predictors, and report here a meta web server, meta-PPISP, that is built on three individual web servers: cons-PPISP (http://pipe.scs.fsu.edu/ppisp.html), Promate (http://bioportal.weizmann.ac.il/promate), and PINUP (http://sparks.informatics.iupui.edu/PINUP/). A linear regression method, using the raw scores of the three servers as input, was trained on a set of 35 nonhomologous proteins. Cross validation showed that meta-PPISP outperforms all the three individual servers. At coverages identical to those of the individual methods, the accuracy of meta-PPISP is higher by 4.8 to 18.2 percentage points. Similar improvements in accuracy are also seen on CAPRI and other targets.'),
(73733, 2007, 'bio', 'Clustering by soft-constraint affinity propagation: applications to gene-expression data', '-', '-', '-', 95, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Simulation|Databases, Protein|Gene Expression Profiling|Models, Biological|Pattern Recognition, Automated|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm414', '17895277', 'Similarity-measure-based clustering is a crucial problem appearing throughout scientific data analysis. Recently, a powerful new algorithm called Affinity Propagation (AP) based on message-passing techniques was proposed by Frey and Dueck (2007a). In AP, each cluster is identified by a common exemplar all other data points of the same cluster refer to, and exemplars have to refer to themselves. Albeit its proved power, AP in its present form suffers from a number of drawbacks. The hard constraint of having exactly one exemplar per cluster restricts AP to classes of regularly shaped clusters, and leads to suboptimal performance, e.g. in analyzing gene expression data.'),
(73734, 2007, 'bio', 'Minimizing the overlap problem in protein NMR: a computational framework for precision amino acid labeling', 'Sweredoski, Michael J|Donovan, Kevin J|Nguyen, Bao D|Shaka, A J|Baldi, Pierre', 'Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, USA.|Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, USA.|Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, USA.|Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, USA.|Department of Computer Science, Institute for Genomics and Bioinformatics, University of California, Irvine, USA.', 'United States|United States|United States|United States|United States', 5, 'Algorithms|Amino Acid Sequence|Amino Acids|Isotope Labeling|Magnetic Resonance Spectroscopy|Molecular Sequence Data|Peptide Mapping|Proteins|Radioisotopes|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm406', '17895278', 'Recent advances in cell-free protein expression systems allow specific labeling of proteins with amino acids containing stable isotopes ((15)N, (13) C and (2)H), an important feature for protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. Given this labeling ability, we present a mathematical optimization framework for designing a set of protein isotopomers, or labeling schedules, to reduce the congestion in the NMR spectra. The labeling schedules, which are derived by the optimization of a cost function, are tailored to a specific protein and NMR experiment.'),
(73735, 2007, 'bio', 'Systematic order-dependent effect in expression values, variance, detection calls and differential expression in Affymetrix GeneChips', 'Bjork, Kathe E|Kafadar, Karen', 'Department of Mathematical Sciences, University of Colorado at Denver and Health Sciences Center, Denver, CO 80217, USA. Kathe.bjork@cudenver.edu|Department of Mathematical Sciences, University of Colorado at Denver and Health Sciences Center, Denver, CO 80217, USA. Kathe.bjork@cudenver.edu', 'United States|United States', 0, 'Artifacts|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btm450', '17897972', 'Affymetrix GeneChips are common 3 profiling platforms for quantifying gene expression. Using publicly available datasets of expression profiles from human and mouse experiments, we sought to characterize features of GeneChip data to better compare and evaluate analyses for differential expression, regulation and clustering. We uncovered an unexpected order dependence in expression data that holds across a variety of chips in both human and mouse data.'),
(73736, 2007, 'bio', 'DIA-MCIS: an importance sampling network randomizer for network motif discovery and other topological observables in transcription networks', 'Fusco, D|Bassetti, B|Jona, P|Lagomarsino, M Cosentino', 'Università degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, Italy. diana.fusco@studenti.unimi.it|Università degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, Italy. diana.fusco@studenti.unimi.it|Università degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, Italy. diana.fusco@studenti.unimi.it|Università degli Studi di Milano, Dip. Fisica, Via Celoria 16, 20133 Milano, Italy. diana.fusco@studenti.unimi.it', 'Italy|Italy|Italy|Italy', 4, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Models, Biological|Models, Statistical|Signal Transduction|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm454', '17901083', 'Transcription networks, and other directed networks can be characterized by some topological observables (e.g. network motifs), that require a suitable randomized network ensemble, typically with the same degree sequences of the original ones. The commonly used algorithms sometimes have long convergence times, and sampling problems. We present here an alternative, based on a variant of the importance sampling Monte Carlo developed by (Chen et al.).'),
(73737, 2007, 'bio', 'XtalPred: a web server for prediction of protein crystallizability', 'Slabinski, Lukasz|Jaroszewski, Lukasz|Rychlewski, Leszek|Wilson, Ian A|Lesley, Scott A|Godzik, Adam', 'Joint Center for Structural Genomics, La Jolla, CA 92037, USA.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA.|Joint Center for Structural Genomics, La Jolla, CA 92037, USA.', 'United States|United States|United States|United States|United States|United States', 170, 'Computer Simulation|Crystallization|Crystallography|Internet|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btm477', '17921170', 'XtalPred is a web server for prediction of protein crystallizability. The prediction is made by comparing several features of the protein with distributions of these features in TargetDB and combining the results into an overall probability of crystallization. XtalPred provides: (1) a detailed comparison of the proteins features to the corresponding distribution from TargetDB, (2) a summary of protein features and predictions that indicate problems that are likely to be encountered during protein crystallization, (3) prediction of ligands, and (4) (optional) lists of close homologs from complete microbial genomes that are more likely to crystallize.'),
(73738, 2007, 'bio', 'Annotation of selection strengths in viral genomes', 'McCauley, Stephen|de Groot, Saskia|Mailund, Thomas|Hein, Jotun', 'Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, UK.|Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, UK.|Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, UK.|Department of Statistics, University of Oxford, 1 South Parks Road, OX1 3TG, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Genome, Viral|Molecular Sequence Data|Phylogeny|Repetitive Sequences, Nucleic Acid|Selection, Genetic|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm472', '17921171', 'Viral genomes tend to code in overlapping reading frames to maximize informational content. This may result in atypical codon bias and particular evolutionary constraints. Due to the fast mutation rate of viruses, there is additional strong evidence for varying selection between intra- and intergenomic regions. The presence of multiple coding regions complicates the concept of K(a)/K(s) ratio, and thus begs for an alternative approach when investigating selection strengths. Building on the paper by McCauley and Hein, we develop a method for annotating a viral genome coding in overlapping reading frames. We introduce an evolutionary model capable of accounting for varying levels of selection along the genome, and incorporate it into our prior single sequence HMM methodology, extending it now to a phylogenetic HMM. Given an alignment of several homologous viruses to a reference sequence, we may thus achieve an annotation both of coding regions as well as selection strengths, allowing us to investigate different selection patterns and hypotheses.'),
(73739, 2007, 'bio', 'I/NI-calls for the exclusion of non-informative genes: a highly effective filtering tool for microarray data', 'Talloen, Willem|Clevert, Djork-Arné|Hochreiter, Sepp|Amaratunga, Dhammika|Bijnens, Luc|Kass, Stefan|Göhlmann, Hinrich W H', 'Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com|Johnson & Johnson Pharmaceutical Research & Development, Division of Janssen Pharmaceutica n.v., Beerse, Belgium. wtalloen@prdbe.jnj.com', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 83, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software', 'Journal Article', '10.1093/bioinformatics/btm478', '17921172', 'DNA microarray technology typically generates many measurements of which only a relatively small subset is informative for the interpretation of the experiment. To avoid false positive results, it is therefore critical to select the informative genes from the large noisy data before the actual analysis. Most currently available filtering techniques are supervised and therefore suffer from a potential risk of overfitting. The unsupervised filtering techniques, on the other hand, are either not very efficient or too stringent as they may mix up signal with noise. We propose to use the multiple probes measuring the same target mRNA as repeated measures to quantify the signal-to-noise ratio of that specific probe set. A Bayesian factor analysis with specifically chosen prior settings, which models this probe level information, is providing an objective feature filtering technique, named informative/non-informative calls (I/NI calls).'),
(73740, 2007, 'bio', 'Identification and visualization of cage-shaped proteins', 'Hu, Min|Wang, Junhui|Peng, Qunsheng', 'State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou, 310058, China. humin@cad.zju.edu.cn|State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou, 310058, China. humin@cad.zju.edu.cn|State Key Laboratory of CAD & CG, Zhejiang University, Hangzhou, 310058, China. humin@cad.zju.edu.cn', 'China|China|China', 1, 'Computer Graphics|Computer Simulation|Imaging, Three-Dimensional|Models, Chemical|Models, Molecular|Protein Conformation|Proteins|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm476', '17921173', 'Cage-shaped protein, with its special structure, may have potential applications in biomedicine and nanotechnology. We developed a program CSPro (Cage-Shaped Protein) for efficient identification of cage-shaped proteins based on quaternary structure. CSPro is capable of revealing the corresponding cage-shaped feature more clearly and quickly than traditional visualization tools. Using CSPro, we have searched the full set of PDB (protein data bank) and three types of proteins are retrieved with notably large central cavities inside. CSPro can be used to validate if the quaternary structure of a protein is cage shaped in molecular simulation.'),
(73741, 2007, 'bio', 'OSCAR: one-class SVM for accurate recognition of cis-elements', 'Jiang, Bo|Zhang, Michael Q|Zhang, Xuegong', 'MOE Key Laboratory of Bioinformatics, Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics, Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China', 0, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Base Sequence|Binding Sites|Molecular Sequence Data|Pattern Recognition, Automated|Promoter Regions, Genetic|Protein Binding|Regulatory Elements, Transcriptional|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm473', '17921174', 'Traditional methods to identify potential binding sites of known transcription factors still suffer from large number of false predictions. They mostly use sequence information in a position-specific manner and neglect other types of information hidden in the proximal promoter regions. Recent biological and computational researches, however, suggest that there exist not only locational preferences of binding, but also correlations between transcription factors.'),
(73742, 2007, 'bio', 'Improved BLAST searches using longer words for protein seeding', 'Shiryev, Sergey A|Papadopoulos, Jason S|Schäffer, Alejandro A|Agarwala, Richa', 'Department of Health and Human Services, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.|Department of Health and Human Services, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.|Department of Health and Human Services, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.|Department of Health and Human Services, National Center for Biotechnology Information, National Institutes of Health, Bethesda, MD, USA.', 'United States|United States|United States|United States', 37, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Proteins|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm479', '17921491', 'The blastp and tblastn modules of BLAST are widely used methods for searching protein queries against protein and nucleotide databases, respectively. One heuristic used in BLAST is to consider only database sequences that contain a high-scoring match of length at most 5 to the query. We implemented the capability to use words of length 6 or 7. We demonstrate an improved trade-off between running time and retrieval accuracy, controlled by the score threshold used for short word matches. For example, the running time can be reduced by 20-30% while achieving ROC (receiver operator characteristic) scores similar to those obtained with current default parameters.'),
(73743, 2007, 'bio', 'HMM-Kalign: a tool for generating sub-optimal HMM alignments', 'Becker, Emmanuelle|Cotillard, Aurélie|Meyer, Vincent|Madaoui, Hocine|Guérois, Raphaël', 'CEA, iBiTecS, URA 2096, SBSM, Laboratoire de Biologie Structurale et Radiobiologie, Gif sur Yvette, F-91191 France.|CEA, iBiTecS, URA 2096, SBSM, Laboratoire de Biologie Structurale et Radiobiologie, Gif sur Yvette, F-91191 France.|CEA, iBiTecS, URA 2096, SBSM, Laboratoire de Biologie Structurale et Radiobiologie, Gif sur Yvette, F-91191 France.|CEA, iBiTecS, URA 2096, SBSM, Laboratoire de Biologie Structurale et Radiobiologie, Gif sur Yvette, F-91191 France.|CEA, iBiTecS, URA 2096, SBSM, Laboratoire de Biologie Structurale et Radiobiologie, Gif sur Yvette, F-91191 France.', 'France|France|France|France|France', 5, 'Algorithms|Markov Chains|Pattern Recognition, Automated|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm492', '17921492', 'Recent development of strategies using multiple sequence alignments (MSA) or profiles to detect remote homologies between proteins has led to a significant increase in the number of proteins whose structures can be generated by comparative modeling methods. However, prediction of the optimal alignment between these highly divergent homologous proteins remains a difficult issue. We present a tool based on a generalized Viterbi algorithm that generates optimal and sub-optimal alignments between a sequence and a Hidden Markov Model. The tool is implemented as a new function within the HMMER package called hmmkalign.'),
(73744, 2007, 'bio', 'BiasViz: visualization of amino acid biased regions in protein alignments', 'Huska, Matthew R|Buschmann, Henrik|Andrade-Navarro, Miguel A', 'Molecular Medicine, Ottawa Health Research Institute, 501 Smyth Road, Ottawa, ON, Canada. matthuska@alumni.uwaterloo.ca|Molecular Medicine, Ottawa Health Research Institute, 501 Smyth Road, Ottawa, ON, Canada. matthuska@alumni.uwaterloo.ca|Molecular Medicine, Ottawa Health Research Institute, 501 Smyth Road, Ottawa, ON, Canada. matthuska@alumni.uwaterloo.ca', 'Canada|Canada|Canada', 8, 'Algorithms|Amino Acid Sequence|Amino Acids|Computer Graphics|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm489', '17921493', 'About a third of all protein sequences have at least one composition biased region (CBR). Such regions might act as linkers between protein domains but often confer specific binding to various molecules, therefore, their characterization in terms of their boundaries and over-represented residues is important. Analysis of CBRs in a particular sequence can be time consuming if several types of biases have to be explored and their position visualized. Assessment of the significance of the detected CBRs can be approached by comparison to homologous protein sequences. To assist this procedure, we have developed BiasViz, a tool that allows to graphically studying local amino acid composition in protein sequences of a multiple sequence alignment.'),
(73745, 2007, 'bio', 'Biclustering as a method for RNA local multiple sequence alignment', 'Wang, Shu|Gutell, Robin R|Miranker, Daniel P', 'Department of Electrical and Computer Engineering, School of Biological Sciences, University of Texas At Austin, Austin, TX 78712, USA. shuwang2006@gmail.com|Department of Electrical and Computer Engineering, School of Biological Sciences, University of Texas At Austin, Austin, TX 78712, USA. shuwang2006@gmail.com|Department of Electrical and Computer Engineering, School of Biological Sciences, University of Texas At Austin, Austin, TX 78712, USA. shuwang2006@gmail.com', 'United States|United States|United States', 13, 'Algorithms|Artificial Intelligence|Base Sequence|Cluster Analysis|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btm485', '17921494', 'Biclustering is a clustering method that simultaneously clusters both the domain and range of a relation. A challenge in multiple sequence alignment (MSA) is that the alignment of sequences is often intended to reveal groups of conserved functional subsequences. Simultaneously, the grouping of the sequences can impact the alignment, precisely the kind of dual situation biclustering is intended to address.'),
(73746, 2007, 'bio', 'Evaluation and integration of 49 genome-wide experiments and the prediction of previously unknown obesity-related genes', 'English, Sangeeta B|Butte, Atul J', 'Department of Medicine, Stanford Medical Informatics, Stanford University School of Medicine, Lucile Packard Childrens Hospital, Stanford, CA 94305, USA.|Department of Medicine, Stanford Medical Informatics, Stanford University School of Medicine, Lucile Packard Childrens Hospital, Stanford, CA 94305, USA.', 'United States|United States', 37, 'Algorithms|Biomarkers|Chromosome Mapping|Databases, Protein|Gene Expression Profiling|Humans|Information Storage and Retrieval|Obesity|Proteome|Reproducibility of Results|Sensitivity and Specificity|Systems Integration', 'Comparative Study', '10.1093/bioinformatics/btm483', '17921495', 'Genome-wide experiments only rarely show resounding success in yielding genes associated with complex polygenic disorders. We evaluate 49 obesity-related genome-wide experiments with publicly available findings including microarray, genetics, proteomics and gene knock-down from human, mouse, rat and worm, in terms of their ability to rediscover a comprehensive set of genes previously found to be causally associated or having variants associated with obesity.'),
(73747, 2007, 'bio', 'Extracting three-way gene interactions from microarray data', 'Zhang, Jiexin|Ji, Yuan|Zhang, Li', 'Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 237, Houston, TX 77030-4009, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 237, Houston, TX 77030-4009, USA.|Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, 1515 Holcombe Boulevard, Unit 237, Houston, TX 77030-4009, USA.', 'United States|United States|United States', 31, 'Algorithms|Animals|Computer Simulation|Gene Expression Profiling|Humans|Models, Biological|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm482', '17921496', 'It is an important and difficult task to extract gene network information from high-throughput genomic data. A common approach is to cluster genes using pairwise correlation as a distance metric. However, pairwise correlation is clearly too simplistic to describe the complex relationships among real genes since co-expression relationships are often restricted to a specific set of biological conditions/processes. In this study, we described a three-way gene interaction model that captures the dynamic nature of co-expression relationship between a gene pair through the introduction of a controller gene.'),
(73748, 2007, 'bio', 'Four-body scoring function for mutagenesis', 'Deutsch, Chris|Krishnamoorthy, Bala', 'Department of Mathematics, Washington State University, USA.|Department of Mathematics, Washington State University, USA.', 'United States|United States', 34, 'Amino Acid Sequence|Molecular Sequence Data|Mutagenesis, Site-Directed|Mutation|Proteins|Quantitative Structure-Activity Relationship|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm481', '17921497', 'There is a need for an efficient and accurate computational method to identify the effects of single- and multiple-residue mutations on the stability and reactivity of proteins. Such a method should ideally be consistent and yet applicable in a widespread manner, i.e. it should be applied to various proteins under the same parameter settings, and have good predictive power for all of them.'),
(73749, 2007, 'bio', 'Leveraging the structure of the Semantic Web to enhance information retrieval for proteomics', 'Smith, Andrew|Cheung, Kei|Krauthammer, Michael|Schultz, Martin|Gerstein, Mark', 'Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.|Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA.', 'United States|United States|United States|United States|United States', 9, 'Artificial Intelligence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Natural Language Processing|Proteins|Proteomics', 'Journal Article', '10.1093/bioinformatics/btm452', '17923450', 'Proteomics researchers need to be able to quickly retrieve relevant information from the web and the biomedical literature. To improve information retrieval, we leverage the structure of the semantic web, developing an approach for joining it with the largely opposing paradigm of unsupervised web search.'),
(73750, 2007, 'bio', 'Naïve Bayes for microRNA target predictions--machine learning for microRNA targets', 'Yousef, Malik|Jung, Segun|Kossenkov, Andrew V|Showe, Louise C|Showe, Michael K', 'The Wistar Institute, Philadelphia, PA 19104, USA.|The Wistar Institute, Philadelphia, PA 19104, USA.|The Wistar Institute, Philadelphia, PA 19104, USA.|The Wistar Institute, Philadelphia, PA 19104, USA.|The Wistar Institute, Philadelphia, PA 19104, USA.', 'United States|United States|United States|United States|United States', 108, 'Algorithms|Artificial Intelligence|Base Sequence|Bayes Theorem|Gene Targeting|MicroRNAs|Molecular Sequence Data|Pattern Recognition, Automated|RNA Probes|Sequence Alignment|Sequence Analysis, RNA', 'Journal Article', '10.1093/bioinformatics/btm484', '17925304', 'Most computational methodologies for miRNA:mRNA target gene prediction use the seed segment of the miRNA and require cross-species sequence conservation in this region of the mRNA target. Methods that do not rely on conservation generate numbers of predictions, which are too large to validate. We describe a target prediction method (NBmiRTar) that does not require sequence conservation, using instead, machine learning by a naïve Bayes classifier. It generates a model from sequence and miRNA:mRNA duplex information from validated targets and artificially generated negative examples. Both the seed and out-seed segments of the miRNA:mRNA duplex are used for target identification.'),
(73751, 2008, 'bio', 'Successful anti-cancer drug targets able to pass FDA review demonstrate the identifiable signature distinct from the signatures of random genes and initially proposed targets', 'Mayburd, Anatoly L|Golovchikova, Inna|Mulshine, James L', 'CPA Global, LLC, 1725 Duke Street, Alexnadria, VA 22314, USA. amayburd@cpaglobal.com|CPA Global, LLC, 1725 Duke Street, Alexnadria, VA 22314, USA. amayburd@cpaglobal.com|CPA Global, LLC, 1725 Duke Street, Alexnadria, VA 22314, USA. amayburd@cpaglobal.com', 'United States|United States|United States', 8, 'Algorithms|Antineoplastic Agents|Drug Approval|Drug Delivery Systems|Drug Design|Drug Therapy, Computer-Assisted|Gene Expression Profiling|Gene Targeting|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|United States|United States Food and Drug Administration', 'Journal Article', '10.1093/bioinformatics/btm447', '17925305', 'New efforts to guide and prioritize the selection of cancer drug targets are urgently needed, as is evident by the slow development of novel anti-cancer agents and the narrow therapeutic index of existing drugs. Given these limitations, the current study was conducted to explore the classification features defining the therapeutic success that can result from targeting a particular gene.'),
(73752, 2007, 'bio', 'Feature construction from synergic pairs to improve microarray-based classification', 'Hanczar, Blaise|Zucker, Jean-Daniel|Henegar, Corneliu|Saitta, Lorenza', 'Laboratoire dInformatique Médicale et Bioinformatique (Lim & Bio), Université Paris 13, 93017 Bobigny, France. hanczar_blaise@yahoo.fr|Laboratoire dInformatique Médicale et Bioinformatique (Lim & Bio), Université Paris 13, 93017 Bobigny, France. hanczar_blaise@yahoo.fr|Laboratoire dInformatique Médicale et Bioinformatique (Lim & Bio), Université Paris 13, 93017 Bobigny, France. hanczar_blaise@yahoo.fr|Laboratoire dInformatique Médicale et Bioinformatique (Lim & Bio), Université Paris 13, 93017 Bobigny, France. hanczar_blaise@yahoo.fr', 'France|France|France|France', 16, 'Algorithms|Artificial Intelligence|Cluster Analysis|Data Interpretation, Statistical|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm429', '17925306', 'Microarray experiments that allow simultaneous expression profiling of thousands of genes in various conditions (tissues, cells or time) generate data whose analysis raises difficult problems. In particular, there is a vast disproportion between the number of attributes (tens of thousands) and the number of examples (several tens). Dimension reduction is therefore a key step before applying classification approaches. Many methods have been proposed to this purpose, but only a few of them considered a direct quantification of transcriptional interactions. We describe and experimentally validate a new dimension reduction and feature construction method, which assesses interactions between expression profiles to improve microarray-based classification accuracy.'),
(73753, 2007, 'bio', 'CellLine, a stochastic cell lineage simulator', 'Ribeiro, Andre S|Charlebois, Daniel A|Lloyd-Price, Jason', 'Institute for Biocomplexity and Informatics, University of Calgary, Canada. ARibeiro@ucalgary.ca|Institute for Biocomplexity and Informatics, University of Calgary, Canada. ARibeiro@ucalgary.ca|Institute for Biocomplexity and Informatics, University of Calgary, Canada. ARibeiro@ucalgary.ca', 'Canada|Canada|Canada', 9, 'Animals|Cell Differentiation|Cells, Cultured|Computer Simulation|Evolution, Molecular|Humans|Models, Biological|Models, Statistical|Proteome|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btm491', '17928303', 'We present CellLine, a simulator of the dynamics of gene regulatory networks (GRN) in the cells of a lineage. From user-defined reactions and initial substance quantities, it generates cell lineages, i.e. genealogic pedigrees of cells related through mitotic division. Each cells dynamics is driven by a delayed stochastic simulation algorithm (delayed SSA), allowing multiple time delayed reactions. The cells of the lineage can be individually subject to perturbations, such as gene deletion, duplication and mutation. External interventions, such as adding or removing a substance at a given moment, can be specified. Cell differentiation lineages, where differentiation is stochastically driven or externally induced, can be modeled as well. Finally, CellLine can generate and simulate the dynamics of multiple copies of any given cell of the lineage. As examples of CellLine use, we simulate the following systems: cell lineages containing a model of the P53-Mdm2 feedback loop, a differentiation lineage where each cell contains a 4 gene repressilator (a bistable circuit), a model of the differentiation of the cells of the retinal mosaic required for color vision in Drosophila melanogaster, where the differentiation pathway depends on one substances concentration that is controlled by a stochastic process, and a 9 gene GRN to illustrate the advantage of using CellLine rather than simulating multiple independent cells, in cases where the cells of the lineage are dynamically correlated.'),
(73754, 2007, 'bio', 'Conformational analysis of alternative protein structures', 'Domingues, Francisco S|Rahnenführer, Jörg|Lengauer, Thomas', 'Max-Planck-Institut Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. doming@mpi-sb.mpg.de|Max-Planck-Institut Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. doming@mpi-sb.mpg.de|Max-Planck-Institut Informatik, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. doming@mpi-sb.mpg.de', 'Germany|Germany|Germany', 6, 'Algorithms|Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm499', '17933849', 'Alternative structural models determined experimentally are available for an increasing number of proteins. Structural and functional studies of these proteins need to take these models into consideration as they can present considerable structural differences. The characterization of the structural differences and similarities between these models is a fundamental task in structural biology requiring appropriate methods.'),
(73755, 2007, 'bio', 'Steady-state expression of self-regulated genes', 'Fournier, T|Gabriel, J P|Mazza, C|Pasquier, J|Galbete, J L|Mermod, N', 'Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.|Department of Mathematics, University of Fribourg, Chemin du Musée 23, CH-1700 Fribourg, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 11, 'Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Models, Statistical|Proteome|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btm490', '17933850', 'Regulatory gene networks contain generic modules such as feedback loops that are essential for the regulation of many biological functions. The study of the stochastic mechanisms of gene regulation is instrumental for the understanding of how cells maintain their expression at levels commensurate with their biological role, as well as to engineer gene expression switches of appropriate behavior. The lack of precise knowledge on the steady-state distribution of gene expression requires the use of Gillespie algorithms and Monte-Carlo approximations.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73756, 2007, 'bio', 'Incorporating prior knowledge of gene functional groups into regularized discriminant analysis of microarray data', 'Tai, Feng|Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA.|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA.', 'United States|United States', 36, 'Algorithms|Artificial Intelligence|Data Interpretation, Statistical|Discriminant Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm488', '17933851', 'Discriminant analysis for high-dimensional and low-sample-sized data has become a hot research topic in bioinformatics, mainly motivated by its importance and challenge in applications to tumor classifications for high-dimensional microarray data. Two of the popular methods are the nearest shrunken centroids, also called predictive analysis of microarray (PAM), and shrunken centroids regularized discriminant analysis (SCRDA). Both methods are modifications to the classic linear discriminant analysis (LDA) in two aspects tailored to high-dimensional and low-sample-sized data: one is the regularization of the covariance matrix, and the other is variable selection through shrinkage. In spite of their usefulness, there are potential limitations with each method. The main concern is that both PAM and SCRDA are possibly too extreme: the covariance matrix in the former is restricted to be diagonal while in the latter there is barely any restriction. Based on the biology of gene functions and given the feature of the data, it may be beneficial to estimate the covariance matrix as an intermediate between the two, furthermore, more effective shrinkage schemes may be possible.'),
(73757, 2007, 'bio', 'A congruence index for testing topological similarity between trees', 'de Vienne, Damien M|Giraud, Tatiana|Martin, Olivier C', 'University Paris-Sud, Laboratoire Ecologie Systématique et Evolution, UMR8079, Orsay, F-91405, Paris, France. damien.de-vienne@u-psud.fr|University Paris-Sud, Laboratoire Ecologie Systématique et Evolution, UMR8079, Orsay, F-91405, Paris, France. damien.de-vienne@u-psud.fr|University Paris-Sud, Laboratoire Ecologie Systématique et Evolution, UMR8079, Orsay, F-91405, Paris, France. damien.de-vienne@u-psud.fr', 'France|France|France', 126, 'Algorithms|Animals|Biological Evolution|Computer Simulation|Genetics, Population|Host-Parasite Interactions|Humans|Models, Genetic|Phylogeny', 'Journal Article', '10.1093/bioinformatics/btm500', '17933852', 'Phylogenetic trees are omnipresent in evolutionary biology and the comparison of trees plays a central role there. Tree congruence statistics are based on the null hypothesis that two given trees are not more congruent (topologically similar) than expected by chance. Usually, one searches for the most parsimonious evolutionary scenario relating two trees and then one tests the null hypothesis by generating a high number of random trees and comparing these to the one between the observed trees. However, this approach requires a lot of computational work (human and machine) and the results depend on the evolutionary assumptions made.'),
(73758, 2007, 'bio', 'Carbon-fate maps for metabolic reactions', 'Mu, Fangping|Williams, Robert F|Unkefer, Clifford J|Unkefer, Pat J|Faeder, James R|Hlavacek, William S', 'Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.|Theoretical Division, Los Alamos National Laboratory, Los Alamos, NM 87545, USA.', 'United States|United States|United States|United States|United States|United States', 31, 'Algorithms|Carbon Radioisotopes|Gene Expression Profiling|Isotope Labeling|Magnetic Resonance Imaging|Multienzyme Complexes|Peptide Mapping', 'Journal Article', '10.1093/bioinformatics/btm498', '17933853', 'Stable isotope labeling of small-molecule metabolites (e.g. (13)C-labeling of glucose) is a powerful tool for characterizing pathways and reaction fluxes in a metabolic network. Analysis of isotope labeling patterns requires knowledge of the fates of individual atoms and moieties in reactions, which can be difficult to collect in a useful form when considering a large number of enzymatic reactions.'),
(73759, 2007, 'bio', 'MDQC: a new quality assessment method for microarrays based on quality control reports', 'Cohen Freue, Gabriela V|Hollander, Zsuzsanna|Shen, Enqing|Zamar, Ruben H|Balshaw, Robert|Scherer, Andreas|McManus, Bruce|Keown, Paul|McMaster, W Robert|Ng, Raymond T', 'Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca|Department of Computer Science, University of British Columbia, Vancouver, British Columbia, Canada. gcohen@mrl.ubc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 30, 'Algorithms|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Evaluation Studies', '10.1093/bioinformatics/btm487', '17933854', 'The process of producing microarray data involves multiple steps, some of which may suffer from technical problems and seriously damage the quality of the data. Thus, it is essential to identify those arrays with low quality. This article addresses two questions: (1) how to assess the quality of a microarray dataset using the measures provided in quality control (QC) reports, (2) how to identify possible sources of the quality problems.'),
(73760, 2007, 'bio', 'Creating protein models from electron-density maps using particle-filtering methods', 'DiMaio, Frank|Kondrashov, Dmitry A|Bitto, Eduard|Soni, Ameet|Bingman, Craig A|Phillips, George N|Shavlik, Jude W', 'Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu|Department of Computer Sciences, University of Wisconsin, Madison, WI 53706, USA. dimaio@cs.wisc.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Absorptiometry, Photon|Algorithms|Computer Simulation|Crystallography, X-Ray|Filtration|Models, Chemical|Models, Molecular|Models, Statistical|Particle Size|Protein Conformation|Proteins', 'Journal Article', '10.1093/bioinformatics/btm480', '17933855', 'One bottleneck in high-throughput protein crystallography is interpreting an electron-density map, that is, fitting a molecular model to the 3D picture crystallography produces. Previously, we developed ACMI (Automatic Crystallographic Map Interpreter), an algorithm that uses a probabilistic model to infer an accurate protein backbone layout. Here, we use a sampling method known as particle filtering to produce a set of all-atom protein models. We use the output of ACMI to guide the particle filters sampling, producing an accurate, physically feasible set of structures.'),
(73761, 2007, 'bio', 'InterProSurf: a web server for predicting interacting sites on protein surfaces', 'Negi, Surendra S|Schein, Catherine H|Oezguen, Numan|Power, Trevor D|Braun, Werner', 'Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0857, USA.|Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0857, USA.|Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0857, USA.|Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0857, USA.|Department of Biochemistry and Molecular Biology, Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, Texas 77555-0857, USA.', 'United States|United States|United States|United States|United States', 104, 'Algorithms|Binding Sites|Internet|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm474', '17933856', 'A new web server, InterProSurf, predicts interacting amino acid residues in proteins that are most likely to interact with other proteins, given the 3D structures of subunits of a protein complex. The prediction method is based on solvent accessible surface area of residues in the isolated subunits, a propensity scale for interface residues and a clustering algorithm to identify surface regions with residues of high interface propensities. Here we illustrate the application of InterProSurf to determine which areas of Bacillus anthracis toxins and measles virus hemagglutinin protein interact with their respective cell surface receptors. The computationally predicted regions overlap with those regions previously identified as interface regions by sequence analysis and mutagenesis experiments.'),
(73762, 2007, 'bio', 'Optimization of HAART with genetic algorithms and agent-based models of HIV infection', 'Castiglione, F|Pappalardo, F|Bernaschi, M|Motta, S', 'Institute for Computing Applications M. Picone, Consiglio Nazionale delle Ricerche (CNR), V.le del Policlinico, 137, 00161 Rome, Italy. f.castiglione@iac.cnr.it|Institute for Computing Applications M. Picone, Consiglio Nazionale delle Ricerche (CNR), V.le del Policlinico, 137, 00161 Rome, Italy. f.castiglione@iac.cnr.it|Institute for Computing Applications M. Picone, Consiglio Nazionale delle Ricerche (CNR), V.le del Policlinico, 137, 00161 Rome, Italy. f.castiglione@iac.cnr.it|Institute for Computing Applications M. Picone, Consiglio Nazionale delle Ricerche (CNR), V.le del Policlinico, 137, 00161 Rome, Italy. f.castiglione@iac.cnr.it', 'Italy|Italy|Italy|Italy', 0, 'Algorithms|Anti-HIV Agents|Antiretroviral Therapy, Highly Active|Computer Simulation|Drug Administration Schedule|Drug Therapy, Computer-Assisted|HIV Infections|Humans|Immunity, Innate|Models, Immunological', 'Journal Article', '10.1093/bioinformatics/btm408', '17942443', 'Highly Active AntiRetroviral Therapies (HAART) can prolong life significantly to people infected by HIV since, although unable to eradicate the virus, they are quite effective in maintaining control of the infection. However, since HAART have several undesirable side effects, it is considered useful to suspend the therapy according to a suitable schedule of Structured Therapeutic Interruptions (STI). In the present article we describe an application of genetic algorithms (GA) aimed at finding the optimal schedule for a HAART simulated with an agent-based model (ABM) of the immune system that reproduces the most significant features of the response of an organism to the HIV-1 infection.'),
(73763, 2007, 'bio', 'Predicting disulfide connectivity from protein sequence using multiple sequence feature vectors and secondary structure', 'Song, Jiangning|Yuan, Zheng|Tan, Hao|Huber, Thomas|Burrage, Kevin', 'Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia.|Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia.|Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia.|Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia.|Advanced Computational Modelling Centre, The University of Queensland, Brisbane, QLD 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia', 64, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Computer Simulation|Disulfides|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm505', '17942444', 'Disulfide bonds are primary covalent crosslinks between two cysteine residues in proteins that play critical roles in stabilizing the protein structures and are commonly found in extracy-toplasmatic or secreted proteins. In protein folding prediction, the localization of disulfide bonds can greatly reduce the search in conformational space. Therefore, there is a great need to develop computational methods capable of accurately predicting disulfide connectivity patterns in proteins that could have potentially important applications.'),
(73764, 2007, 'bio', 'Mining experimental evidence of molecular function claims from the literature', 'Crangle, Colleen E|Cherry, J Michael|Hong, Eurie L|Zbyslaw, Alex', 'Converspeech LLC, 60 Kirby Place, Palo Alto, CA 94301, USA. crangle@converspeech.com|Converspeech LLC, 60 Kirby Place, Palo Alto, CA 94301, USA. crangle@converspeech.com|Converspeech LLC, 60 Kirby Place, Palo Alto, CA 94301, USA. crangle@converspeech.com|Converspeech LLC, 60 Kirby Place, Palo Alto, CA 94301, USA. crangle@converspeech.com', 'United States|United States|United States|United States', 8, 'Artificial Intelligence|Evidence-Based Medicine|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm495', '17942445', 'The rate at which gene-related findings appear in the scientific literature makes it difficult if not impossible for biomedical scientists to keep fully informed and up to date. The importance of these findings argues for the development of automated methods that can find, extract and summarize this information. This article reports on methods for determining the molecular function claims that are being made in a scientific article, specifically those that are backed by experimental evidence.'),
(73765, 2007, 'bio', 'PFRES: protein fold classification by using evolutionary information and predicted secondary structure', 'Chen, Ke|Kurgan, Lukasz', 'Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.|Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada.', 'Canada|Canada', 0, 'Algorithms|Amino Acid Sequence|Computational Biology|Computer Simulation|Models, Chemical|Models, Genetic|Models, Molecular|Molecular Sequence Data|Protein Folding|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm475', '17942446', 'The number of protein families has been estimated to be as small as 1000. Recent study shows that the growth in discovery of novel structures that are deposited into PDB and the related rate of increase of SCOP categories are slowing down. This indicates that the protein structure space will be soon covered and thus we may be able to derive most of remaining structures by using the known folding patterns. Present tertiary structure prediction methods behave well when a homologous structure is predicted, but give poorer results when no homologous templates are available. At the same time, some proteins that share twilight-zone sequence identity can form similar folds. Therefore, determination of structural similarity without sequence similarity would be beneficial for prediction of tertiary structures.'),
(73766, 2008, 'bio', 'i-ADHoRe 20: an improved tool to detect degenerated genomic homology using genomic profiles', 'Simillion, Cedric|Janssens, Koen|Sterck, Lieven|Van de Peer, Yves', 'Institute for Cell and Molecular Biosciences (ICaMB), Newcastle University, Newcastle-upon-Tyne, UK.|Institute for Cell and Molecular Biosciences (ICaMB), Newcastle University, Newcastle-upon-Tyne, UK.|Institute for Cell and Molecular Biosciences (ICaMB), Newcastle University, Newcastle-upon-Tyne, UK.|Institute for Cell and Molecular Biosciences (ICaMB), Newcastle University, Newcastle-upon-Tyne, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 38, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Evolution, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btm449', '17947255', 'i-ADHoRe is a software tool that combines gene content and gene order information of homologous genomic segments into profiles to detect highly degenerated homology relations within and between genomes. The new version offers, besides a significant increase in performance, several optimizations to the algorithm, most importantly to the profile alignment routine. As a result, the annotations of multiple genomes, or parts thereof, can be fed simultaneously into the program, after which it will report all regions of homology, both within and between genomes.'),
(73767, 2007, 'bio', 'NAPROC-13: a database for the dereplication of natural product mixtures in bioassay-guided protocols', 'López-Pérez, José Luis|Therón, Roberto|del Olmo, Esther|Díaz, David', 'Departamento de Química Farmacéutica, Facultad de Farmacia, Campus M. Unamuno, Universidad de Salamanca, Spain.|Departamento de Química Farmacéutica, Facultad de Farmacia, Campus M. Unamuno, Universidad de Salamanca, Spain.|Departamento de Química Farmacéutica, Facultad de Farmacia, Campus M. Unamuno, Universidad de Salamanca, Spain.|Departamento de Química Farmacéutica, Facultad de Farmacia, Campus M. Unamuno, Universidad de Salamanca, Spain.', 'Spain|Spain|Spain|Spain', 0, 'Biological Assay|Biological Products|Combinatorial Chemistry Techniques|Complex Mixtures|Database Management Systems|Databases, Factual|Internet|Mass Spectrometry|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm516', '17956876', 'Although natural products represent a reservoir of molecular diversity, the process of isolating and identifying active compounds is a bottleneck in drug discovery programs. The rapid isolation and identification of the bioactive component(s) of natural product mixtures during the bioassay-guided fractionation have become crucial factors in the competition with chemical compound libraries and combinatorial synthetic efforts. In this respect, the use of spectral databases in identification processes is indispensable.'),
(73768, 2007, 'bio', 'Electronically subtracting expression patterns from a mixed cell population', 'Gosink, Mark M|Petrie, Howard T|Tsinoremas, Nicholas F', 'Scientific Computing, Scripps Florida, 5353 Parkside Dr Jupiter, FL 33458, USA. gosink@scripps.edu|Scientific Computing, Scripps Florida, 5353 Parkside Dr Jupiter, FL 33458, USA. gosink@scripps.edu|Scientific Computing, Scripps Florida, 5353 Parkside Dr Jupiter, FL 33458, USA. gosink@scripps.edu', 'United States|United States|United States', 0, 'Algorithms|Animals|Artificial Intelligence|Cell Physiological Phenomena|Coculture Techniques|Gene Expression|Gene Expression Profiling|Mice|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome', 'Journal Article', '10.1093/bioinformatics/btm508', '17956877', 'Biological samples frequently contain multiple cell-types that each can play a crucial role in the development and/or regulation of adjacent cells or tissues. The search for biomarkers, or expression patterns of, one cell-type in those samples can be a complex and time-consuming process. Ordinarily, extensive laboratory bench work must be performed to separate the mixed cell population into its subcomponents, such that each can be accurately characterized.'),
(73769, 2007, 'bio', 'On the hierarchical classification of G protein-coupled receptors', 'Davies, Matthew N|Secker, Andrew|Freitas, Alex A|Mendao, Miguel|Timmis, Jon|Flower, Darren R', 'Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk|Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk|Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk|Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk|Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk|Edward Jenner Institute, Compton, Newbury, Berkshire, UK. m.davies@mail.cryst.bbk.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 56, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Pattern Recognition, Automated|Receptors, G-Protein-Coupled|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm506', '17956878', 'G protein-coupled receptors (GPCRs) play an important role in many physiological systems by transducing an extracellular signal into an intracellular response. Over 50% of all marketed drugs are targeted towards a GPCR. There is considerable interest in developing an algorithm that could effectively predict the function of a GPCR from its primary sequence. Such an algorithm is useful not only in identifying novel GPCR sequences but in characterizing the interrelationships between known GPCRs.'),
(73770, 2007, 'bio', 'Boosting multiclass learning with repeating codes and weak detectors for protein subcellular localization', 'Lin, Chung-Chih|Tsai, Yuh-Show|Lin, Yu-Shi|Chiu, Tai-Yu|Hsiung, Chia-Cheng|Lee, May-I|Simpson, Jeremy C|Hsu, Chun-Nan', 'Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.|Faculty of Life Sciences and Institute of Genomes, National Yang-Ming University, Taipei, Taiwan.', '-|-|-|-|-|-|-|-', 0, 'Algorithms|Artificial Intelligence|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Pattern Recognition, Automated|Proteins|Subcellular Fractions', 'Journal Article', '10.1093/bioinformatics/btm497', '17956879', 'Determining locations of protein expression is essential to understand protein function. Advances in green fluorescence protein (GFP) fusion proteins and automated fluorescence microscopy allow for rapid acquisition of large collections of protein localization images. Recognition of these cell images requires an automated image analysis system. Approaches taken by previous work concentrated on designing a set of optimal features and then applying standard machine-learning algorithms. In fact, trends of recent advances in machine learning and computer vision can be applied to improve the performance. One trend is the advances in multiclass learning with error-correcting output codes (ECOC). Another trend is the use of a large number of weak detectors with boosting for detecting objects in images of real-world scenes.'),
(73771, 2007, 'bio', 'VisGenome: visualization of single and comparative genome representations', 'Jakubowska, Joanna|Hunt, Ela|Chalmers, Matthew|McBride, Martin|Dominiczak, Anna F', 'Department of Computing Science, University of Glasgow, G12 8QQ, Scotland. asia@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, G12 8QQ, Scotland. asia@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, G12 8QQ, Scotland. asia@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, G12 8QQ, Scotland. asia@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, G12 8QQ, Scotland. asia@dcs.gla.ac.uk', '-|-|-|-|-', 1, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Humans|Mice|Molecular Sequence Data|Rats|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm394', '17965437', 'VisGenome visualizes single and comparative representations for the rat, the mouse and the human chromosomes at different levels of detail. The tool offers smooth zooming and panning which is more flexible than seen in other browsers. It presents information available in Ensembl for single chromosomes, as well as homologies (orthologue predictions including ortholog one2one, apparent ortholog one2one, ortholog many2many) for any two chromosomes from different species. The application can query supporting data from Ensembl by invoking a link in a browser.'),
(73772, 2007, 'bio', 'A computational strategy for the prediction of functional linear peptide motifs in proteins', 'Dinkel, Holger|Sticht, Heinrich', 'Abteilung für Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.|Abteilung für Bioinformatik, Institut für Biochemie, Friedrich-Alexander-Universität Erlangen-Nürnberg, 91054 Erlangen, Germany.', 'Germany|Germany', 32, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Binding Sites|Computer Simulation|Models, Chemical|Molecular Sequence Data|Peptides|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm524', '17977881', 'Short linear peptide motifs mediate protein-protein interaction, cell compartment targeting and represent the sites of post-translational modification. The identification of functional motifs by conventional sequence searches, however, is hampered by the short length of the motifs resulting in a large number of hits of which only a small portion is functional.'),
(73773, 2007, 'bio', 'PfamAlyzer: domain-centric homology search', 'Hollich, Volker|Sonnhammer, Erik L L', 'Department of Cell and Molecular Biology, Karolinska Institutet, S-171 77 Stockholm, Sweden.|Department of Cell and Molecular Biology, Karolinska Institutet, S-171 77 Stockholm, Sweden.', 'Sweden|Sweden', 7, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Programming Languages|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm521', '17977882', 'PfamAlyzer is a Java applet that enables exploration of Pfam domain architectures using a user-friendly graphical interface. It can search the UniProt protein database for a domain pattern. Domain patterns similar to the query are presented graphically by PfamAlyzer either in a ranked list or pinned to the tree of life. Such domain-centric homology search can assist identification of distant homologs with shared domain architecture.'),
(73774, 2007, 'bio', 'NPIDB: a database of nucleic acids-protein interactions', 'Spirin, Sergei|Titov, Mikhail|Karyagina, Anna|Alexeevski, Andrei', 'A.N.Belozersky Institute of Physical and Chemical Biology, Moscow State University, Moscow, Russia. sas@belozersky.msu.ru|A.N.Belozersky Institute of Physical and Chemical Biology, Moscow State University, Moscow, Russia. sas@belozersky.msu.ru|A.N.Belozersky Institute of Physical and Chemical Biology, Moscow State University, Moscow, Russia. sas@belozersky.msu.ru|A.N.Belozersky Institute of Physical and Chemical Biology, Moscow State University, Moscow, Russia. sas@belozersky.msu.ru', '-|-|-|-', 9, 'Binding Sites|DNA-Binding Proteins|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Nucleic Acids|Protein Binding|Protein Interaction Mapping|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm519', '17977883', 'The database NPIDB (Nucleic Acids-Protein Interaction DataBase) contains information derived from structures of DNA-protein and RNA-protein complexes extracted from PDB (1834 complexes in July 2007). It is organized as a collection of files in PDB format and is equipped with a web-interface and a set of tools for extracting biologically meaningful characteristics of complexes. The content of the database is weekly updated.'),
(73775, 2007, 'bio', 'Ensemble learning of genetic networks from time-series expression data', 'Nam, Dougu|Yoon, Sung Ho|Kim, Jihyun F', 'Korea Research Institute of Bioscience and Biotechnology (KRIBB), PO Box 115, Yuseong, Daejeon 305-600, Republic of Korea. dunam@nims.re.kr|Korea Research Institute of Bioscience and Biotechnology (KRIBB), PO Box 115, Yuseong, Daejeon 305-600, Republic of Korea. dunam@nims.re.kr|Korea Research Institute of Bioscience and Biotechnology (KRIBB), PO Box 115, Yuseong, Daejeon 305-600, Republic of Korea. dunam@nims.re.kr', '-|-|-', 0, 'Algorithms|Computer Simulation|Gene Expression|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Proteome|Signal Transduction|Time Factors', 'Journal Article', '10.1093/bioinformatics/btm514', '17977884', 'Inferring genetic networks from time-series expression data has been a great deal of interest. In most cases, however, the number of genes exceeds that of data points which, in principle, makes it impossible to recover the underlying networks. To address the dimensionality problem, we apply the subset selection method to a linear system of difference equations. Previous approaches assign the single most likely combination of regulators to each target gene, which often causes over-fitting of the small number of data.'),
(73776, 2007, 'bio', 'CONSORF: a consensus prediction system for prokaryotic coding sequences', 'Kang, Sungsoo|Yang, Sung-Jin|Kim, Sangsoo|Bhak, Jong', 'KOBIC (Korean BioInformation Center), KRIBB, Daejeon 305-806 and Soongsil University, 1-1 Sangdo-dong, Dongjak-gu, Seoul 156-743, Korea.|KOBIC (Korean BioInformation Center), KRIBB, Daejeon 305-806 and Soongsil University, 1-1 Sangdo-dong, Dongjak-gu, Seoul 156-743, Korea.|KOBIC (Korean BioInformation Center), KRIBB, Daejeon 305-806 and Soongsil University, 1-1 Sangdo-dong, Dongjak-gu, Seoul 156-743, Korea.|KOBIC (Korean BioInformation Center), KRIBB, Daejeon 305-806 and Soongsil University, 1-1 Sangdo-dong, Dongjak-gu, Seoul 156-743, Korea.', '-|-|-|-', 6, 'Algorithms|Base Sequence|Chromosome Mapping|Consensus Sequence|Genome, Bacterial|Molecular Sequence Data|Open Reading Frames|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm512', '17977885', 'CONSORF is a fully automatic high-accuracy identification system that provides consensus prokaryotic CDS information. It first predicts the CDSs supported by consensus alignments. The alignments are derived from multiple genome-to-proteome comparisons with other prokaryotes using the FASTX program. Then, it fills the empty genomic regions with the CDSs supported by consensus ab initio predictions. From those consensus results, CONSORF provides prediction reliability scores, predicted frame-shifts, alternative start sites and best pair-wise match information against other prokaryotes. These results are easily accessed from a website.'),
(73777, 2007, 'bio', 'Graph sharpening plus graph integration: a synergy that improves protein functional classification', 'Shin, Hyunjung|Lisewski, Andreas Martin|Lichtarge, Olivier', 'Department of Industrial & Information Systems Engineering, Ajou University, San 5, Wonchun-dong, Yeoungtong-gu, 443-749, Suwon, Korea. shin@ajou.ac.kr|Department of Industrial & Information Systems Engineering, Ajou University, San 5, Wonchun-dong, Yeoungtong-gu, 443-749, Suwon, Korea. shin@ajou.ac.kr|Department of Industrial & Information Systems Engineering, Ajou University, San 5, Wonchun-dong, Yeoungtong-gu, 443-749, Suwon, Korea. shin@ajou.ac.kr', '-|-|-', 36, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm511', '17977886', 'Predicting protein function is a central problem in bioinformatics, and many approaches use partially or fully automated methods based on various combination of sequence, structure and other information on proteins or genes. Such information establishes relationships between proteins that can be modelled most naturally as edges in graphs. A priori, however, it is often unclear which edges from which graph may contribute most to accurate predictions. For that reason, one established strategy is to integrate all available sources, or graphs as in graph integration, in the hope that the positive signals will add to each other. However, in the problem of functional prediction, noise, i.e. the presence of inaccurate or false edges, can still be large enough that integration alone has little effect on prediction accuracy. In order to reduce noise levels and to improve integration efficiency, we present here a recent method in graph-based learning, graph sharpening, which provides a theoretically firm yet intuitive and practical approach for disconnecting undesirable edges from protein similarity graphs. This approach has several attractive features: it is quick, scalable in the number of proteins, robust with respect to errors and tolerant of very diverse types of protein similarity measures.'),
(73778, 2007, 'bio', 'Accurate prediction of enzyme mutant activity based on a multibody statistical potential', 'Masso, Majid|Vaisman, Iosif I', 'Laboratory for Structural Bioinformatics, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA.|Laboratory for Structural Bioinformatics, School of Computational Sciences, George Mason University, 10900 University Boulevard, MSN 5B3, Manassas, VA 20110, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Artificial Intelligence|Computer Simulation|Data Interpretation, Statistical|Enzyme Activation|Enzymes|Models, Chemical|Models, Molecular|Molecular Sequence Data|Mutagenesis, Site-Directed|Mutation|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btm509', '17977887', 'An important area of research in biochemistry and molecular biology focuses on characterization of enzyme mutants. However, synthesis and analysis of experimental mutants is time consuming and expensive. We describe a machine-learning approach for inferring the activity levels of all unexplored single point mutants of an enzyme, based on a training set of such mutants with experimentally measured activity.'),
(73779, 2007, 'bio', 'Moment invariants as shape recognition technique for comparing protein binding sites', 'Sommer, Ingolf|Müller, Oliver|Domingues, Francisco S|Sander, Oliver|Weickert, Joachim|Lengauer, Thomas', 'Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de|Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany. sommer@mpi-inf.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Interaction Mapping|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btm503', '17977888', 'An approach for identifying similarities of protein-protein binding sites is presented. The geometric shape of a binding site is described by computing a feature vector based on moment invariants. In order to search for similarities, feature vectors of binding sites are compared. Similar feature vectors indicate binding sites with similar shapes.'),
(73780, 2007, 'bio', 'Pepitope: epitope mapping from affinity-selected peptides', 'Mayrose, Itay|Penn, Osnat|Erez, Elana|Rubinstein, Nimrod D|Shlomi, Tomer|Freund, Natalia Tarnovitski|Bublil, Erez M|Ruppin, Eytan|Sharan, Roded|Gershoni, Jonathan M|Martz, Eric|Pupko, Tal', 'Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 69978, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 91, 'Algorithms|Amino Acid Sequence|Binding Sites|Epitope Mapping|Molecular Sequence Data|Peptides|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm493', '17977889', 'Identifying the epitope to which an antibody binds is central for many immunological applications such as drug design and vaccine development. The Pepitope server is a web-based tool that aims at predicting discontinuous epitopes based on a set of peptides that were affinity-selected against a monoclonal antibody of interest. The server implements three different algorithms for epitope mapping: PepSurf, Mapitope, and a combination of the two. The rationale behind these algorithms is that the set of peptides mimics the genuine epitope in terms of physicochemical properties and spatial organization. When the three-dimensional (3D) structure of the antigen is known, the information in these peptides can be used to computationally infer the corresponding epitope. A user-friendly web interface and a graphical tool that allows viewing the predicted epitopes were developed. Pepitope can also be applied for inferring other types of protein-protein interactions beyond the immunological context, and as a general tool for aligning linear sequences to a 3D structure.'),
(73781, 2008, 'bio', 'Synthetic microarray data generation with RANGE and NEMO', 'Long, James|Roth, Mitchell', 'Biotechnology Computing Research Group, University of Alaska Fairbanks, PO Box 757000, Fairbanks, AK, USA. jlong@alaska.edu|Biotechnology Computing Research Group, University of Alaska Fairbanks, PO Box 757000, Fairbanks, AK, USA. jlong@alaska.edu', 'United States|United States', 6, 'Computer Simulation|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Signal Transduction|Software|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm529', '17982169', 'For testing and sensitivity analysis purposes, it is beneficial to have known transcription networks of sufficient size and variability during development of microarray data and network deconvolution algorithms. Description of such networks in a simple language translatable to Systems Biology Markup Language would allow generation of model data for the networks.'),
(73782, 2007, 'bio', 'Unsupervised feature selection under perturbations: meeting the challenges of biological data', 'Varshavsky, Roy|Gottlieb, Assaf|Horn, David|Linial, Michal', 'School of Computer Science and Engineering, The Hebrew University of Jerusalem 91904, Israel. royke@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem 91904, Israel. royke@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem 91904, Israel. royke@cs.huji.ac.il|School of Computer Science and Engineering, The Hebrew University of Jerusalem 91904, Israel. royke@cs.huji.ac.il', 'Israel|Israel|Israel|Israel', 18, 'Algorithms|Artificial Intelligence|Computer Simulation|Databases, Factual|Information Storage and Retrieval|Models, Biological|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm528', '17989091', 'Feature selection methods aim to reduce the complexity of data and to uncover the most relevant biological variables. In reality, information in biological datasets is often incomplete as a result of untrustworthy samples and missing values. The reliability of selection methods may therefore be questioned.'),
(73783, 2007, 'bio', 'Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs', 'Shamim, Mohammad Tabrez Anwar|Anwaruddin, Mohammad|Nagarajaram, H A', 'Laboratory of Computational Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.|Laboratory of Computational Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.|Laboratory of Computational Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.', 'India|India|India', 0, 'Algorithms|Amino Acids|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm527', '17989092', 'Fold recognition is a key step in the protein structure discovery process, especially when traditional sequence comparison methods fail to yield convincing structural homologies. Although many methods have been developed for protein fold recognition, their accuracies remain low. This can be attributed to insufficient exploitation of fold discriminatory features.'),
(73784, 2008, 'bio', 'Novel cell segmentation and online SVM for cell cycle phase identification in automated microscopy', 'Wang, Meng|Zhou, Xiaobo|Li, Fuhai|Huckins, Jeremy|King, Randall W|Wong, Stephen T C', 'Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.|Center for Bioinformatics, Harvard Center for Neurodegeneration and Repair, Harvard Medical School, 3rd floor, 1249 Boylston, Boston, MA 02215, USA.', 'United States|United States|United States|United States|United States|United States', 103, 'Algorithms|Artificial Intelligence|Cell Cycle|Cell Nucleus|Image Enhancement|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm530', '17989093', 'Automated identification of cell cycle phases captured via fluorescent microscopy is very important for understanding cell cycle and for drug discovery. In this article, we propose a novel cell detection method that utilizes both the intensity and shape information of the cell for better segmentation quality. In contrast to conventional off-line learning algorithms, an Online Support Vector Classifier (OSVC) is thus proposed, which removes support vectors from the old model and assigns new training examples weighted according to their importance to accommodate the ever-changing experimental conditions.'),
(73785, 2007, 'bio', 'Hierarchical tree snipping: clustering guided by prior knowledge', 'Dotan-Cohen, Dikla|Melkman, Avraham A|Kasif, Simon', 'Department of Computer Science, Ben Gurion University, Beer Sheva 84105, Israel. dotna@cs.bgu.ac.il|Department of Computer Science, Ben Gurion University, Beer Sheva 84105, Israel. dotna@cs.bgu.ac.il|Department of Computer Science, Ben Gurion University, Beer Sheva 84105, Israel. dotna@cs.bgu.ac.il', 'Israel|Israel|Israel', 0, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Proteome', 'Journal Article', '10.1093/bioinformatics/btm526', '17989094', 'Hierarchical clustering is widely used to cluster genes into groups based on their expression similarity. This method first constructs a tree. Next this tree is partitioned into subtrees by cutting all edges at some level, thereby inducing a clustering. Unfortunately, the resulting clusters often do not exhibit significant functional coherence.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73786, 2008, 'bio', 'Statistical methods to infer cooperative binding among transcription factors in Saccharomyces cerevisiae', 'Datta, Debayan|Zhao, Hongyu', 'Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.|Department of Biomedical Engineering, Yale University, New Haven, CT 06520, USA.', 'United States|United States', 20, 'Algorithms|Cell Cycle|Computational Biology|Computer Simulation|Culture Media|Databases, Protein|Gene Regulatory Networks|Models, Statistical|Protein Binding|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm523', '17989095', 'Transcription factors regulate transcription in prokaryotes and eukaryotes by binding to specific DNA sequences in the regulatory regions of the genes. This regulation usually occurs in a coordinated manner involving multiple transcription factors. Genome-wide location data, also called ChIP-chip data, have enabled researchers to infer the binding sites for individual regulatory proteins. However, current methods to infer binding sites, such as simple thresholding based on p-values, are not optimal for a number of study objectives like combinatorial regulation, leading to potential loss of information. Hence, there is a need to develop more efficient statistical methods for analyzing such data.'),
(73787, 2008, 'bio', 'Rintact: enabling computational analysis of molecular interaction data from the IntAct repository', 'Chiang, Tony|Li, Nianhua|Orchard, Sandra|Kerrien, Samuel|Hermjakob, Henning|Gentleman, Robert|Huber, Wolfgang', 'EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EBI-EMBL, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Computer Graphics|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Programming Languages|Protein Interaction Mapping|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm518', '17989096', 'The IntAct repository is one of the largest and most widely used databases for the curation and storage of molecular interaction data. These datasets need to be analyzed by computational methods. Software packages in the statistical environment R provide powerful tools for conducting such analyses.'),
(73788, 2008, 'bio', 'MetaNetter: inference and visualization of high-resolution metabolomic networks', 'Jourdan, Fabien|Breitling, Rainer|Barrett, Michael P|Gilbert, David', 'UMR1089 Xénobiotiques INRA-ENVT, 180 chemin de Tournefeuille, St-Martin-du-Touch, BP3 31931 Toulouse, France. Fabien.Jourdan@toulouse.inra.fr|UMR1089 Xénobiotiques INRA-ENVT, 180 chemin de Tournefeuille, St-Martin-du-Touch, BP3 31931 Toulouse, France. Fabien.Jourdan@toulouse.inra.fr|UMR1089 Xénobiotiques INRA-ENVT, 180 chemin de Tournefeuille, St-Martin-du-Touch, BP3 31931 Toulouse, France. Fabien.Jourdan@toulouse.inra.fr|UMR1089 Xénobiotiques INRA-ENVT, 180 chemin de Tournefeuille, St-Martin-du-Touch, BP3 31931 Toulouse, France. Fabien.Jourdan@toulouse.inra.fr', 'France|France|France|France', 14, 'Computer Simulation|Gene Expression Profiling|Models, Biological|Protein Interaction Mapping|Proteome|Reproducibility of Results|Sensitivity and Specificity|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm536', '18003642', 'We present a Cytoscape plugin for the inference and visualization of networks from high-resolution mass spectrometry metabolomic data. The software also provides access to basic topological analysis. This open source, multi-platform software has been successfully used to interpret metabolomic experiments and will enable others using filtered, high mass accuracy mass spectrometric data sets to build and analyse networks.'),
(73789, 2008, 'bio', 'Vbmp: variational Bayesian Multinomial Probit Regression for multi-class classification in R', 'Lama, Nicola|Girolami, Mark', 'Medical Statistics Unit, Department of Medicine and Public Health, Second University of Napoli, Italy. nicola.lama@unina2.it|Medical Statistics Unit, Department of Medicine and Public Health, Second University of Napoli, Italy. nicola.lama@unina2.it', 'Italy|Italy', 5, 'Algorithms|Artificial Intelligence|Bayes Theorem|Biomarkers, Tumor|Breast Neoplasms|Gene Expression Profiling|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming Languages|Regression Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btm535', '18003643', 'Vbmp is an R package for Gaussian Process classification of data over multiple classes. It features multinomial probit regression with Gaussian Process priors and estimates class posterior probabilities employing fast variational approximations to the full posterior. This software also incorporates feature weighting by means of Automatic Relevance Determination. Being equipped with only one main function and reasonable default values for optional parameters, vbmp combines flexibility with ease of usage as is demonstrated on a breast cancer microarray study.'),
(73790, 2008, 'bio', 'Uniformization for sampling realizations of Markov processes: applications to Bayesian implementations of codon substitution models', 'Rodrigue, Nicolas|Philippe, Hervé|Lartillot, Nicolas', 'Canadian Institute for Advanced Research, Département de Biochimie, Université de Montréal, C.P. 6821, Succ. Centre-ville, Montréal, Québec Canada. nicolas.rodrigue@umontreal.ca|Canadian Institute for Advanced Research, Département de Biochimie, Université de Montréal, C.P. 6821, Succ. Centre-ville, Montréal, Québec Canada. nicolas.rodrigue@umontreal.ca|Canadian Institute for Advanced Research, Département de Biochimie, Université de Montréal, C.P. 6821, Succ. Centre-ville, Montréal, Québec Canada. nicolas.rodrigue@umontreal.ca', 'Canada|Canada|Canada', 32, 'Algorithms|Bayes Theorem|Chromosome Mapping|Codon|Computer Simulation|Evolution, Molecular|Markov Chains|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Phylogeny|Sample Size|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm532', '18003644', 'Mapping character state changes over phylogenetic trees is central to the study of evolution. However, current probabilistic methods for generating such mappings are ill-suited to certain types of evolutionary models, in particular, the widely used models of codon substitution.'),
(73791, 2008, 'bio', 'Kernel approaches for genic interaction extraction', 'Kim, Seonho|Yoon, Juntae|Yang, Jihoon', 'Department of Computer Science, Sogang University and Daumsoft Inc., Se-Ah Venture Tower, Seoul, Korea. shkim@lex.yonsei.ac.kr|Department of Computer Science, Sogang University and Daumsoft Inc., Se-Ah Venture Tower, Seoul, Korea. shkim@lex.yonsei.ac.kr|Department of Computer Science, Sogang University and Daumsoft Inc., Se-Ah Venture Tower, Seoul, Korea. shkim@lex.yonsei.ac.kr', '-|-|-', 0, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Protein|Gene Expression Profiling|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Proteins|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm544', '18003645', 'Automatic knowledge discovery and efficient information access such as named entity recognition and relation extraction between entities have recently become critical issues in the biomedical literature. However, the inherent difficulty of the relation extraction task, mainly caused by the diversity of natural language, is further compounded in the biomedical domain because biomedical sentences are commonly long and complex. In addition, relation extraction often involves modeling long range dependencies, discontiguous word patterns and semantic relations for which the pattern-based methodology is not directly applicable.'),
(73792, 2008, 'bio', 'Independent component analysis for the extraction of reliable protein signal profiles from MALDI-TOF mass spectra', 'Mantini, Dante|Petrucci, Francesca|Del Boccio, Piero|Pieragostino, Damiana|Di Nicola, Marta|Lugaresi, Alessandra|Federici, Giorgio|Sacchetta, Paolo|Di Ilio, Carmine|Urbani, Andrea', 'Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.|Istituto Tecnologie Avanzate Biomediche (ITAB), Fondazione G. dAnnunzio, Roma, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy|Italy', 36, 'Algorithms|Amino Acid Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Peptide Mapping|Principal Component Analysis|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Journal Article', '10.1093/bioinformatics/btm533', '18003646', 'Independent component analysis (ICA) is a signal processing technique that can be utilized to recover independent signals from a set of their linear mixtures. We propose ICA for the analysis of signals obtained from large proteomics investigations such as clinical multi-subject studies based on MALDI-TOF MS profiling. The method is validated on simulated and experimental data for demonstrating its capability of correctly extracting protein profiles from MALDI-TOF mass spectra.'),
(73793, 2008, 'bio', 'Fast protein fold estimation from NMR-derived distance restraints', 'Angyán, Annamária F|Perczel, András|Pongor, Sándor|Gáspári, Zoltán', 'Institute of Chemistry, Eötvös Loránd University, Budapest, Hungary.|Institute of Chemistry, Eötvös Loránd University, Budapest, Hungary.|Institute of Chemistry, Eötvös Loránd University, Budapest, Hungary.|Institute of Chemistry, Eötvös Loránd University, Budapest, Hungary.', 'Hungary|Hungary|Hungary|Hungary', 8, 'Algorithms|Amino Acid Sequence|Computer Simulation|Magnetic Resonance Spectroscopy|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm564', '18003647', 'PRIDE-NMR is a fast novel method to relate known protein folds to NMR distance restraints. It can be used to obtain a first guess about a structure being determined, as well as to estimate the completeness or verify the correctness of NOE data.'),
(73794, 2008, 'bio', 'Gaining confidence in biological interpretation of the microarray data: the functional consistence of the significant GO categories', 'Yang, Da|Li, Yanhui|Xiao, Hui|Liu, Qing|Zhang, Min|Zhu, Jing|Ma, Wencai|Yao, Chen|Wang, Jing|Wang, Dong|Guo, Zheng|Yang, Baofeng', 'Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.|Department of Bioinformatics, Bio-pharmaceutical Key Laboratory of Heilongjiang Province-Incubator of State Key Laboratory, Harbin Medical University, Harbin 150086, China.', 'China|China|China|China|China|China|China|China|China|China|China|China', 0, 'Algorithms|Biomarkers, Tumor|Databases, Genetic|Gene Expression Profiling|Humans|Information Storage and Retrieval|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm558', '18006543', 'In microarray studies, numerous tools are available for functional enrichment analysis based on GO categories. Most of these tools, due to their requirement of a prior threshold for designating genes as differentially expressed genes (DEGs), are categorized as threshold-dependent methods that often suffer from a major criticism on their changing results with different thresholds.'),
(73795, 2008, 'bio', 'Text processing through Web services: calling Whatizit', 'Rebholz-Schuhmann, Dietrich|Arregui, Miguel|Gaudan, Sylvain|Kirsch, Harald|Jimeno, Antonio', 'European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk|European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK. rebholz@ebi.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 163, 'Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|Internet|MEDLINE|Natural Language Processing|Periodicals as Topic|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm557', '18006544', 'Text-mining (TM) solutions are developing into efficient services to researchers in the biomedical research community. Such solutions have to scale with the growing number and size of resources (e.g. available controlled vocabularies), with the amount of literature to be processed (e.g. about 17 million documents in PubMed) and with the demands of the user community (e.g. different methods for fact extraction). These demands motivated the development of a server-based solution for literature analysis. Whatizit is a suite of modules that analyse text for contained information, e.g. any scientific publication or Medline abstracts. Special modules identify terms and then link them to the corresponding entries in bioinformatics databases such as UniProtKb/Swiss-Prot data entries and gene ontology concepts. Other modules identify a set of selected annotation types like the set produced by the EBIMed analysis pipeline for proteins. In the case of Medline abstracts, Whatizit offers access to EBIs in-house installation via PMID or term query. For large quantities of the users own text, the server can be operated in a streaming mode (http://www.ebi.ac.uk/webservices/whatizit).'),
(73796, 2008, 'bio', 'Computing topological parameters of biological networks', 'Assenov, Yassen|Ramírez, Fidel|Schelhorn, Sven-Eric|Lengauer, Thomas|Albrecht, Mario', 'Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.|Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.|Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.|Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.|Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Stuhlsatzenhausweg 85, 66123 Saarbrücken, Germany.', 'Germany|Germany|Germany|Germany|Germany', 886, 'Algorithms|Computer Simulation|Models, Biological|Protein Interaction Mapping|Proteome|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm554', '18006545', 'Rapidly increasing amounts of molecular interaction data are being produced by various experimental techniques and computational prediction methods. In order to gain insight into the organization and structure of the resultant large complex networks formed by the interacting molecules, we have developed the versatile Cytoscape plugin NetworkAnalyzer. It computes and displays a comprehensive set of topological parameters, which includes the number of nodes, edges, and connected components, the network diameter, radius, density, centralization, heterogeneity, and clustering coefficient, the characteristic path length, and the distributions of node degrees, neighborhood connectivities, average clustering coefficients, and shortest path lengths. NetworkAnalyzer can be applied to both directed and undirected networks and also contains extra functionality to construct the intersection or union of two networks. It is an interactive and highly customizable application that requires no expert knowledge in graph theory from the user.'),
(73797, 2008, 'bio', 'GWAsimulator: a rapid whole-genome simulation program', 'Li, Chun|Li, Mingyao', 'Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA. chun.li@vanderbilt.edu|Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA. chun.li@vanderbilt.edu', 'United States|United States', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Genome|Models, Genetic|Polymorphism, Single Nucleotide|Population Dynamics|Software', 'Journal Article', '10.1093/bioinformatics/btm549', '18006546', 'GWAsimulator implements a rapid moving-window algorithm to simulate genotype data for case-control or population samples from genomic SNP chips. For case-control data, the program generates cases and controls according to a user-specified multi-locus disease model, and can simulate specific regions if desired. The program uses phased genotype data as input and has the flexibility of simulating genotypes for different populations and different genomic SNP chips. When the HapMap phased data are used, the simulated data have similar local LD patterns as the HapMap data. As genome-wide association (GWA) studies become increasingly popular and new GWA data analysis methods are being developed, we anticipate that GWAsimulator will be an important tool for evaluating performance of new GWA analysis methods.'),
(73798, 2008, 'bio', 'TMBpro: secondary structure, beta-contact and tertiary structure prediction of transmembrane beta-barrel proteins', 'Randall, Arlo|Cheng, Jianlin|Sweredoski, Michael|Baldi, Pierre', 'School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.|School of Information and Computer Sciences, University of California, Irvine, CA 92697, USA.', 'United States|United States|United States|United States', 60, 'Amino Acid Sequence|Computational Biology|Membrane Proteins|Molecular Sequence Data|Protein Structure, Secondary|Protein Structure, Tertiary|Software', 'Journal Article', '10.1093/bioinformatics/btm548', '18006547', 'Transmembrane beta-barrel (TMB) proteins are embedded in the outer membranes of mitochondria, Gram-negative bacteria and chloroplasts. These proteins perform critical functions, including active ion-transport and passive nutrient intake. Therefore, there is a need for accurate prediction of secondary and tertiary structure of TMB proteins. Traditional homology modeling methods, however, fail on most TMB proteins since very few non-homologous TMB structures have been determined. Yet, because TMB structures conform to specific construction rules that restrict the conformational space drastically, it should be possible for methods that do not depend on target-template homology to be applied successfully.'),
(73799, 2008, 'bio', 'Determination and validation of principal gene products', 'Tress, Michael L|Wesselink, Jan-Jaap|Frankish, Adam|López, Gonzalo|Goldman, Nick|Löytynoja, Ari|Massingham, Tim|Pardi, Fabio|Whelan, Simon|Harrow, Jennifer|Valencia, Alfonso', 'Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es|Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre, Madrid, Spain. mtress@cnio.es', 'Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain|Spain', 15, 'Algorithms|Alternative Splicing|Evolution, Molecular|Gene Expression Profiling|Protein Isoforms|Sequence Alignment|Sequence Analysis|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/btm547', '18006548', 'Alternative splicing has the potential to generate a wide range of protein isoforms. For many computational applications and for experimental research, it is important to be able to concentrate on the isoform that retains the core biological function. For many genes this is far from clear.'),
(73800, 2008, 'bio', 'Gene Set Expression Comparison kit for BRB-ArrayTools', 'Xu, Xiaojiang|Zhao, Yingdong|Simon, Richard', 'Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA.|Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA.|Biometric Research Branch, National Cancer Institute, 9000 Rockville Pike, Bethesda, MD 20892-7434, USA.', 'United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software', 'Journal Article', '10.1093/bioinformatics/btm541', '18006549', 'A Gene Set Expression Comparison kit is developed as a module of BRB-ArrayTools for discovering biologically meaningful patterns in gene expression data. The kit consists of gene sets of transcription factor (TF) targets, gene sets containing genes whose protein products share the same protein domain and gene sets of microRNA targets. Using this module of BRB-ArrayTools, researchers can efficiently analyze pre-defined sets of gene whose expression is correlated with a categorical quantitative phenotype or patient survival.'),
(73801, 2008, 'bio', 'GEIGER: investigating evolutionary radiations', 'Harmon, Luke J|Weir, Jason T|Brock, Chad D|Glor, Richard E|Challenger, Wendell', 'Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA. lukeh@uidaho.edu|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA. lukeh@uidaho.edu|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA. lukeh@uidaho.edu|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA. lukeh@uidaho.edu|Department of Biological Sciences, University of Idaho, Moscow, ID 83844, USA. lukeh@uidaho.edu', 'United States|United States|United States|United States|United States', 1426, 'Algorithms|Animals|Biological Evolution|Chromosome Mapping|Computer Graphics|Computer Simulation|Genetics, Population|Humans|Models, Genetic|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm538', '18006550', 'GEIGER is a new software package, written in the R language, to describe evolutionary radiations. GEIGER can carry out simulations, parameter estimation and statistical hypothesis testing. Additionally, GEIGERs simulation algorithms can be used to analyze the statistical power of comparative approaches.'),
(73802, 2007, 'bio', 'MASTR: multiple alignment and structure prediction of non-coding RNAs using simulated annealing', 'Lindgreen, Stinus|Gardner, Paul P|Krogh, Anders', 'Bioinformatics Centre, Department of Molecular Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark. stinus@binf.ku.dk|Bioinformatics Centre, Department of Molecular Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark. stinus@binf.ku.dk|Bioinformatics Centre, Department of Molecular Biology, University of Copenhagen, Ole Maaloes Vej 5, 2200 Copenhagen N, Denmark. stinus@binf.ku.dk', 'Denmark|Denmark|Denmark', 57, 'Algorithms|Base Sequence|Molecular Sequence Data|RNA|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm525', '18006551', 'As more non-coding RNAs are discovered, the importance of methods for RNA analysis increases. Since the structure of ncRNA is intimately tied to the function of the molecule, programs for RNA structure prediction are necessary tools in this growing field of research. Furthermore, it is known that RNA structure is often evolutionarily more conserved than sequence. However, few existing methods are capable of simultaneously considering multiple sequence alignment and structure prediction.'),
(73803, 2007, 'bio', 'Detecting high-order interactions of single nucleotide polymorphisms using genetic programming', 'Nunkesser, Robin|Bernholt, Thorsten|Schwender, Holger|Ickstadt, Katja|Wegener, Ingo', 'Collaborative Research Center 475, Department of Computer Science, University of Dortmund, Dortmund, Germany. robin.nunkesser@uni-dortmund.de|Collaborative Research Center 475, Department of Computer Science, University of Dortmund, Dortmund, Germany. robin.nunkesser@uni-dortmund.de|Collaborative Research Center 475, Department of Computer Science, University of Dortmund, Dortmund, Germany. robin.nunkesser@uni-dortmund.de|Collaborative Research Center 475, Department of Computer Science, University of Dortmund, Dortmund, Germany. robin.nunkesser@uni-dortmund.de|Collaborative Research Center 475, Department of Computer Science, University of Dortmund, Dortmund, Germany. robin.nunkesser@uni-dortmund.de', 'Germany|Germany|Germany|Germany|Germany', 45, 'Base Sequence|Biomarkers, Tumor|Breast Neoplasms|Chromosome Mapping|DNA Mutational Analysis|Genetic Predisposition to Disease|Humans|Molecular Sequence Data|Neoplasm Proteins|Polymorphism, Single Nucleotide|Programming, Linear', 'Journal Article', '10.1093/bioinformatics/btm522', '18006552', 'Not individual single nucleotide polymorphisms (SNPs), but high-order interactions of SNPs are assumed to be responsible for complex diseases such as cancer. Therefore, one of the major goals of genetic association studies concerned with such genotype data is the identification of these high-order interactions. This search is additionally impeded by the fact that these interactions often are only explanatory for a relatively small subgroup of patients. Most of the feature selection methods proposed in the literature, unfortunately, fail at this task, since they can either only identify individual variables or interactions of a low order, or try to find rules that are explanatory for a high percentage of the observations. In this article, we present a procedure based on genetic programming and multi-valued logic that enables the identification of high-order interactions of categorical variables such as SNPs. This method called GPAS cannot only be used for feature selection, but can also be employed for discrimination.'),
(73804, 2007, 'bio', 'Low folding propensity and high translation efficiency distinguish in vivo substrates of GroEL from other Escherichia coli proteins', 'Noivirt-Brik, Orly|Unger, Ron|Horovitz, Amnon', 'Department of Structural Biology, Weizmann Institute, Rehovot 76100, Israel.|Department of Structural Biology, Weizmann Institute, Rehovot 76100, Israel.|Department of Structural Biology, Weizmann Institute, Rehovot 76100, Israel.', 'Israel|Israel|Israel', 20, 'Amino Acid Sequence|Base Sequence|Chaperonin 60|Chromosome Mapping|Escherichia coli Proteins|Molecular Sequence Data|Protein Biosynthesis|Protein Folding', 'Journal Article', '10.1093/bioinformatics/btm513', '18006553', 'Theoretical considerations have indicated that the amount of chaperonin GroEL in Escherichia coli cells is sufficient to fold only approximately 2-5% of newly synthesized proteins under normal physiological conditions, thereby suggesting that only a subset of E.coli proteins fold in vivo in a GroEL-dependent manner. Recently, members of this subset were identified in two independent studies that resulted in two partially overlapping lists of GroEL-interacting proteins. The objective of the work described here was to identify sequence-based features of GroEL-interacting proteins that distinguish them from other E.coli proteins and that may account for their dependence on the chaperonin system.'),
(73805, 2008, 'bio', 'Genome-wide co-expression based prediction of differential expressions', 'Lai, Yinglei', 'Department of Statistics and Biostatistics Center, The George Washington University, 2140 Pennsylvania Avenue, NW Washington, DC 20052, USA. ylai@gwu.edu', 'United States', 8, 'Diabetes Mellitus, Type 2|Gene Expression|Genome|Humans|Male|Models, Theoretical|Prostatic Neoplasms', 'Journal Article', '10.1093/bioinformatics/btm507', '18006554', 'Microarrays have been widely used for medical studies to detect novel disease-related genes. They enable us to study differential gene expressions at a genomic level. They also provide us with informative genome-wide co-expressions. Although many statistical methods have been proposed for identifying differentially expressed genes, genome-wide co-expressions have not been well considered for this issue. Incorporating genome-wide co-expression information in the differential expression analysis may improve the detection of disease-related genes.'),
(73806, 2007, 'bio', 'Genome-wide selection of tag SNPs using multiple-marker correlation', 'Hao, K', 'Algorithm and Data Analysis, Affymetrix, Inc., 3420 Central Expressway, Santa Clara, California, USA. ke_hao@163.com', 'United States', 14, 'Algorithms|Base Sequence|Chromosome Mapping|Expressed Sequence Tags|Genetic Markers|Linkage Disequilibrium|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btm496', '18006555', 'The tag SNP approach is a valuable tool in whole genome association studies, and a variety of algorithms have been proposed to identify the optimal tag SNP set. Currently, most tag SNP selection is based on two-marker (pairwise) linkage disequilibrium (LD). Recent literature has shown that multiple-marker LD also contains useful information that can further increase the genetic coverage of the tag SNP set. Thus, tag SNP selection methods that incorporate multiple-marker LD are expected to have advantages in terms of genetic coverage and statistical power.'),
(73807, 2008, 'bio', 'Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R', 'Langfelder, Peter|Zhang, Bin|Horvath, Steve', 'Department of Human Genetics, University of California at Los Angeles, CA 90095-7088, USA.|Department of Human Genetics, University of California at Los Angeles, CA 90095-7088, USA.|Department of Human Genetics, University of California at Los Angeles, CA 90095-7088, USA.', 'United States|United States|United States', 0, 'Algorithms|Cluster Analysis|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/btm563', '18024473', 'Hierarchical clustering is a widely used method for detecting clusters in genomic data. Clusters are defined by cutting branches off the dendrogram. A common but inflexible method uses a constant height cutoff value, this method exhibits suboptimal performance on complicated dendrograms. We present the Dynamic Tree Cut R package that implements novel dynamic branch cutting methods for detecting clusters in a dendrogram depending on their shape. Compared to the constant height cutoff method, our techniques offer the following advantages: (1) they are capable of identifying nested clusters, (2) they are flexible-cluster shape parameters can be tuned to suit the application at hand, (3) they are suitable for automation, and (4) they can optionally combine the advantages of hierarchical clustering and partitioning around medoids, giving better detection of outliers. We illustrate the use of these methods by applying them to protein-protein interaction network data and to a simulated gene expression data set.'),
(73808, 2008, 'bio', 'BiNoM: a Cytoscape plugin for manipulating and analyzing biological networks', 'Zinovyev, Andrei|Viara, Eric|Calzone, Laurence|Barillot, Emmanuel', 'Institut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. andrei.zinovyev@curie.fr|Institut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. andrei.zinovyev@curie.fr|Institut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. andrei.zinovyev@curie.fr|Institut Curie, Service de Bioinformatique, 26 rue dUlm, F-75248 Paris Cedex 05, France. andrei.zinovyev@curie.fr', 'France|France|France|France', 71, 'Computer Simulation|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Models, Biological|Programming Languages|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm553', '18024474', 'BiNoM (Biological Network Manager) is a new bioinformatics software that significantly facilitates the usage and the analysis of biological networks in standard systems biology formats (SBML, SBGN, BioPAX). BiNoM implements a full-featured BioPAX editor and a method of interfaces for accessing BioPAX content. BiNoM is able to work with huge BioPAX files such as whole pathway databases. In addition, BiNoM allows the analysis of networks created with CellDesigner software and their conversion into BioPAX format. BiNoM comes as a library and as a Cytoscape plugin which adds a rich set of operations to Cytoscape such as path and cycle analysis, clustering sub-networks, decomposition of network into modules, clipboard operations and others.'),
(73809, 2008, 'bio', 'Algebraic stability indicators for ranked lists in molecular profiling', 'Jurman, Giuseppe|Merler, Stefano|Barla, Annalisa|Paoli, Silvano|Galea, Antonio|Furlanello, Cesare', 'FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.|FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.|FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.|FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.|FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.|FBK, via Sommarive 18, I-38100 Povo (Trento), Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy', 62, 'Algorithms|Biomarkers, Tumor|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btm550', '18024475', 'We propose a method for studying the stability of biomarker lists obtained from functional genomics studies. It is common to adopt resampling methods to tune and evaluate marker-based diagnostic and prognostic systems in order to prevent selection bias. Such caution promotes honest estimation of class prediction, but leads to alternative sets of solutions. In microarray studies, the difference in lists may be bewildering, also due to the presence of modules of functionally related genes. Methods for assessing stability understand the dependency of the markers on the data or on the predictors type and help selecting solutions.'),
(73810, 2008, 'bio', 'KUTE-BASE: storing, downloading and exporting MIAME-compliant microarray experiments in minutes rather than hours', 'Draghici, Sorin|Tarca, Adi L|Yu, Longfei|Ethier, Stephen|Romero, Roberto', 'Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA. sod@cs.wayne.edu|Department of Computer Science, Wayne State University, 431 State Hall, Detroit, MI 48202, USA. sod@cs.wayne.edu', 'United States|United States|United States|United States|United States', 4, 'Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm559', '18024967', 'The BioArray Software Environment (BASE) is a very popular MIAME-compliant, web-based microarray data repository. However in BASE, like in most other microarray data repositories, the experiment annotation and raw data uploading can be very timeconsuming, especially for large microarray experiments.'),
(73811, 2008, 'bio', 'A hierarchical statistical model to assess the confidence of peptides and proteins inferred from tandem mass spectrometry', 'Shen, Changyu|Wang, Zhiping|Shankar, Ganesh|Zhang, Xiang|Li, Lang', 'Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu|Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu|Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu|Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu|Division of Biostatistics, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN 46202, USA. chashen@iupui.edu', 'India|India|India|India|India', 32, 'Computer Simulation|Data Interpretation, Statistical|Mass Spectrometry|Models, Chemical|Models, Statistical|Peptide Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm555', '18024968', 'Statistical evaluation of the confidence of peptide and protein identifications made by tandem mass spectrometry is a critical component for appropriately interpreting the experimental data and conducting downstream analysis. Although many approaches have been developed to assign confidence measure from different perspectives, a unified statistical framework that integrates the uncertainty of peptides and proteins is still missing.'),
(73812, 2008, 'bio', 'Identification of linked regions using high-density SNP genotype data in linkage analysis', 'Lin, Guohui|Wang, Zhanyong|Wang, Lusheng|Lau, Yu-Lung|Yang, Wanling', 'Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.|Department of Computing Science, University of Alberta, Edmonton, Alberta T6G 2E8, Canada.', 'Canada|Canada|Canada|Canada|Canada', 15, 'Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Genotype|Humans|Linkage Disequilibrium', 'Journal Article', '10.1093/bioinformatics/btm552', '18024969', 'With the knowledge of large number of SNPs in human genome and the fast development in high-throughput genotyping technologies, identification of linked regions in linkage analysis through allele sharing status determination will play an ever important role, while consideration of recombination fractions becomes unnecessary.'),
(73813, 2008, 'bio', 'SNPtoGO: characterizing SNPs by enriched GO terms', 'Schwarz, Daniel F|Hädicke, Oliver|Erdmann, Jeanette|Ziegler, Andreas|Bayer, Daniel|Möller, Steffen', 'Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de|Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de|Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de|Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de|Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de|Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 11, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Databases, Genetic|Gene Expression Profiling|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm551', '18024970', 'For the analysis of complex polygenic diseases, one does not expect all patients to share the same disease-associated alleles. Not even will disease-causing variations be assigned to the identical sets of genes between patients. However, one does expect overlaps in the sets of genes that are involved and even more so in their assigned molecular processes. Furthermore, the assignment of single nucleotide polymorphisms (SNPs) to genes is highly ambiguous for intergenic SNPs. The tool presented here hence adds external information, i.e. GeneOntology (GO) terms (Gene Ontology Consortium), to the analysis of SNP data.'),
(73814, 2008, 'bio', 'Computational epigenetics', 'Bock, Christoph|Lengauer, Thomas', 'Max-Planck-Institut für Informatik, Saarbrücken, Germany. cbock@mpi-inf.mpg.de|Max-Planck-Institut für Informatik, Saarbrücken, Germany. cbock@mpi-inf.mpg.de', 'Germany|Germany', 130, 'Biological Evolution|Chromosome Mapping|Computational Biology|Epigenesis, Genetic|Evolution, Molecular|Gene Expression Profiling|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/btm546', '18024971', 'Epigenetic research aims to understand heritable gene regulation that is not directly encoded in the DNA sequence. Epigenetic mechanisms such as DNA methylation and histone modifications modulate the packaging of the DNA in the nucleus and thereby influence gene expression. Patterns of epigenetic information are faithfully propagated over multiple cell divisions, which makes epigenetic regulation a key mechanism for cellular differentiation and cell fate decisions. In addition, incomplete erasure of epigenetic information can lead to complex patterns of non-Mendelian inheritance. Stochastic and environment-induced epigenetic defects are known to play a major role in cancer and ageing, and they may also contribute to mental disorders and autoimmune diseases. Recent technical advances such as ChIP-on-chip and ChIP-seq have started to convert epigenetic research into a high-throughput endeavor, to which bioinformatics is expected to make significant contributions. Here, we review pioneering computational studies that have contributed to epigenetic research. In addition, we give a brief introduction into epigenetics-targeted at bioinformaticians who are new to the field-and we outline future challenges in computational epigenetics.'),
(73815, 2008, 'bio', 'A profile-based deterministic sequential Monte Carlo algorithm for motif discovery', 'Liang, Kuo-Ching|Wang, Xiaodong|Anastassiou, Dimitris', 'Columbia University, Department of Electrical Engineering, New York, NY 10025, USA.|Columbia University, Department of Electrical Engineering, New York, NY 10025, USA.|Columbia University, Department of Electrical Engineering, New York, NY 10025, USA.', 'United States|United States|United States', 11, 'Algorithms|Base Sequence|Computer Simulation|DNA|Models, Genetic|Models, Statistical|Molecular Sequence Data|Monte Carlo Method|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm543', '18024972', 'Conserved motifs often represent biological significance, providing insight on biological aspects such as gene transcription regulation, biomolecular secondary structure, presence of non-coding RNAs and evolution history. With the increasing number of sequenced genomic data, faster and more accurate tools are needed to automate the process of motif discovery.'),
(73816, 2008, 'bio', 'Estimation of an in vivo fitness landscape experienced by HIV-1 under drug selective pressure useful for prediction of drug resistance evolution during treatment', 'Deforche, K|Camacho, R|Van Laethem, K|Lemey, P|Rambaut, A|Moreau, Y|Vandamme, A-M', 'Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.|Rega Institute for Medical Research, Katholieke Universiteit Leuven, Leuven, Belgium.', 'Belgium|Belgium|Belgium|Belgium|Belgium|Belgium|Belgium', 27, 'Anti-HIV Agents|Biological Evolution|Chromosome Mapping|Computer Simulation|Drug Resistance, Viral|Genetic Variation|HIV-1|Models, Genetic|Mutation|Selection, Genetic', 'Journal Article', '10.1093/bioinformatics/btm540', '18024973', 'HIV-1 antiviral resistance is a major cause of antiviral treatment failure. The in vivo fitness landscape experienced by the virus in presence of treatment could in principle be used to determine both the susceptibility of the virus to the treatment and the genetic barrier to resistance. We propose a method to estimate this fitness landscape from cross-sectional clinical genetic sequence data of different subtypes, by reverse engineering the required selective pressure for HIV-1 sequences obtained from treatment naive patients, to evolve towards sequences obtained from treated patients. The method was evaluated for recovering 10 random fictive selective pressures in simulation experiments, and for modeling the selective pressure under treatment with the protease inhibitor nelfinavir.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73817, 2008, 'bio', 'Predicting and understanding transcription factor interactions based on sequence level determinants of combinatorial control', 'van Dijk, A D J|ter Braak, C J F|Immink, R G|Angenent, G C|van Ham, R C H J', 'Applied Bioinformatics, PRI, Wageningen UR, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, PRI, Wageningen UR, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, PRI, Wageningen UR, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, PRI, Wageningen UR, Droevendaalsesteeg 1, Wageningen, The Netherlands.|Applied Bioinformatics, PRI, Wageningen UR, Droevendaalsesteeg 1, Wageningen, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 14, 'Amino Acid Sequence|Binding Sites|Combinatorial Chemistry Techniques|Computer Simulation|Data Interpretation, Statistical|Models, Chemical|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm539', '18024974', 'Transcription factor interactions are the cornerstone of combinatorial control, which is a crucial aspect of the gene regulatory system. Understanding and predicting transcription factor interactions based on their sequence alone is difficult since they are often part of families of factors sharing high sequence identity. Given the scarcity of experimental data on interactions compared to available sequence data, however, it would be most useful to have accurate methods for the prediction of such interactions.'),
(73818, 2008, 'bio', 'Multi-RELIEF: a method to recognize specificity determining residues from multiple sequence alignments using a Machine-Learning approach for feature weighting', 'Ye, Kai|Feenstra, K Anton|Heringa, Jaap|Ijzerman, Adriaan P|Marchiori, Elena', 'Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.|Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.|Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.|Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.|Division of Medical Chemistry, LACDR, Leiden University, P.O. Box 9502, 2300 RA, Leiden, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 64, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm537', '18024975', 'Identification of residues that account for protein function specificity is crucial, not only for understanding the nature of functional specificity, but also for protein engineering experiments aimed at switching the specificity of an enzyme, regulator or transporter. Available algorithms generally use multiple sequence alignments to identify residue positions conserved within subfamilies but divergent in between. However, many biological examples show a much subtler picture than simple intra-group conservation versus inter-group divergence.'),
(73819, 2008, 'bio', 'GlobalANCOVA: exploration and assessment of gene group effects', 'Hummel, Manuela|Meister, Reinhard|Mansmann, Ulrich', 'IBE, University of Munich, Technische Fachhochschule Berlin and Department of Statistics, University of Munich, Germany. hummel@ibe.med.uni-muenchen.de|IBE, University of Munich, Technische Fachhochschule Berlin and Department of Statistics, University of Munich, Germany. hummel@ibe.med.uni-muenchen.de|IBE, University of Munich, Technische Fachhochschule Berlin and Department of Statistics, University of Munich, Germany. hummel@ibe.med.uni-muenchen.de', 'Germany|Germany|Germany', 107, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Multigene Family|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm531', '18024976', 'Several authors have studied expression in gene sets with specific goals: overrepresentation of interesting genes in functional groups, predictive power for class membership and searches for groups where the constituent genes show coordinated changes in expression under the experimental conditions. The purpose of this article is to follow the third direction. One important aspect is that the gene sets under analysis are known a priori and are not determined from the experimental data at hand. Our goal is to provide a methodology that helps to identify the relevant structural constituents (phenotypical, experimental design, biological component) that determine gene expression in a group.'),
(73820, 2008, 'bio', 'Straightening Caenorhabditis elegans images', 'Peng, Hanchuan|Long, Fuhui|Liu, Xiao|Kim, Stuart K|Myers, Eugene W', 'Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. pengh@janelia.hhmi.org|Janelia Farm Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA. pengh@janelia.hhmi.org', 'United States|United States|United States|United States|United States', 45, 'Algorithms|Animals|Caenorhabditis elegans|Image Enhancement|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|Microscopy, Fluorescence', 'Journal Article', '10.1093/bioinformatics/btm569', '18025002', 'Caenorhabditis elegans, a roundworm found in soil, is a widely studied model organism with about 1000 cells in the adult. Producing high-resolution fluorescence images of C.elegans to reveal biological insights is becoming routine, motivating the development of advanced computational tools for analyzing the resulting image stacks. For example, worm bodies usually curve significantly in images. Thus one must straighten the worms if they are to be compared under a canonical coordinate system.'),
(73821, 2008, 'bio', 'Clustering of change patterns using Fourier coefficients', 'Kim, Jaehee|Kim, Haseong', 'Department of Statistics, Duksung Womens University, Seoul National University, Seoul, S. Korea. jaehee@duksung.ac.kr|Department of Statistics, Duksung Womens University, Seoul National University, Seoul, S. Korea. jaehee@duksung.ac.kr', '-|-', 10, 'Algorithms|Artificial Intelligence|Cluster Analysis|Fourier Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Saccharomyces cerevisiae Proteins', 'Journal Article', '10.1093/bioinformatics/btm568', '18025003', 'To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a time period because biologically related gene groups can share the same change patterns. Many clustering algorithms have been proposed to group observation data. However, because of the complexity of the underlying functions there have not been many studies on grouping data based on change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. The sample Fourier coefficients not only provide information about the underlying functions, but also reduce the dimension. In addition, as their limiting distribution is a multivariate normal, a model-based clustering method incorporating statistical properties would be appropriate.'),
(73822, 2008, 'bio', 'MANTIS: a phylogenetic framework for multi-species genome comparisons', 'Tzika, Athanasia C|Helaers, Raphaël|Van de Peer, Yves|Milinkovitch, Michel C', 'Laboratory of Evolutionary Genetics, Institute for Molecular Biology & Medicine, Université Libre de Bruxelles, Belgium.|Laboratory of Evolutionary Genetics, Institute for Molecular Biology & Medicine, Université Libre de Bruxelles, Belgium.|Laboratory of Evolutionary Genetics, Institute for Molecular Biology & Medicine, Université Libre de Bruxelles, Belgium.|Laboratory of Evolutionary Genetics, Institute for Molecular Biology & Medicine, Université Libre de Bruxelles, Belgium.', 'Belgium|Belgium|Belgium|Belgium', 10, 'Base Sequence|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm567', '18025004', 'Practitioners of comparative genomics face huge analytical challenges as whole genome sequences and functional/expression data accumulate. Furthermore, the field would greatly benefit from a better integration of this wealth of data with evolutionary concepts.'),
(73823, 2008, 'bio', 'The SBML discrete stochastic models test suite', 'Evans, Thomas W|Gillespie, Colin S|Wilkinson, Darren J', 'Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK.|Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK.|Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK.', 'United Kingdom|United Kingdom|United Kingdom', 23, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Models, Biological|Models, Statistical|Signal Processing, Computer-Assisted|Software|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/btm566', '18025005', 'Stochastic simulation is a very important tool for mathematical modelling. However, it is difficult to check the correctness of a stochastic simulator, since any two realizations from a single model will typically be different.'),
(73824, 2008, 'bio', 'Estimating node degree in bait-prey graphs', 'Scholtens, Denise|Chiang, Tony|Huber, Wolfgang|Gentleman, Robert', 'Department of Preventive Medicine, Northwestern University Medical School, 680 N. Lake Shore Drive Suite 1102, Chicago, IL 60611-4402, USA. dscholtens@northwestern.edu|Department of Preventive Medicine, Northwestern University Medical School, 680 N. Lake Shore Drive Suite 1102, Chicago, IL 60611-4402, USA. dscholtens@northwestern.edu|Department of Preventive Medicine, Northwestern University Medical School, 680 N. Lake Shore Drive Suite 1102, Chicago, IL 60611-4402, USA. dscholtens@northwestern.edu|Department of Preventive Medicine, Northwestern University Medical School, 680 N. Lake Shore Drive Suite 1102, Chicago, IL 60611-4402, USA. dscholtens@northwestern.edu', 'United States|United States|United States|United States', 13, 'Algorithms|Computer Graphics|Computer Simulation|Data Interpretation, Statistical|Models, Biological|Models, Statistical|Protein Interaction Mapping|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm565', '18025006', 'Proteins work together to drive biological processes in cellular machines. Summarizing global and local properties of the set of protein interactions, the interactome, is necessary for describing cellular systems. We consider a relatively simple per-protein feature of the interactome: the number of interaction partners for a protein, which in graph terminology is the degree of the protein.'),
(73825, 2007, 'bio', 'Marker development for the genetic study of natural variation in Arabidopsis thaliana', 'Nemri, Adnane|Neff, Michael M|Burrell, Michael|Jones, Jonathan D G|Studholme, David J', 'Sainsbury Laboratory, Norwich NR4 7UH, UK. adnane.nemri@tsl.ac.uk|Sainsbury Laboratory, Norwich NR4 7UH, UK. adnane.nemri@tsl.ac.uk|Sainsbury Laboratory, Norwich NR4 7UH, UK. adnane.nemri@tsl.ac.uk|Sainsbury Laboratory, Norwich NR4 7UH, UK. adnane.nemri@tsl.ac.uk|Sainsbury Laboratory, Norwich NR4 7UH, UK. adnane.nemri@tsl.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 3, 'Algorithms|Arabidopsis|Base Sequence|DNA Mutational Analysis|DNA Primers|DNA, Plant|Genetic Markers|Genetic Variation|Molecular Sequence Data|Polymorphism, Single Nucleotide|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm501', '18025007', 'We report AtPRIMER, an application that automates the discovery of new polymorphic markers between ecotypes of Arabidopsis thaliana. On specifying two ecotypes and the genomic region of interest, the script retrieves all corresponding single nucleotide polymorphisms (SNPs) and generates CAPS and/or dCAPS PCR primer sequences. We show that AtPRIMER accurately found specific polymorphic markers for our linkage mapping project. AtPRIMER will therefore be useful for efficient marker development with high density and specificity.'),
(73826, 2008, 'bio', 'PedVizApi: a Java API for the interactive, visual analysis of extended pedigrees', 'Fuchsberger, Christian|Falchi, Mario|Forer, Lukas|Pramstaller, Peter P', 'Institute of Genetic Medicine, European Academy, Bolzano, Italy.|Institute of Genetic Medicine, European Academy, Bolzano, Italy.|Institute of Genetic Medicine, European Academy, Bolzano, Italy.|Institute of Genetic Medicine, European Academy, Bolzano, Italy.', 'Italy|Italy|Italy|Italy', 8, 'Algorithms|Computer Graphics|Models, Genetic|Pedigree|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm577', '18033791', 'PedVizApi is a Java API (application program interface) for the visual analysis of large and complex pedigrees. It provides all the necessary functionality for the interactive exploration of extended genealogies. While available packages are mostly focused on a static representation or cannot be added to an existing application, PedVizApi is a highly flexible open source library for the efficient construction of visual-based applications for the analysis of family data. An extensive demo application and a R interface is provided.'),
(73827, 2008, 'bio', 'ARWEN: a program to detect tRNA genes in metazoan mitochondrial nucleotide sequences', 'Laslett, Dean|Canbäck, Björn', 'Murdoch University, Perth, Western Australia, Australia.|Murdoch University, Perth, Western Australia, Australia.', 'Australia|Australia', 680, 'Algorithms|Animals|Base Sequence|Chromosome Mapping|Molecular Sequence Data|RNA|RNA, Mitochondrial|RNA, Transfer|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm573', '18033792', 'Mitochondrial genomes encode their own transfer RNAs (tRNAs). These are often degenerate in sequence and structure compared to tRNAs in their bacterial ancestors. This is one of the reasons why current tRNA gene predictor programs perform poorly identifying mitochondrial tRNA genes. As a consequence there is a need for a new program with the specific aim of predicting these tRNAs.'),
(73828, 2008, 'bio', 'NET-SYNTHESIS: a software for synthesis, inference and simplification of signal transduction networks', 'Kachalo, Sema|Zhang, Ranran|Sontag, Eduardo|Albert, Réka|DasGupta, Bhaskar', 'Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.', 'United States|United States|United States|United States|United States', 29, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Biological|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/btm571', '18033793', 'We present a software for combined synthesis, inference and simplification of signal transduction networks. The main idea of our method lies in representing observed indirect causal relationships as network paths and using techniques from combinatorial optimization to find the sparsest graph consistent with all experimental observations. We illustrate the biological usability of our software by applying it to a previously published signal transduction network and by using it to synthesize and simplify a novel network corresponding to activation-induced cell death in large granular lymphocyte leukemia.'),
(73829, 2008, 'bio', 'Analysis of a Gibbs sampler method for model-based clustering of gene expression data', 'Joshi, Anagha|Van de Peer, Yves|Michoel, Tom', 'Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Gent, Belgium.|Department of Plant Systems Biology, VIB, Technologiepark 927, 9052 Gent, Belgium.', 'Belgium|Belgium|Belgium', 48, 'Algorithms|Cluster Analysis|Fourier Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae Proteins|Sample Size|Signal Processing, Computer-Assisted', 'Journal Article', '10.1093/bioinformatics/btm562', '18033794', 'Over the last decade, a large variety of clustering algorithms have been developed to detect coregulatory relationships among genes from microarray gene expression data. Model-based clustering approaches have emerged as statistically well-grounded methods, but the properties of these algorithms when applied to large-scale data sets are not always well understood. An in-depth analysis can reveal important insights about the performance of the algorithm, the expected quality of the output clusters, and the possibilities for extracting more relevant information out of a particular data set.'),
(73830, 2008, 'bio', 'Improved recognition of figures containing fluorescence microscope images in online journal articles using graphical models', 'Qian, Yuntao|Murphy, Robert F', 'Center for Bioimage Informatics and Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA.|Center for Bioimage Informatics and Machine Learning Department, Carnegie Mellon University, Pittsburgh, USA.', 'United States|United States', 24, 'Algorithms|Computer Graphics|Image Processing, Computer-Assisted|Internet|Microscopy, Fluorescence|Models, Statistical|Publishing', 'Journal Article', '10.1093/bioinformatics/btm561', '18033795', 'There is extensive interest in automating the collection, organization and analysis of biological data. Data in the form of images in online literature present special challenges for such efforts. The first steps in understanding the contents of a figure are decomposing it into panels and determining the type of each panel. In biological literature, panel types include many kinds of images collected by different techniques, such as photographs of gels or images from microscopes. We have previously described the SLIF system (http://slif.cbi.cmu.edu) that identifies panels containing fluorescence microscope images among figures in online journal articles as a prelude to further analysis of the subcellular patterns in such images. This system contains a pretrained classifier that uses image features to assign a type (class) to each separate panel. However, the types of panels in a figure are often correlated, so that we can consider the class of a panel to be dependent not only on its own features but also on the types of the other panels in a figure.'),
(73831, 2008, 'bio', 'Petri net-based method for the analysis of the dynamics of signal propagation in signaling pathways', 'Hardy, Simon|Robillard, Pierre N', 'Department of Computer Engineering, Ecole Polytechnique de Montréal, P.O. Box 6079, Station Centre-Ville, Montréal, H3C 3A7, Canada. simon.hardy@polymtl.ca|Department of Computer Engineering, Ecole Polytechnique de Montréal, P.O. Box 6079, Station Centre-Ville, Montréal, H3C 3A7, Canada. simon.hardy@polymtl.ca', 'Canada|Canada', 32, 'Algorithms|Computer Simulation|Models, Biological|Neural Networks (Computer)|Pattern Recognition, Automated|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm560', '18033796', 'Cellular signaling networks are dynamic systems that propagate and process information, and, ultimately, cause phenotypical responses. Understanding the circuitry of the information flow in cells is one of the keys to understanding complex cellular processes. The development of computational quantitative models is a promising avenue for attaining this goal. Not only does the analysis of the simulation data based on the concentration variations of biological compounds yields information about systemic state changes, but it is also very helpful for obtaining information about the dynamics of signal propagation.'),
(73832, 2008, 'bio', 'Fast and accurate identification of semi-tryptic peptides in shotgun proteomics', 'Alves, Pedro|Arnold, Randy J|Clemmer, David E|Li, Yixue|Reilly, James P|Sheng, Quanhu|Tang, Haixu|Xun, Zhiyin|Zeng, Rong|Radivojac, Predrag', 'School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.|School of Informatics, Bloomington, IN, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 35, 'Amino Acid Sequence|Binding Sites|Molecular Sequence Data|Peptide Mapping|Peptides|Protein Binding|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Trypsin', 'Journal Article', '10.1093/bioinformatics/btm545', '18033797', 'One of the major problems in shotgun proteomics is the low peptide coverage when analyzing complex protein samples. Identifying more peptides, e.g. non-tryptic peptides, may increase the peptide coverage and improve protein identification and/or quantification that are based on the peptide identification results. Searching for all potential non-tryptic peptides is, however, time consuming for shotgun proteomics data from complex samples, and poses a challenge for a routine data analysis.'),
(73833, 2008, 'bio', 'GEAR: genomic enrichment analysis of regional DNA copy number changes', 'Kim, Tae-Min|Jung, Yu-Chae|Rhyu, Mun-Gan|Jung, Myeong Ho|Chung, Yeun-Jun', 'Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul 137-701.|Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul 137-701.|Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul 137-701.|Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul 137-701.|Department of Microbiology, College of Medicine, The Catholic University of Korea, Seoul 137-701.', '-|-|-|-|-', 11, 'Algorithms|Chromosome Aberrations|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Genetic Variation|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm582', '18037611', 'We developed an algorithm named GEAR (genomic enrichment analysis of regional DNA copy number changes) for functional interpretation of genome-wide DNA copy number changes identified by array-based comparative genomic hybridization. GEAR selects two types of chromosomal alterations with potential biological relevance, i.e. recurrent and phenotype-specific alterations. Then it performs functional enrichment analysis using a priori selected functional gene sets to identify primary and clinical genomic signatures. The genomic signatures identified by GEAR represent functionally coordinated genomic changes, which can provide clues on the underlying molecular mechanisms related to the phenotypes of interest. GEAR can help the identification of key molecular functions that are activated or repressed in the tumor genomes leading to the improved understanding on the tumor biology.'),
(73834, 2008, 'bio', 'Genome scale enzyme-metabolite and drug-target interaction predictions using the signature molecular descriptor', 'Faulon, Jean-Loup|Misra, Milind|Martin, Shawn|Sale, Ken|Sapra, Rajat', 'Sandia National Laboratories, Computational Biosciences Department, P.O. Box 5800, Albuquerque, NM 87185-1413, USA. jfaulon@sandia.gov|Sandia National Laboratories, Computational Biosciences Department, P.O. Box 5800, Albuquerque, NM 87185-1413, USA. jfaulon@sandia.gov|Sandia National Laboratories, Computational Biosciences Department, P.O. Box 5800, Albuquerque, NM 87185-1413, USA. jfaulon@sandia.gov|Sandia National Laboratories, Computational Biosciences Department, P.O. Box 5800, Albuquerque, NM 87185-1413, USA. jfaulon@sandia.gov|Sandia National Laboratories, Computational Biosciences Department, P.O. Box 5800, Albuquerque, NM 87185-1413, USA. jfaulon@sandia.gov', 'United States|United States|United States|United States|United States', 111, 'Binding Sites|Chromosome Mapping|Computer Simulation|Databases, Protein|Drug Delivery Systems|Drug Design|Enzymes|Models, Chemical|Models, Molecular|Protein Binding|Protein Interaction Mapping', 'Journal Article', '10.1093/bioinformatics/btm580', '18037612', 'Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. There is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a genome scale. Current machine-learning techniques use as input either protein sequences and structures or chemical information. We propose here a method to infer protein-chemical interactions using heterogeneous input consisting of both protein sequence and chemical information.'),
(73835, 2008, 'bio', 'Automatic synchronization and distribution of biological databases and software over low-bandwidth networks among developing countries', 'Sangket, Unitsa|Phongdara, Amornrat|Chotigeat, Wilaiwan|Nathan, Darran|Kim, Woo-Yeon|Bhak, Jong|Ngamphiw, Chumpol|Tongsima, Sissades|Khan, Asif M|Lin, Honghuang|Tan, Tin Wee', 'Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com|Center for Genomics and Bioinformatics Research, Prince of Songkla University, Thailand. usangket@yahoo.com', 'Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand|Thailand', 8, 'Computer Communication Networks|Data Compression|Database Management Systems|Databases, Factual|Developing Countries|Information Dissemination|Information Storage and Retrieval', 'Journal Article', '10.1093/bioinformatics/btm570', '18037613', 'Bioinformatics involves the collection, organization and analysis of large amounts of biological data, using networks of computers and databases. Developing countries in the Asia-Pacific region are just moving into this new field of information-based biotechnology. However, the computational infrastructure and network bandwidths available in these countries are still at a basic level compared to that in developed countries. In this study, we assessed the utility of a BitTorrent-based Peer-to-Peer (btP2P) file distribution model for automatic synchronization and distribution of large amounts of biological data among developing countries. The initial country-level nodes in the Asia-Pacific region comprised Thailand, Korea and Singapore. The results showed a significant improvement in download performance using btP2P--three times faster overall download performance than conventional File Transfer Protocol (FTP). This study demonstrated the reliability of btP2P in the dissemination of continuously growing multi-gigabyte biological databases across the three Asia-Pacific countries. The download performance for btP2P can be further improved by including more nodes from other countries into the network. This suggests that the btP2P technology is appropriate for automatic synchronization and distribution of biological databases and software over low-bandwidth networks among developing countries in the Asia-Pacific region.'),
(73836, 2008, 'bio', 'Probabilistic path ranking based on adjacent pairwise coexpression for metabolic transcripts analysis', 'Takigawa, Ichigaku|Mamitsuka, Hiroshi', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. takigawa@kuicr.kyoto-u.ac.jp|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan. takigawa@kuicr.kyoto-u.ac.jp', 'Japan|Japan', 14, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression|Gene Expression Profiling|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm575', '18037682', 'Pathway knowledge in public databases enables us to examine how individual metabolites are connected via chemical reactions and what genes are implicated in those processes. For two given (sets of) compounds, the number of possible paths between them in a metabolic network can be intractably large. It would be informative to rank these paths in order to differentiate between them.'),
(73837, 2008, 'bio', 'Identification of phylogenetically conserved microRNA cis-regulatory elements across 12 Drosophila species', 'Wang, Xiaowo|Gu, Jin|Zhang, Michael Q|Li, Yanda', 'MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.|MOE Key Laboratory of Bioinformatics and Bioinformatics Division, TNLIST/Department of Automation, Tsinghua University, Beijing 100084, China.', 'China|China|China|China', 15, 'Animals|Base Sequence|Conserved Sequence|Drosophila|Evolution, Molecular|MicroRNAs|Molecular Sequence Data|Phylogeny|RNA, Small Nucleolar|Regulatory Elements, Transcriptional|Sequence Alignment|Sequence Analysis, RNA|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btm572', '18037683', 'MicroRNAs are a class of endogenous small RNAs that play regulatory roles. Intergenic miRNAs are believed to be transcribed independently, but the transcriptional control of these crucial regulators is still poorly understood.'),
(73838, 2008, 'bio', 'RReportGenerator: automatic reports from routine statistical analysis using R', 'Raffelsberger, Wolfgang|Krause, Yannick|Moulinier, Luc|Kieffer, David|Morand, Anne-Laure|Brino, Laurent|Poch, Olivier', 'Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr|Laboratoire de Bioinformatique et Génomique Intégratives, IGBMC, UMR 7104, 67404 Illkirch, France. wolfgang.raffelsberger@igbmc.u-strasbg.fr', 'France|France|France|France|France|France|France', 13, 'Algorithms|Computer Graphics|Data Interpretation, Statistical|Documentation|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm556', '18037684', 'With the establishment of high-throughput (HT) screening methods there is an increasing need for automatic analysis methods. Here we present RReportGenerator, a user-friendly portal for automatic routine analysis using the statistical platform R and Bioconductor. RReportGenerator is designed to analyze data using predefined analysis scenarios via a graphical user interface (GUI). A report in pdf format combining text, figures and tables is automatically generated and results may be exported. To demonstrate suitable analysis tasks we provide direct web access to a collection of analysis scenarios for summarizing data from transfected cell arrays (TCA), segmentation of CGH data, and microarray quality control and normalization.'),
(73839, 2008, 'bio', 'Identification of differentially expressed gene categories in microarray studies using nonparametric multivariate analysis', 'Nettleton, Dan|Recknor, Justin|Reecy, James M', 'Department of Statistics, Lowa State University, Ames, Lowa 50011-1210, USA. dnett@iastate.edu|Department of Statistics, Lowa State University, Ames, Lowa 50011-1210, USA. dnett@iastate.edu|Department of Statistics, Lowa State University, Ames, Lowa 50011-1210, USA. dnett@iastate.edu', 'United States|United States|United States', 44, 'Algorithms|Data Interpretation, Statistical|Gene Expression Profiling|Multivariate Analysis|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btm583', '18042553', 'The field of microarray data analysis is shifting emphasis from methods for identifying differentially expressed genes to methods for identifying differentially expressed gene categories. The latter approaches utilize a priori information about genes to group genes into categories and enhance the interpretation of experiments aimed at identifying expression differences across treatments. While almost all of the existing approaches for identifying differentially expressed gene categories are practically useful, they suffer from a variety of drawbacks. Perhaps most notably, many popular tools are based exclusively on gene-specific statistics that cannot detect many types of multivariate expression change.'),
(73840, 2008, 'bio', 'An assessment of the uses of homologous interactions', 'Saeed, Ramazan|Deane, Charlotte', 'Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. saeed@stats.ox.ac.uk|Department of Statistics, University of Oxford, 1 South Parks Road, Oxford OX1 3TG, UK. saeed@stats.ox.ac.uk', 'United Kingdom|United Kingdom', 20, 'Protein Binding|Proteins|Reproducibility of Results|Saccharomyces cerevisiae', 'Journal Article', '10.1093/bioinformatics/btm576', '18042554', 'Protein-protein interactions have proved to be a valuable starting point for understanding the inner workings of the cell. Computational methodologies have been built which both predict interactions and use interaction datasets in order to predict other protein features. Such methods require gold standard positive (GSP) and negative (GSN) interaction sets. Here we examine and demonstrate the usefulness of homologous interactions in predicting good quality positive and negative interaction datasets.'),
(73841, 2008, 'bio', 'Choosing BLAST options for better detection of orthologs as reciprocal best hits', 'Moreno-Hagelsieb, Gabriel|Latimer, Kristen', 'Department of Biology, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON, Canada, N2L 3C5. gmoreno@wlu.ca|Department of Biology, Wilfrid Laurier University, 75 University Avenue West, Waterloo, ON, Canada, N2L 3C5. gmoreno@wlu.ca', 'Canada|Canada', 277, 'Base Sequence|Chromosome Mapping|DNA, Bacterial|Database Management Systems|Databases, Genetic|Escherichia coli|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Journal Article', '10.1093/bioinformatics/btm585', '18042555', 'The analyses of the increasing number of genome sequences requires shortcuts for the detection of orthologs, such as Reciprocal Best Hits (RBH), where orthologs are assumed if two genes each in a different genome find each other as the best hit in the other genome. Two BLAST options seem to affect alignment scores the most, and thus the choice of a best hit: the filtering of low information sequence segments and the algorithm used to produce the final alignment. Thus, we decided to test whether such options would help better detect orthologs.'),
(73842, 2007, 'bio', 'Reconstructing protein networks of epithelial differentiation from histological sections', 'Grabe, Niels|Pommerencke, Thora|Steinberg, Thorsten|Dickhaus, Hartmut|Tomakidi, Pascal', 'Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de|Hamamatsu Tissue Imaging and Analysis (TIGA) Center, BIOQUANT, University Heidelberg, Heidelberg, Germany. niels.grabe@med.uni-heidelberg.de', 'Germany|Germany|Germany|Germany|Germany', 11, 'Cells, Cultured|Gene Expression Profiling|Humans|Keratinocytes|Protein Interaction Mapping|Proteome|Signal Transduction|Tissue Array Analysis|Tissue Distribution', 'Journal Article', '10.1093/bioinformatics/btm504', '18042556', 'For systems biology of complex stratified epithelia like human epidermis, it will be of particular importance to reconstruct the spatiotemporal gene and protein networks regulating keratinocyte differentiation and homeostasis.'),
(73843, 2007, 'bio', 'Estimating parameters and hidden variables in non-linear state-space models based on ODEs for biological networks inference', 'Quach, Minh|Brunel, Nicolas|dAlché-Buc, Florence', 'IBISC FRE CNRS 2873, University of Evry and Genopole 523, place des terrasses 91025 Evry, France.|IBISC FRE CNRS 2873, University of Evry and Genopole 523, place des terrasses 91025 Evry, France.|IBISC FRE CNRS 2873, University of Evry and Genopole 523, place des terrasses 91025 Evry, France.', 'France|France|France', 100, 'Algorithms|Computer Simulation|Models, Biological|Models, Statistical|Nonlinear Dynamics|Proteome|Signal Transduction|Stochastic Processes|Systems Biology', 'Journal Article', '10.1093/bioinformatics/btm510', '18042557', 'Statistical inference of biological networks such as gene regulatory networks, signaling pathways and metabolic networks can contribute to build a picture of complex interactions that take place in the cell. However, biological systems considered as dynamical, non-linear and generally partially observed processes may be difficult to estimate even if the structure of interactions is given.'),
(73844, 2007, 'bio', 'Modeling the adaptive immune system: predictions and simulations', 'Lundegaard, Claus|Lund, Ole|Kesmir, Can|Brunak, Søren|Nielsen, Morten', 'Center for biological sequence analysis, CBS, Kemitorvet 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk|Center for biological sequence analysis, CBS, Kemitorvet 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk|Center for biological sequence analysis, CBS, Kemitorvet 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk|Center for biological sequence analysis, CBS, Kemitorvet 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk|Center for biological sequence analysis, CBS, Kemitorvet 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. lunde@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark', 91, 'Adaptation, Physiological|Animals|Computer Simulation|Epitope Mapping|Humans|Immunity, Innate|Immunologic Factors|Models, Immunological', 'Journal Article', '10.1093/bioinformatics/btm471', '18045832', 'Immunological bioinformatics methods are applicable to a broad range of scientific areas. The specifics of how and where they might be implemented have recently been reviewed in the literature. However, the background and concerns for selecting between the different available methods have so far not been adequately covered.'),
(73845, 2008, 'bio', 'Prediction of both conserved and nonconserved microRNA targets in animals', 'Wang, Xiaowei|El Naqa, Issam M', 'Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA. xwang@radonc.wustl.edu|Department of Radiation Oncology, Washington University School of Medicine, St. Louis, MO 63110, USA. xwang@radonc.wustl.edu', 'United States|United States', 0, 'Animals|Artificial Intelligence|Conserved Sequence|Evolution, Molecular|Gene Targeting|Humans|MicroRNAs|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, RNA|Species Specificity', 'Journal Article', '10.1093/bioinformatics/btm595', '18048393', 'MicroRNAs (miRNAs) are involved in many diverse biological processes and they may potentially regulate the functions of thousands of genes. However, one major issue in miRNA studies is the lack of bioinformatics programs to accurately predict miRNA targets. Animal miRNAs have limited sequence complementarity to their gene targets, which makes it challenging to build target prediction models with high specificity.'),
(73846, 2008, 'bio', 'TOM: enhancement and extension of a tool suite for in silico approaches to multigenic hereditary disorders', 'Masotti, Daniele|Nardini, Christine|Rossi, Simona|Bonora, Elena|Romeo, Giovanni|Volinia, Stefano|Benini, Luca', 'Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it|Dipartimento di Elettronica, Informatica e Sistemistica (DEIS), University of Bologna, Viale Risorgimento 2, 40136 Bologna, Italy. daniele.masotti@unibo.it', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 9, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Genetic Diseases, Inborn|Genetic Predisposition to Disease|Humans|Linkage Disequilibrium|Software', 'Journal Article', '10.1093/bioinformatics/btm588', '18048394', 'The study of complex hereditary diseases is a very challenging area of research. The expanding set of in silico approaches offers a flourishing ground for the acceleration of meaningful findings in this area by exploitation of rich and diverse sources of omic data. These approaches are cheap, flexible, extensible, often complementary and can continuously integrate new information and tests to improve the selection of genes responsible for hereditary diseases. Following this principle, we improved and extended our web-service TOM for the identification of candidate genes in the study of complex hereditary diseases.'),
(73847, 2008, 'bio', 'MutaGeneSys: estimating individual disease susceptibility based on genome-wide SNP array data', 'Stoyanovich, Julia|Peer, Itsik', 'Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, New York, NY 10025, USA. jds1@cs.columbia.edu|Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, New York, NY 10025, USA. jds1@cs.columbia.edu', 'United States|United States', 6, 'Algorithms|Chromosome Mapping|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genetic Markers|Genetic Predisposition to Disease|Humans|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm587', '18048395', 'We present MutaGeneSys: a system that uses genome-wide genotype data to estimate disease susceptibility. Our system integrates three data sources: the International HapMap project, whole-genome marker correlation data and the Online Mendelian Inheritance in Man (OMIM) database. It accepts SNP data of individuals as query input and delivers disease susceptibility hypotheses even if the original set of typed SNPs is incomplete. Our system is scalable and flexible: it produces population, technology and confidence-specific predictions in interactive time.'),
(73848, 2007, 'bio', 'An efficient strategy for extensive integration of diverse biological data for protein function prediction', 'Chua, Hon Nian|Sung, Wing-Kin|Wong, Limsoon', 'Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore. hnchua@i2r.a-star.edu.sg|Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore. hnchua@i2r.a-star.edu.sg|Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore. hnchua@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Computational Biology|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Biological|Proteins|Structure-Activity Relationship|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btm520', '18048396', 'With the increasing availability of diverse biological information, protein function prediction approaches have converged towards integration of heterogeneous data. Many adapted existing techniques, such as machine-learning and probabilistic methods, which have proven successful on specific data types. However, the impact of these approaches is hindered by a couple of factors. First, there is little comparison between existing approaches. This is in part due to a divergence in the focus adopted by different works, which makes comparison difficult or even fuzzy. Second, there seems to be over-emphasis on the use of computationally demanding machine-learning methods, which runs counter to the surge in biological data. Analogous to the success of BLAST for sequence homology search, we believe that the ability to tap escalating quantity, quality and diversity of biological data is crucial to the success of automated function prediction as a useful instrument for the advancement of proteomic research. We address these problems by: (1) providing useful comparison between some prominent methods, (2) proposing Integrated Weighted Averaging (IWA)--a scalable, efficient and flexible function prediction framework that integrates diverse information using simple weighting strategies and a local prediction method. The simplicity of the approach makes it possible to make predictions based on on-the-fly information fusion.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73849, 2007, 'bio', 'Möbius: an integrated discrete-event modeling environment', 'Peccoud, Jean|Courtney, Tod|Sanders, William H', 'Virginia Bioinformatics Institute, Washington Street, MC0477, Blacksburg, VA 24061, USA. peccoud@vt.edu|Virginia Bioinformatics Institute, Washington Street, MC0477, Blacksburg, VA 24061, USA. peccoud@vt.edu|Virginia Bioinformatics Institute, Washington Street, MC0477, Blacksburg, VA 24061, USA. peccoud@vt.edu', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Models, Biological|Models, Statistical|Software|Stochastic Processes|Time Factors', 'Journal Article', '10.1093/bioinformatics/btm517', '18048397', 'Möbius has found numerous applications in computational biology to build and solve stochastic models of biological processes. It provides the user with a modeling workflow and several sophisticated features that are not available in the simulation tools commonly used by computational biologists.'),
(73850, 2008, 'bio', 'Monte Carlo feature selection for supervised classification', 'Draminski, Michal|Rada-Iglesias, Alvaro|Enroth, Stefan|Wadelius, Claes|Koronacki, Jacek|Komorowski, Jan', 'Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.|Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.|Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.|Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.|Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.|Institute of Computer Science, Polish Academy of Science, Ordona 21, PL-01-237 Warsaw, Poland.', 'Poland|Poland|Poland|Poland|Poland|Poland', 0, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Gene Expression Profiling|Humans|Monte Carlo Method|Neoplasm Proteins|Neoplasms|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm486', '18048398', 'Pre-selection of informative features for supervised classification is a crucial, albeit delicate, task. It is desirable that feature selection provides the features that contribute most to the classification task per se and which should therefore be used by any classifier later used to produce classification rules. In this article, a conceptually simple but computer-intensive approach to this task is proposed. The reliability of the approach rests on multiple construction of a tree classifier for many training sets randomly chosen from the original sample set, where samples in each training set consist of only a fraction of all of the observed features.'),
(73851, 2008, 'bio', 'Putative promoter regions of miRNA genes involved in evolutionarily conserved regulatory systems among vertebrates', 'Fujita, Shuji|Iba, Hideo', 'Division of Host-Parasite Interaction, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku Tokyo, 108-8639, Japan.|Division of Host-Parasite Interaction, Department of Microbiology and Immunology, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku Tokyo, 108-8639, Japan.', 'Japan|Japan', 0, 'Animals|Biological Evolution|Chickens|Conserved Sequence|Evolution, Molecular|Humans|MicroRNAs|Promoter Regions, Genetic|Regulatory Sequences, Ribonucleic Acid|Sequence Analysis, RNA|Species Specificity|Vertebrates|Zebrafish', 'Journal Article', '10.1093/bioinformatics/btm589', '18055479', 'Just as transcription factors, miRNA genes modulate global patterns of gene expression during differentiation, metabolic activation, stimulus response and also carcinogenesis. However, little is currently known how the miRNA gene expression itself is regulated owing to lack of basic information of their gene structure. Global prediction of promoter regions of miRNA genes would allow us to explore the mechanisms underlying gene-regulatory mechanisms involving these miRNAs.'),
(73852, 2008, 'bio', 'Déjà vu--a study of duplicate citations in Medline', 'Errami, Mounir|Hicks, Justin M|Fisher, Wayne|Trusty, David|Wren, Jonathan D|Long, Tara C|Garner, Harold R', 'UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.|UT Southwestern Medical Center, 5323 Harry Hines Blvd., Dallas TX 75390-9185, USA.', 'United States|United States|United States|United States|United States|United States|United States', 69, 'Bibliometrics|MEDLINE|Medical Subject Headings|Natural Language Processing|Periodicals as Topic|Plagiarism|Semantics|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btm574', '18056062', 'Duplicate publication impacts the quality of the scientific corpus, has been difficult to detect, and studies this far have been limited in scope and size. Using text similarity searches, we were able to identify signatures of duplicate citations among a body of abstracts.'),
(73853, 2008, 'bio', 'Model-based deconvolution of genome-wide DNA binding', 'Reiss, David J|Facciotti, Marc T|Baliga, Nitin S', 'Institute for Systems Biology, 1441 N. 34th St. Seattle, WA 98103-8904, USA. dreiss@systemsbiology.org|Institute for Systems Biology, 1441 N. 34th St. Seattle, WA 98103-8904, USA. dreiss@systemsbiology.org|Institute for Systems Biology, 1441 N. 34th St. Seattle, WA 98103-8904, USA. dreiss@systemsbiology.org', 'United States|United States|United States', 0, 'Algorithms|Chromatin Immunoprecipitation|Chromosome Mapping|Computer Simulation|DNA|DNA-Binding Proteins|Models, Genetic|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btm592', '18056063', 'Chromatin immunoprecipitation followed by hybridization to a genomic tiling microarray (ChIP-chip) is a routinely used protocol for localizing the genomic targets of DNA-binding proteins. The resolution to which binding sites in this assay can be identified is commonly considered to be limited by two factors: (1) the resolution at which the genomic targets are tiled in the microarray and (2) the large and variable lengths of the immunoprecipitated DNA fragments.'),
(73854, 2008, 'bio', 'BAGET: a web server for the effortless retrieval of prokaryotic gene context and sequence', 'Oberto, Jacques', 'Biologie Moléculaire du Gène chez les Extrêmophiles, Université Paris-Sud, Institut de Génétique et Microbiologie, CNRS UMR8621, 91405 Orsay Cedex, France. jacques.oberto@igmors.u-psud.fr', 'France', 14, 'Archaea|Bacteria|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Proteome|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm600', '18056064', 'BAGET (Bacterial and Archaeal Gene Exploration Tool) is a web service designed to facilitate extraction, by molecular geneticists and phylogeneticists, of specific gene and protein sequences from completely determined prokaryotic genomes. Upon selection of a particular prokaryotic organism and gene, two levels of visual gene context information are provided on a single dynamic page: (i) a graphical representation of a user defined portion of the chromosome centered on the gene of interest and (ii) the DNA sequence of the query gene, of the immediate neighboring genes and the intergenic regions each identified by a consistent color code. The aminoacid sequence is provided for protein-coding query genes. Query results can be exported as a rich text format (RTF) word processor file for printing, archival or further analysis.'),
(73855, 2008, 'bio', 'COMPARE, a multi-organism system for cross-species data comparison and transfer of information', 'Salgado, David|Gimenez, Gregory|Coulier, François|Marcelle, Christophe', 'Developmental Biology Institute of Marseille Luminy (IBDML), CNRS UMR 6216, Université de la Méditerranée, Campus de Luminy, case 907. 13288 Marseille, France.|Developmental Biology Institute of Marseille Luminy (IBDML), CNRS UMR 6216, Université de la Méditerranée, Campus de Luminy, case 907. 13288 Marseille, France.|Developmental Biology Institute of Marseille Luminy (IBDML), CNRS UMR 6216, Université de la Méditerranée, Campus de Luminy, case 907. 13288 Marseille, France.|Developmental Biology Institute of Marseille Luminy (IBDML), CNRS UMR 6216, Université de la Méditerranée, Campus de Luminy, case 907. 13288 Marseille, France.', 'France|France|France|France', 11, 'Animals|Biological Evolution|Chromosome Mapping|Database Management Systems|Databases, Genetic|Documentation|Evolution, Molecular|Humans|Information Storage and Retrieval|Species Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm599', '18056065', 'COMPARE is a multi-organism web-based resource system designed to easily retrieve, correlate and interpret data across species. The COMPARE interface provides access to a wide array of information including genomic structure, expression data, annotations, pathways and literature links for human and three widely studied animal models (zebrafish, Drosophila and mouse). A consensus ortholog-finding pipeline combining several ortholog prediction methods allows accurate comparisons of data across species and has been utilized to transfer information from well studied organisms to more poorly annotated ones.'),
(73856, 2008, 'bio', 'OBO Explorer: an editor for Open Biomedical Ontologies in OWL', 'Aitken, Stuart|Chen, Yin|Bard, Jonathan', 'School of Informatics, University of Edinburgh, 11 Crichton Street, Edinburgh, UK. stuart@aiai.ed.ac.uk|School of Informatics, University of Edinburgh, 11 Crichton Street, Edinburgh, UK. stuart@aiai.ed.ac.uk|School of Informatics, University of Edinburgh, 11 Crichton Street, Edinburgh, UK. stuart@aiai.ed.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Database Management Systems|Databases, Genetic|Documentation|Information Storage and Retrieval|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm593', '18056066', 'To clarify the semantics, and take advantage of tools and algorithms developed for the Semantic Web, a mapping from the Open Biomedical Ontologies (OBO) format to the Web Ontology Language (OWL) has been established. We present an ontology editor that allows end users to work directly with this OWL representation of OBO format ontologies.'),
(73857, 2008, 'bio', 'An integrated system for studying residue coevolution in proteins', 'Yip, Kevin Y|Patel, Prianka|Kim, Philip M|Engelman, Donald M|McDermott, Drew|Gerstein, Mark', 'Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.|Department of Computer Science, Yale University, 51 Prospect Street, New Haven, CT 06511, USA.', 'United States|United States|United States|United States|United States|United States', 57, 'Algorithms|Amino Acid Sequence|Computer Graphics|Evolution, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Analysis, Protein|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm584', '18056067', 'Residue coevolution has recently emerged as an important concept, especially in the context of protein structures. While a multitude of different functions for quantifying it have been proposed, not much is known about their relative strengths and weaknesses. Also, subtle algorithmic details have discouraged implementing and comparing them. We addressed this issue by developing an integrated online system that enables comparative analyses with a comprehensive set of commonly used scoring functions, including Statistical Coupling Analysis (SCA), Explicit Likelihood of Subset Variation (ELSC), mutual information and correlation-based methods. A set of data preprocessing options are provided for improving the sensitivity and specificity of coevolution signal detection, including sequence weighting, residue grouping and the filtering of sequences, sites and site pairs. A total of more than 100 scoring variations are available. The system also provides facilities for studying the relationship between coevolution scores and inter-residue distances from a crystal structure if provided, which may help in understanding protein structures.'),
(73858, 2008, 'bio', 'KEGGanim: pathway animations for high-throughput data', 'Adler, Priit|Reimand, Jüri|Jänes, Jürgen|Kolde, Raivo|Peterson, Hedi|Vilo, Jaak', 'Estonian Biocentre, Riia 23b, Estonia.|Estonian Biocentre, Riia 23b, Estonia.|Estonian Biocentre, Riia 23b, Estonia.|Estonian Biocentre, Riia 23b, Estonia.|Estonian Biocentre, Riia 23b, Estonia.|Estonian Biocentre, Riia 23b, Estonia.', 'Estonia|Estonia|Estonia|Estonia|Estonia|Estonia', 24, 'Animals|Computational Biology|Computer Graphics|Gene Expression Regulation|Humans|Metabolic Networks and Pathways|Software|Ventricular Remodeling', 'Journal Article', '10.1093/bioinformatics/btm581', '18056068', 'Gene expression analysis with microarrays has become one of the most widely used high-throughput methods for gathering genome-wide functional data. Emerging -omics fields such as proteomics and interactomics introduce new information sources. With the rise of systems biology, researchers need to concentrate on entire complex pathways that guide individual genes and related processes. Bioinformatics methods are needed to link the existing knowledge about pathways with the growing amounts of experimental data.'),
(73859, 2008, 'bio', 'Automated manipulation of systems biology models using libSBML within Taverna workflows', 'Li, Peter|Oinn, Tom|Soiland, Stian|Kell, Douglas B', 'School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, UK. peter.li@manchester.ac.uk|School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, UK. peter.li@manchester.ac.uk|School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, UK. peter.li@manchester.ac.uk|School of Chemistry and Manchester Centre for Integrative Systems Biology, Manchester Interdisciplinary Biocentre, University of Manchester, UK. peter.li@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 20, 'Algorithms|Computer Simulation|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Models, Biological|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm578', '18056069', 'Many data manipulation processes involve the use of programming libraries. These processes may beneficially be automated due to their repeated use. A convenient type of automation is in the form of workflows that also allow such processes to be shared amongst the community. The Taverna workflow system has been extended to enable it to use and invoke Java classes and methods as tasks within Taverna workflows. These classes and methods are selected for use during workflow construction by a Java Doclet application called the API Consumer. This selection is stored as an XML file which enables Taverna to present the subset of the API for use in the composition of workflows. The ability of Taverna to invoke Java classes and methods is demonstrated by a workflow in which we use libSBML to map gene expression data onto a metabolic pathway represented as a SBML model.'),
(73860, 2008, 'bio', 'Rfold: an exact algorithm for computing local base pairing probabilities', 'Kiryu, Hisanori|Kin, Taishin|Asai, Kiyoshi', 'Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-42 Aomi, Koto-ku, Tokyo, Japan. kiryu-h@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-42 Aomi, Koto-ku, Tokyo, Japan. kiryu-h@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-42 Aomi, Koto-ku, Tokyo, Japan. kiryu-h@aist.go.jp', 'Japan|Japan|Japan', 32, 'Algorithms|Base Pairing|Base Sequence|Computer Simulation|Models, Chemical|Models, Genetic|Models, Statistical|Molecular Sequence Data|RNA, Untranslated|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm591', '18056736', 'Base pairing probability matrices have been frequently used for the analyses of structural RNA sequences. Recently, there has been a growing need for computing these probabilities for long DNA sequences by constraining the maximal span of base pairs to a limited value. However, none of the existing programs can exactly compute the base pairing probabilities associated with the energy model of secondary structures under such a constraint.'),
(73861, 2008, 'bio', 'Bayesian ranking of biochemical system models', 'Vyshemirsky, Vladislav|Girolami, Mark A', 'Department of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK. vvv@dcs.gla.ac.uk|Department of Computing Science, University of Glasgow, Glasgow, G12 8QQ, UK. vvv@dcs.gla.ac.uk', 'United Kingdom|United Kingdom', 131, 'Algorithms|Artificial Intelligence|Bayes Theorem|Biochemistry|Computer Simulation|Models, Biological|Pattern Recognition, Automated|Proteome|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/btm607', '18057018', 'There often are many alternative models of a biochemical system. Distinguishing models and finding the most suitable ones is an important challenge in Systems Biology, as such model ranking, by experimental evidence, will help to judge the support of the working hypotheses forming each model. Bayes factors are employed as a measure of evidential preference for one model over another. Marginal likelihood is a key component of Bayes factors, however computing the marginal likelihood is a difficult problem, as it involves integration of nonlinear functions in multidimensional space. There are a number of methods available to compute the marginal likelihood approximately. A detailed investigation of such methods is required to find ones that perform appropriately for biochemical modelling.'),
(73862, 2008, 'bio', 'Mutual information without the influence of phylogeny or entropy dramatically improves residue contact prediction', 'Dunn, S D|Wahl, L M|Gloor, G B', 'Department of Biochemistry, University of Western Ontario, London, Ontario, Canada, N6A 5C1.|Department of Biochemistry, University of Western Ontario, London, Ontario, Canada, N6A 5C1.|Department of Biochemistry, University of Western Ontario, London, Ontario, Canada, N6A 5C1.', 'Canada|Canada|Canada', 252, 'Algorithms|Amino Acid Sequence|Base Sequence|Binding Sites|Computational Biology|Entropy|Evolution, Molecular|Molecular Sequence Data|Phylogeny|Protein Binding|Proteins|Sequence Alignment|Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/btm604', '18057019', 'Compensating alterations during the evolution of protein families give rise to coevolving positions that contain important structural and functional information. However, a high background composed of random noise and phylogenetic components interferes with the identification of coevolving positions.'),
(73863, 2008, 'bio', 'Association studies for untyped markers with TUNA', 'Wen, Xiaoquan|Nicolae, Dan L', 'Department of Statistics, Chicago, IL 60637, USA.|Department of Statistics, Chicago, IL 60637, USA.', 'United States|United States', 12, 'Algorithms|Alleles|Chromosome Mapping|Databases, Genetic|Genetic Markers|Linkage Disequilibrium|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/btm603', '18057020', 'The software package TUNA (Testing UNtyped Alleles) implements a fast and efficient algorithm for testing association of genotyped and ungenotyped variants in genome-wide case-control studies. TUNA uses Linkage Disequilibrium (LD) information from existing comprehensive variation datasets such as HapMap to construct databases of frequency predictors using linear combination of haplotype frequencies of genotyped SNPs. The predictors are used to estimate untyped allele frequencies, and to perform association tests. The methods incorporated in TUNA achieve great accuracy in estimation, and the software is computationally efficient and does not demand a lot of system memory and CPU resources.'),
(73864, 2008, 'bio', 'Assembly reconciliation', 'Zimin, Aleksey V|Smith, Douglas R|Sutton, Granger|Yorke, James A', 'IPST, University of Maryland, College Park, Agencourt Bioscience Inc., Beverly, MA. alekseyz@ipst.umd.edu|IPST, University of Maryland, College Park, Agencourt Bioscience Inc., Beverly, MA. alekseyz@ipst.umd.edu|IPST, University of Maryland, College Park, Agencourt Bioscience Inc., Beverly, MA. alekseyz@ipst.umd.edu|IPST, University of Maryland, College Park, Agencourt Bioscience Inc., Beverly, MA. alekseyz@ipst.umd.edu', '-|-|-|-', 45, 'Algorithms|Base Sequence|Chromosome Mapping|Contig Mapping|Genome|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm542', '18057021', 'Many genomes are sequenced by a collaboration of several centers, and then each center produces an assembly using their own assembly software. The collaborators then pick the draft assembly that they judge to be the best and the information contained in the other assemblies is usually not used.'),
(73865, 2008, 'bio', 'TFBS identification based on genetic algorithm with combined representations and adaptive post-processing', 'Chan, Tak-Ming|Leung, Kwong-Sak|Lee, Kin-Hong', 'Department of Computer Science & Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong. tmchan@cse.cuhk.edu.hk|Department of Computer Science & Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong. tmchan@cse.cuhk.edu.hk|Department of Computer Science & Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong. tmchan@cse.cuhk.edu.hk', 'Hong Kong|Hong Kong|Hong Kong', 53, 'Algorithms|Base Sequence|Binding Sites|Molecular Sequence Data|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm606', '18065426', 'Identification of transcription factor binding sites (TFBSs) plays an important role in deciphering the mechanisms of gene regulation. Recently, GAME, a Genetic Algorithm (GA)-based approach with iterative post-processing, has shown superior performance in TFBS identification. However, the basic GA in GAME is not elaborately designed, and may be trapped in local optima in real problems. The feature operators are only applied in the post-processing, but the final performance heavily depends on the GA output. Hence, both effectiveness and efficiency of the overall algorithm can be improved by introducing more advanced representations and novel operators in the GA, as well as designing the post-processing in an adaptive way.'),
(73866, 2008, 'bio', 'TimeClust: a clustering tool for gene expression time series', 'Magni, Paolo|Ferrazzi, Fulvia|Sacchi, Lucia|Bellazzi, Riccardo', 'Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, Pavia, Italy. paolo.magni@unipv.it|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, Pavia, Italy. paolo.magni@unipv.it|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, Pavia, Italy. paolo.magni@unipv.it|Dipartimento di Informatica e Sistemistica, Università degli Studi di Pavia, Via Ferrata 1, Pavia, Italy. paolo.magni@unipv.it', 'Italy|Italy|Italy|Italy', 36, 'Algorithms|Artificial Intelligence|Cluster Analysis|Gene Expression Profiling|Multigene Family|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software|Time Factors', 'Journal Article', '10.1093/bioinformatics/btm605', '18065427', 'TimeClust is a user-friendly software package to cluster genes according to their temporal expression profiles. It can be conveniently used to analyze data obtained from DNA microarray time-course experiments. It implements two original algorithms specifically designed for clustering short time series together with hierarchical clustering and self-organizing maps.'),
(73867, 2008, 'bio', 'ConoServer, a database for conopeptide sequences and structures', 'Kaas, Quentin|Westermann, Jan-C|Halai, Reena|Wang, Conan K L|Craik, David J', 'Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia.|Institute for Molecular Bioscience, University of Queensland, Brisbane, Queensland, 4072, Australia.', 'Australia|Australia|Australia|Australia|Australia', 145, 'Amino Acid Sequence|Animals|Conotoxins|Conus Snail|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Protein Conformation|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm596', '18065428', 'ConoServer is a new database dedicated to conopeptides, a large family of peptides found in the venom of marine snails of the genus Conus. These peptides have an exceptional diversity of sequences and chemical modifications and their ability to block ion channels makes them important as drug leads and tools for physiological studies. ConoServer uses standardized names and a genetic and structural classification scheme to present data retrieved from SwissProt, GenBank, the Protein DataBank and the literature. The ConoServer web site incorporates specialized features like the graphic display of post-translational modifications that are extensively present in conopeptides. Currently, ConoServer manages 1214 nucleic sequences (from 54 Conus species), 2258 proteic sequences (from 66 Conus species) and 99 3D structures.'),
(73868, 2007, 'bio', 'Co-evolving residues in membrane proteins', 'Fuchs, Angelika|Martin-Galiano, Antonio J|Kalman, Matan|Fleishman, Sarel|Ben-Tal, Nir|Frishman, Dmitrij', 'Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.|Department of Genome Oriented Bioinformatics, Technische Universität München, Wissenschaftszentrum Weihenstephan, 85350 Freising, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Amino Acid Substitution|Amino Acids|DNA Mutational Analysis|Evolution, Molecular|Membrane Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology', 'Journal Article', '10.1093/bioinformatics/btm515', '18065429', 'The analysis of co-evolving residues has been exhaustively evaluated for the prediction of intramolecular amino acid contacts in soluble proteins. Although a variety of different methods for the detection of these co-evolving residues have been developed, the fraction of correctly predicted contacts remained insufficient for their reliable application in the construction of structural models. Membrane proteins, which constitute between one-fourth and one-third of all proteins in an organism, were only considered in few individual case studies.'),
(73869, 2008, 'bio', 'Incorporating gene networks into statistical tests for genomic data via a spatially correlated mixture model', 'Wei, Peng|Pan, Wei', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA. weip@biostat.umn.edu|Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building (MMC 303), Minneapolis, MN 55455-0378, USA. weip@biostat.umn.edu', 'United States|United States', 49, 'Algorithms|Chromatin Immunoprecipitation|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Proteome|Signal Transduction|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btm612', '18083717', 'It is a common task in genomic studies to identify a subset of the genes satisfying certain conditions, such as differentially expressed genes or regulatory target genes of a transcription factor (TF). This can be formulated as a statistical hypothesis testing problem. Most existing approaches treat the genes as having an identical and independent distribution a priori, testing each gene independently or testing some subsets of the genes one by one. On the other hand, it is known that the genes work coordinately as dictated by gene networks. Treating genes equally and independently ignores the important information contained in gene networks, leading to inefficient analysis and reduced power.'),
(73870, 2008, 'bio', 'Efficient peptide-MHC-I binding prediction for alleles with few known binders', 'Jacob, Laurent|Vert, Jean-Philippe', 'Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint Honoré, 77305 Fontainebleau Cedex, France. laurent.jacob@ensmp.fr|Centre for Computational Biology, Ecole des Mines de Paris, 35 rue Saint Honoré, 77305 Fontainebleau Cedex, France. laurent.jacob@ensmp.fr', 'France|France', 82, 'Alleles|Antigen-Antibody Complex|Binding Sites|Computer Simulation|H-2 Antigens|Models, Chemical|Models, Immunological|Peptides|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btm611', '18083718', 'In silico methods for the prediction of antigenic peptides binding to MHC class I molecules play an increasingly important role in the identification of T-cell epitopes. Statistical and machine learning methods in particular are widely used to score candidate binders based on their similarity with known binders and non-binders. The genes coding for the MHC molecules, however, are highly polymorphic, and statistical methods have difficulties building models for alleles with few known binders. In this context, recent work has demonstrated the utility of leveraging information across alleles to improve the performance of the prediction.'),
(73871, 2008, 'bio', 'A new algorithm for cluster analysis of genomic methylation: the Helicobacter pylori case', 'Vale, F F|Encarnação, P|Vítor, J M B', 'Engineering Faculty, Portuguese Catholic University, Estrada Octávio Pato, 2635-631 Rio de Mouro, Portugal. filipavale@fe.ucp.pt|Engineering Faculty, Portuguese Catholic University, Estrada Octávio Pato, 2635-631 Rio de Mouro, Portugal. filipavale@fe.ucp.pt|Engineering Faculty, Portuguese Catholic University, Estrada Octávio Pato, 2635-631 Rio de Mouro, Portugal. filipavale@fe.ucp.pt', 'Portugal|Portugal|Portugal', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Cluster Analysis|DNA Methylation|DNA Restriction-Modification Enzymes|DNA, Bacterial|Helicobacter pylori|Molecular Sequence Data', 'Journal Article', '10.1093/bioinformatics/btm621', '18086685', 'The genomic methylation analysis is useful to type bacteria that have a high number of expressed type II methyltransferases. Methyltransferases are usually committed to Restriction and Modification (R-M) systems, in which the restriction endonuclease imposes high pressure on the expression of the cognate methyltransferase that hinder R-M system loss. Conventional cluster methods do not reflect this tendency. An algorithm was developed for dendrogram construction reflecting the propensity for conservation of R-M Type II systems.'),
(73872, 2008, 'bio', 'affyGG: computational protocols for genetical genomics with Affymetrix arrays', 'Alberts, Rudi|Vera, Gonzalo|Jansen, Ritsert C', 'Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Haren, The Netherlands.|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Haren, The Netherlands.|Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Haren, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 8, 'Algorithms|Animals|Chromosome Mapping|DNA Mutational Analysis|DNA Probes|Humans|Mice|Oligonucleotide Array Sequence Analysis|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/btm614', '18086686', 'Affymetrix arrays use multiple probes per gene to measure mRNA abundances. Standard software takes averages over probes. Important information may be lost if polymorphisms in the mRNA affect the hybridization of individual probes.'),
(73873, 2008, 'bio', 'Structural flexibility in proteins: impact of the crystal environment', 'Hinsen, Konrad', 'Centre de Biophysique Moléculaire (CNRS), Rue Charles Sadron, 45071 Orléans Cedex 2, France. hinsen@cnrs-orleans.fr', 'France', 0, 'Animals|Chickens|Crystallography, X-Ray|Elasticity|Models, Molecular|Muramidase|Pliability|Vibration', 'Journal Article', '10.1093/bioinformatics/btm625', '18089618', 'In the study of the structural flexibility of proteins, crystallographic Debye-Waller factors are the most important experimental information used in the calibration and validation of computational models, such as the very successful elastic network models (ENMs). However, these models are applied to single protein molecules, whereas the experiments are performed on crystals. Moreover, the energy scale in standard ENMs is undefined and must be obtained by fitting to the same data that the ENM is trying to predict, reducing the predictive power of the model.'),
(73874, 2008, 'bio', 'ZFIQ: a software package for zebrafish biology', 'Liu, Tianming|Nie, Jingxin|Li, Gang|Guo, Lei|Wong, Stephen T C', 'The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital.|The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital.|The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital.|The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital.|The Methodist Hospital Research Institute and Department of Radiology, The Methodist Hospital.', '-|-|-|-|-', 20, 'Algorithms|Animals|Chromosome Mapping|Databases, Genetic|Gene Expression Profiling|Software|Zebrafish|Zebrafish Proteins', 'Journal Article', '10.1093/bioinformatics/btm615', '18089619', 'Rapid development, transparency and small size are the outstanding features of zebrafish that make it as an increasingly important vertebrate system for developmental biology, functional genomics, disease modeling and drug discovery. Zebrafish has been regarded as ideal animal specie for studying the relationship between genotype and phenotype, for pathway analysis and systems biology. However, the tremendous amount of data generated from large numbers of embryos has led to the bottleneck of data analysis and modeling. The zebrafish image quantitator (ZFIQ) software provides streamlined data processing and analysis capability for developmental biology and disease modeling using zebrafish model.'),
(73875, 2008, 'bio', 'A novel genome-scale repeat finder geared towards transposons', 'Li, Xuehui|Kahveci, Tamer|Settles, A Mark', 'CISE Department, University of Florida, Gainesville, FL 32611, USA. xli@cise.ufl.edu|CISE Department, University of Florida, Gainesville, FL 32611, USA. xli@cise.ufl.edu|CISE Department, University of Florida, Gainesville, FL 32611, USA. xli@cise.ufl.edu', 'United States|United States|United States', 0, 'Algorithms|Arabidopsis|Chromosomes, Plant|Computational Biology|DNA Transposable Elements|Exons|Genome, Plant|Mutagenesis, Insertional|Oryza|Retroelements', 'Journal Article', '10.1093/bioinformatics/btm613', '18089620', 'Repeats are ubiquitous in genomes and play important roles in evolution. Transposable elements are a common kind of repeat. Transposon insertions can be nested and make the task of identifying repeats difficult.'),
(73876, 2008, 'bio', 'PRALINETM: a strategy for improved multiple alignment of transmembrane proteins', 'Pirovano, Walter|Feenstra, K Anton|Heringa, Jaap', 'Centre for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, De Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands.|Centre for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, De Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands.|Centre for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, De Boelelaan 1081A, 1081 HV Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands', 0, 'Algorithms|Amino Acid Sequence|Computational Biology|Membrane Proteins|Molecular Sequence Data|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btm636', '18174178', 'Membrane-bound proteins are a special class of proteins. The regions that insert into the cell-membrane have a profoundly different hydrophobicity pattern compared with soluble proteins. Multiple alignment techniques use scoring schemes tailored for sequences of soluble proteins and are therefore in principle not optimal to align membrane-bound proteins.'),
(73877, 2008, 'bio', 'DECOMP--from interpreting Mass Spectrometry peaks to solving the Money Changing Problem', 'Böcker, Sebastian|Lipták, Zsuzsanna|Martin, Marcel|Pervukhin, Anton|Sudek, Henner', 'Lehrstuhl Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.|Lehrstuhl Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.|Lehrstuhl Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.|Lehrstuhl Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.|Lehrstuhl Bioinformatik, Friedrich-Schiller-Universität Jena, Ernst-Abbe-Platz 2, 07743 Jena, Germany.', 'Germany|Germany|Germany|Germany|Germany', 10, 'Computational Biology|Mass Spectrometry|Software', 'Journal Article', '10.1093/bioinformatics/btm631', '18174179', 'We introduce Decomp, a tool that computes the sum formula of all molecules whose mass equals the input mass. This problem arises frequently in biochemistry and mass spectrometry (MS), when we know the molecular mass of a protein, DNA or metabolite fragment but have no other information. A closely related problem is known as the Money Changing Problem (MCP), where all masses are positive integers. Recently, efficient algorithms have been developed for the MCP, in which Decomp applies to real-valued MS data. The excellent performance of this method on proteomic and metabolomic MS data has recently been demonstrated. Decomp has an easy-to-use graphical interface, which caters for both types of users: those interested in solving MCP instances and those submitting MS data.'),
(73878, 2008, 'bio', 'NetworkBLAST: comparative analysis of protein networks', 'Kalaev, Maxim|Smoot, Mike|Ideker, Trey|Sharan, Roded', 'School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. kalaevma@post.tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. kalaevma@post.tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. kalaevma@post.tau.ac.il|School of Computer Science, Tel Aviv University, Tel Aviv 69978, Israel. kalaevma@post.tau.ac.il', 'Israel|Israel|Israel|Israel', 86, 'Algorithms|Animals|Computational Biology|Drosophila Proteins|Drosophila melanogaster|Internet|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Time Factors', 'Journal Article', '10.1093/bioinformatics/btm630', '18174180', 'The identification of protein complexes is a fundamental challenge in interpreting protein-protein interaction data. Cross-species analysis allows coping with the high levels of noise that are typical to these data. The NetworkBLAST web-server provides a platform for identifying protein complexes in protein-protein interaction networks. It can analyze a single network or two networks from different species. In the latter case, NetworkBLAST outputs a set of putative complexes that are evolutionarily conserved across the two networks.'),
(73879, 2008, 'bio', 'Prediction of protein functional residues from sequence by probability density estimation', 'Fischer, J D|Mayer, C E|Söding, J', 'Department for Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany.|Department for Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany.|Department for Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany.', 'Germany|Germany|Germany', 0, 'Catalytic Domain|Probability|Proteins', 'Journal Article', '10.1093/bioinformatics/btm626', '18174181', 'The prediction of ligand-binding residues or catalytically active residues of a protein may give important hints that can guide further genetic or biochemical studies. Existing sequence-based prediction methods mostly rank residue positions by evolutionary conservation calculated from a multiple sequence alignment of homologs. A problem hampering more wide-spread application of these methods is the low per-residue precision, which at 20% sensitivity is around 35% for ligand-binding residues and 20% for catalytic residues.'),
(73880, 2008, 'bio', 'A note on difficult structure alignment problems', 'Sippl, Manfred J|Wiederstein, Markus', 'Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at|Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at', 'Austria|Austria', 104, 'Algorithms|Amino Acid Sequence|Internet|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/btm622', '18174182', 'Progress in structural biology depends on several key technologies. In particular tools for alignment and superposition of protein structures are indispensable. Here we describe the use of the TopMatch web service, an effective computational tool for protein structure alignment, for the visualization of structural similarities, and for highlighting relationships found in protein classifications. We provide several instructive examples.'),
(73881, 2008, 'bio', 'Natural similarity measures between position frequency matrices with an application to clustering', 'Pape, Utz J|Rahmann, Sven|Vingron, Martin', 'Computational Biology, Max Planck Institute f. Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany. utz.pape@molgen.mpg.de|Computational Biology, Max Planck Institute f. Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany. utz.pape@molgen.mpg.de|Computational Biology, Max Planck Institute f. Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany. utz.pape@molgen.mpg.de', 'Germany|Germany|Germany', 40, 'Algorithms|Artificial Intelligence|Base Sequence|Binding Sites|Cluster Analysis|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm610', '18174183', 'Transcription factors (TFs) play a key role in gene regulation by binding to target sequences. In silico prediction of potential binding of a TF to a binding site is a well-studied problem in computational biology. The binding sites for one TF are represented by a position frequency matrix (PFM). The discovery of new PFMs requires the comparison to known PFMs to avoid redundancies. In general, two PFMs are similar if they occur at overlapping positions under a null model. Still, most existing methods compute similarity according to probabilistic distances of the PFMs. Here we propose a natural similarity measure based on the asymptotic covariance between the number of PFM hits incorporating both strands. Furthermore, we introduce a second measure based on the same idea to cluster a set of the Jaspar PFMs.'),
(73882, 2008, 'bio', 'Beyond the best match: machine learning annotation of protein sequences by integration of different sources of information', 'Tetko, Igor V|Rodchenkov, Igor V|Walter, Mathias C|Rattei, Thomas|Mewes, Hans-Werner', 'Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Neuherberg, Germany. i.tetko@gsf.de|Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Neuherberg, Germany. i.tetko@gsf.de|Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Neuherberg, Germany. i.tetko@gsf.de|Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Neuherberg, Germany. i.tetko@gsf.de|Helmholtz Zentrum München - German Research Center for Environmental Health (GmbH), Institute of Bioinformatics and Systems Biology, Neuherberg, Germany. i.tetko@gsf.de', 'Germany|Germany|Germany|Germany|Germany', 6, 'Algorithms|Bacterial Proteins|Genome, Bacterial', 'Journal Article', '10.1093/bioinformatics/btm633', '18174184', 'Accurate automatic assignment of protein functions remains a challenge for genome annotation. We have developed and compared the automatic annotation of four bacterial genomes employing a 5-fold cross-validation procedure and several machine learning methods.'),
(73883, 2008, 'bio', 'Automated programming for bioinformatics algorithm deployment', 'Alterovitz, Gil|Jiwaji, Adnaan|Ramoni, Marco F', 'Childrens Hospital Informatics Program at the Division of Health Sciences and Technology, Harvard University and Massachusetts Institute of Technology, USA. gil@mit.edu|Childrens Hospital Informatics Program at the Division of Health Sciences and Technology, Harvard University and Massachusetts Institute of Technology, USA. gil@mit.edu|Childrens Hospital Informatics Program at the Division of Health Sciences and Technology, Harvard University and Massachusetts Institute of Technology, USA. gil@mit.edu', 'United States|United States|United States', 2, 'Algorithms|Computational Biology|Computer Graphics|Programming Languages|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm602', '18174185', 'Many bioinformatics solutions suffer from the lack of usable interface/platform from which results can be analyzed and visualized. Overcoming this hurdle would allow for more widespread dissemination of bioinformatics algorithms within the biological and medical communities. The algorithms should be accessible without extensive technical support or programming knowledge. Here, we propose a dynamic wizard platform that provides users with a Graphical User Interface (GUI) for most Java bioinformatics library toolkits. The application interface is generated in real-time based on the original source code. This platform lets developers focus on designing algorithms and biologists/physicians on testing hypotheses and analyzing results.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73884, 2008, 'bio', 'Structural search and retrieval using a tableau representation of protein folding patterns', 'Konagurthu, Arun S|Stuckey, Peter J|Lesk, Arthur M', 'Department of Biochemistry and Molecular Biology and The Huck Institute for Genomics, Proteomics and Bioinformatics, The Pennsylvania State University, University Park, PA 16802, USA. arun@bx.psu.edu|Department of Biochemistry and Molecular Biology and The Huck Institute for Genomics, Proteomics and Bioinformatics, The Pennsylvania State University, University Park, PA 16802, USA. arun@bx.psu.edu|Department of Biochemistry and Molecular Biology and The Huck Institute for Genomics, Proteomics and Bioinformatics, The Pennsylvania State University, University Park, PA 16802, USA. arun@bx.psu.edu', 'United States|United States|United States', 26, 'Information Storage and Retrieval|Models, Molecular|Protein Folding|Protein Structure, Secondary', 'Journal Article', '10.1093/bioinformatics/btm641', '18175768', 'Comparison and classification of folding patterns from a database of protein structures is crucial to understand the principles of protein architecture, evolution and function. Current search methods for proteins with similar folding patterns are slow and computationally intensive. The sharp growth in the number of known protein structures poses severe challenges for methods of structural comparison. There is a need for methods that can search the database of structures accurately and rapidly. We provide several methods to search for similar folding patterns using a concise tableau representation of proteins that encodes the relative geometry of secondary structural elements. Our first approach allows the extraction of identical and very closely-related protein folding patterns in constant-time (per hit). Next, we address the hard computational problem of extraction of maximally-similar subtableaux, when comparing two tableaux. We solve the problem using Quadratic and Linear integer programming formulations and demonstrate their power to identify subtle structural similarities, especially when protein structures significantly diverge. Finally, we describe a rapid and accurate method for comparing a query structure against a database of protein domains, TableauSearch. TableauSearch is rapid enough to search the entire structural database in seconds on a standard desktop computer. Our analysis of TableauSearch on many queries shows that the method is very accurate in identifying similarities of folding patterns, even between distantly related proteins.'),
(73885, 2008, 'bio', 'Structural systems identification of genetic regulatory networks', 'Xiong, Hao|Choe, Yoonsuck', 'Department of Computer Science, Texas A&M University, College Station, TX 77843-3112, USA. hxiong@cs.tamu.edu|Department of Computer Science, Texas A&M University, College Station, TX 77843-3112, USA. hxiong@cs.tamu.edu', 'United States|United States', 19, 'Algorithms|Computational Biology|Computer Simulation|DNA Repair|Escherichia coli|Gene Regulatory Networks', 'Journal Article', '10.1093/bioinformatics/btm623', '18175769', 'Reverse engineering of genetic regulatory networks from experimental data is the first step toward the modeling of genetic networks. Linear state-space models, also known as linear dynamical models, have been applied to model genetic networks from gene expression time series data, but existing works have not taken into account available structural information. Without structural constraints, estimated models may contradict biological knowledge and estimation methods may over-fit.'),
(73886, 2008, 'bio', 'Hybrid huberized support vector machines for microarray classification and gene selection', 'Wang, Li|Zhu, Ji|Zou, Hui', 'Ross School of Business, University of Michigan, Ann Arbor, MI 48109, USA.|Ross School of Business, University of Michigan, Ann Arbor, MI 48109, USA.|Ross School of Business, University of Michigan, Ann Arbor, MI 48109, USA.', 'United States|United States|United States', 120, 'Algorithms|Artificial Intelligence|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btm579', '18175770', 'The standard L(2)-norm support vector machine (SVM) is a widely used tool for microarray classification. Previous studies have demonstrated its superior performance in terms of classification accuracy. However, a major limitation of the SVM is that it cannot automatically select relevant genes for the classification. The L(1)-norm SVM is a variant of the standard L(2)-norm SVM, that constrains the L(1)-norm of the fitted coefficients. Due to the singularity of the L(1)-norm, the L(1)-norm SVM has the property of automatically selecting relevant genes. On the other hand, the L(1)-norm SVM has two drawbacks: (1) the number of selected genes is upper bounded by the size of the training data, (2) when there are several highly correlated genes, the L(1)-norm SVM tends to pick only a few of them, and remove the rest.'),
(73887, 2008, 'bio', 'FAST: Fourier transform based algorithms for significance testing of ungapped multiple alignments', 'Nagarajan, Niranjan|Keich, Uri', 'University of Maryland, College Park, MD 20740, USA.|University of Maryland, College Park, MD 20740, USA.', 'United States|United States', 5, 'Algorithms|Computational Biology|Fourier Analysis|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btm594', '18180239', 'As was shown in Nagarajan et al. (2005), commonly used approximations for assessing the significance of multiple alignments can be be very inaccurate. To address this, we present here the FAST package, an open-source collection of programs and libraries for efficiently and reliably computing the significance of ungapped local alignments. We also describe other potential applications in Bioinformatics where these programs can be adapted for significance testing.'),
(73888, 2008, 'bio', 'The ModFOLD server for the quality assessment of protein structural models', 'McGuffin, Liam J', 'School of Biological Sciences, University of Reading, Whiteknights, Reading RG6 6AS, UK. l.j.mcguffin@reading.ac.uk', 'United Kingdom', 107, 'Computational Biology|Internet|Models, Molecular|Protein Structure, Secondary|Proteins|Sensitivity and Specificity', 'Journal Article', '10.1093/bioinformatics/btn014', '18184684', 'The reliable assessment of the quality of protein structural models is fundamental to the progress of structural bioinformatics. The ModFOLD server provides access to two accurate techniques for the global and local prediction of the quality of 3D models of proteins. Firstly ModFOLD, which is a fast Model Quality Assessment Program (MQAP) used for the global assessment of either single or multiple models. Secondly ModFOLDclust, which is a more intensive method that carries out clustering of multiple models and provides per-residue local quality assessment.'),
(73889, 2008, 'bio', 'Reconstructing ancestral genome content based on symmetrical best alignments and Dollo parsimony', 'Sakarya, Onur|Kosik, Kenneth S|Oakley, Todd H', 'Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.|Department of Computer Science, University of California, Santa Barbara, CA 93106, USA.', 'United States|United States|United States', 12, 'Algorithms|Animals|Evolution, Molecular|Gene Duplication|Genome|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btn005', '18184685', 'Gene duplications and losses (GDLs) are important events in genome evolution. They result in expansion or contraction of gene families, with a likely role in phenotypic evolution. As more genomes become available and their annotations are improved, software programs capable of rapidly and accurately identifying the content of ancestral genomes and the timings of GDLs become necessary to understand the unique evolution of each lineage.'),
(73890, 2008, 'bio', 'Interpool: interpreting smart-pooling results', 'Thierry-Mieg, Nicolas|Bailly, Gilles', 'TIMC-IMAG, CNRS UMR5525, Faculte de Medecine, 38706 La Tronche Cedex, France. nicolas.thierry-mieg@imag.fr|TIMC-IMAG, CNRS UMR5525, Faculte de Medecine, 38706 La Tronche Cedex, France. nicolas.thierry-mieg@imag.fr', 'France|France', 12, 'Algorithms|Models, Theoretical|Sensitivity and Specificity|Two-Hybrid System Techniques', 'Journal Article', '10.1093/bioinformatics/btn001', '18184686', 'In high-throughput projects aiming to identify rare positives using a binary assay, smart-pooling constitutes an appealing strategy liable of significantly reducing the number of tests while correcting for experimental noise. In order to perform simulations for choosing an appropriate set of pools, and later to interpret the experimental results, the pool outcomes must be decoded. The intuitive aim is clearly to identify the positives that gave rise to an observation, whether real or simulated. However, this goal is not well-formalized and has been the focus of very few studies.'),
(73891, 2008, 'bio', 'A hybrid model for robust detection of transcription factor binding sites', 'Gunewardena, Sumedha|Zhang, Zhaolei', 'Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College St, Toronto ON, Canada M5S 3E1, Canada. sumedha@cantab.net|Banting and Best Department of Medical Research, Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College St, Toronto ON, Canada M5S 3E1, Canada. sumedha@cantab.net', 'Canada|Canada', 10, 'Binding Sites|Computational Biology|Databases, Nucleic Acid|Models, Genetic|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/btm629', '18184687', 'The short and degenerate nature of transcription factor (TF) binding sites contributes towards a low signal to noise ratio making it very difficult to separate them from their background. In order to tackle this problem one needs to look at ways of capturing the underlying biophysical properties that best discriminates TF binding sites from their background DNA. One such discriminatory property lies in the observed compositional differences in the nucleotide levels of TF binding sites and background DNA which are a result of processes such as purifying selection and selective preferences of TF binding sites for particular nucleotides or a combination of nucleotides over others.'),
(73892, 2008, 'bio', 'Discovery of candidate KEN-box motifs using cell cycle keyword enrichment combined with native disorder prediction and motif conservation', 'Michael, Sushama|Travé, Gilles|Ramu, Chenna|Chica, Claudia|Gibson, Toby J', 'Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.|Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.|Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.|Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.|Structural and Computational Biology Unit, EMBL, Meyerhofstrasse 1, D-69117, Heidelberg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 28, 'Amino Acid Motifs|Amino Acid Sequence|Cell Cycle Proteins|Conserved Sequence|Humans|Molecular Sequence Data', 'Journal Article', '10.1093/bioinformatics/btm624', '18184688', 'KEN-box-mediated target selection is one of the mechanisms used in the proteasomal destruction of mitotic cell cycle proteins via the APC/C complex. While annotating the Eukaryotic Linear Motif resource (ELM, http://elm.eu.org/), we found that KEN motifs were significantly enriched in human protein entries with cell cycle keywords in the UniProt/Swiss-Prot database-implying that KEN-boxes might be more common than reported.'),
(73893, 2008, 'bio', 'Evigan: a hidden variable model for integrating gene evidence for eukaryotic gene prediction', 'Liu, Qian|Mackey, Aaron J|Roos, David S|Pereira, Fernando C N', 'Department of Computer and Information Science, University of Pennsylvania, Philadelphia PA 19104, USA. qianliu@seas.upenn.edu|Department of Computer and Information Science, University of Pennsylvania, Philadelphia PA 19104, USA. qianliu@seas.upenn.edu|Department of Computer and Information Science, University of Pennsylvania, Philadelphia PA 19104, USA. qianliu@seas.upenn.edu|Department of Computer and Information Science, University of Pennsylvania, Philadelphia PA 19104, USA. qianliu@seas.upenn.edu', 'United States|United States|United States|United States', 36, 'Animals|Automation|Database Management Systems|Databases, Genetic|Genome|Humans|Likelihood Functions|Models, Genetic', 'Journal Article', '10.1093/bioinformatics/btn004', '18187439', 'The increasing diversity and variable quality of evidence relevant to gene annotation argues for a probabilistic framework that automatically integrates such evidence to yield candidate gene models.'),
(73894, 2008, 'bio', 'Bioinformatics models for predicting antigenic variants of influenza A/H3N2 virus', 'Liao, Yu-Chieh|Lee, Min-Shi|Ko, Chin-Yu|Hsiung, Chao A', 'Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan 350, Taiwan.|Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan 350, Taiwan.|Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan 350, Taiwan.|Division of Biostatistics and Bioinformatics, National Health Research Institutes, Zhunan 350, Taiwan.', '-|-|-|-', 62, 'Amino Acid Sequence|Antigenic Variation|Antigens, Viral|Computational Biology|Hemagglutinin Glycoproteins, Influenza Virus|Influenza A Virus, H3N2 Subtype|Models, Molecular|Models, Statistical|Molecular Sequence Data|Phylogeny|Regression Analysis', 'Journal Article', '10.1093/bioinformatics/btm638', '18187440', 'Continual and accumulated mutations in hemagglutinin (HA) protein of influenza A virus generate novel antigenic strains that cause annual epidemics.'),
(73895, 2008, 'bio', 'OutlierD: an R package for outlier detection using quantile regression on mass spectrometry data', 'Cho, Hyungjun|Kim, Yang-Jin|Jung, Hee Jung|Lee, Sang-Won|Lee, Jae Won', 'Department of Statistics, Department of Biostatistics, Institute of Statistics and Department of Chemistry, Korea University, Seoul, Korea.|Department of Statistics, Department of Biostatistics, Institute of Statistics and Department of Chemistry, Korea University, Seoul, Korea.|Department of Statistics, Department of Biostatistics, Institute of Statistics and Department of Chemistry, Korea University, Seoul, Korea.|Department of Statistics, Department of Biostatistics, Institute of Statistics and Department of Chemistry, Korea University, Seoul, Korea.|Department of Statistics, Department of Biostatistics, Institute of Statistics and Department of Chemistry, Korea University, Seoul, Korea.', '-|-|-|-|-', 17, 'Algorithms|Artifacts|Data Interpretation, Statistical|Mass Spectrometry|Peptide Mapping|Programming Languages|Regression Analysis|Reproducibility of Results|Sensitivity and Specificity|Software', 'Evaluation Studies', '10.1093/bioinformatics/btn012', '18187441', 'It is important to preprocess high-throughput data generated from mass spectrometry experiments in order to obtain a successful proteomics analysis. Outlier detection is an important preprocessing step. A naive outlier detection approach may miss many true outliers and instead select many non-outliers because of the heterogeneity of the variability observed commonly in high-throughput data. Because of this issue, we developed a outlier detection software program accounting for the heterogeneous variability by utilizing linear, non-linear and non-parametric quantile regression techniques. Our program was developed using the R computer language. As a consequence, it can be used interactively and conveniently in the R environment.'),
(73896, 2008, 'bio', 'Incorporating sequence information into the scoring function: a hidden Markov model for improved peptide identification', 'Khatun, Jainab|Hamlett, Eric|Giddings, Morgan C', 'Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.|Department of Microbiology and Immunology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.', 'United States|United States|United States', 11, 'Algorithms|Markov Chains|Models, Theoretical|Peptides|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization|Tandem Mass Spectrometry', 'Journal Article', '10.1093/bioinformatics/btn011', '18187442', 'The identification of peptides by tandem mass spectrometry (MS/MS) is a central method of proteomics research, but due to the complexity of MS/MS data and the large databases searched, the accuracy of peptide identification algorithms remains limited. To improve the accuracy of identification we applied a machine-learning approach using a hidden Markov model (HMM) to capture the complex and often subtle links between a peptide sequence and its MS/MS spectrum.'),
(73897, 2008, 'bio', 'A feed-forward loop guarantees robust behavior in Escherichia coli carbohydrate uptake', 'Kremling, A|Bettenbrock, K|Gilles, E D', 'Systems Biology Group, Max-Planck-Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. kremling@mpi-magdeburg.mpg.de|Systems Biology Group, Max-Planck-Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. kremling@mpi-magdeburg.mpg.de|Systems Biology Group, Max-Planck-Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany. kremling@mpi-magdeburg.mpg.de', 'Germany|Germany|Germany', 35, 'Carbohydrate Metabolism|Escherichia coli|Kinetics|Models, Theoretical', 'Journal Article', '10.1093/bioinformatics/btn010', '18187443', 'In Escherichia coli, the phosphoenolpyruvate: carbohydrate phosphotransferase system acts like a sensory element which is able to measure the flux through glycolysis. Since the output of the sensor, the phosphorylated form of protein EIIA, is connected to the activity of the global transcription factor Crp, the kinetic and structural properties of the system are important for the understanding of the overall cellular behavior.'),
(73898, 2008, 'bio', 'Effect of spatial distribution of T-Cells and HIV load on HIV progression', 'Graziano, Frank M|Kettoola, Samira Y|Munshower, Judy M|Stapleton, Jack T|Towfic, George J', 'University of Wisconsin Hospital and Clinics, Wisconsin-Madison, USA.|University of Wisconsin Hospital and Clinics, Wisconsin-Madison, USA.|University of Wisconsin Hospital and Clinics, Wisconsin-Madison, USA.|University of Wisconsin Hospital and Clinics, Wisconsin-Madison, USA.|University of Wisconsin Hospital and Clinics, Wisconsin-Madison, USA.', 'United States|United States|United States|United States|United States', 2, 'Anti-HIV Agents|Computer Simulation|Disease Progression|HIV|HIV Infections|Humans|Models, Immunological|Reverse Transcriptase Inhibitors|T-Lymphocytes|Viral Load', 'Journal Article', '10.1093/bioinformatics/btn008', '18187444', 'We present a spatial-temporal (ST) human immunodeficiency virus (HIV) simulation model to investigate the spatial distribution of viral load and T-cells during HIV progression. The proposed model uses the Finite Element (FE) method to divide a considered infected region into interconnected subregions each containing viral population and T-cells. HIV T-cells and viral load are traced and counted within and between subregions to estimate their effect upon neighboring regions. The objective is to estimate overall ST changes of HIV progression and to study the ST therapeutic effect upon HIV dynamics in spatial and temporal domains. We introduce sub-regional (spatial) parameters of T-cells and viral load production and elimination to estimate the spatial propagation and interaction of HIV dynamics under the influence of a 3TC D4T Reverse Transcriptase Inhibitors (RTI) drug regimen.'),
(73899, 2008, 'bio', 'Pinnacle: a fast, automatic and accurate method for detecting and quantifying protein spots in 2-dimensional gel electrophoresis data', 'Morris, Jeffrey S|Clark, Brittan N|Gutstein, Howard B', 'Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd Unit 447, Houston, TX 77030-4009, USA. jefmorris@mdanderson.org|Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd Unit 447, Houston, TX 77030-4009, USA. jefmorris@mdanderson.org|Department of Biostatistics, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd Unit 447, Houston, TX 77030-4009, USA. jefmorris@mdanderson.org', 'United States|United States|United States', 48, 'Animals|Cell Line, Tumor|Computational Biology|Electrophoresis, Gel, Two-Dimensional|Humans|Male|Morphine|Neoplasm Proteins|Proteins|Rats|Rats, Sprague-Dawley|Software', 'Journal Article', '10.1093/bioinformatics/btm590', '18194961', 'One of the key limitations for proteomic studies using 2-dimensional gel electrophoresis (2DE) is the lack of rapid, robust and reproducible methods for detecting, matching and quantifying protein spots. The most commonly used approaches involve first detecting spots and drawing spot boundaries on individual gels, then matching spots across gels and finally quantifying each spot by calculating normalized spot volumes. This approach is time consuming, error-prone and frequently requires extensive manual editing, which can unintentionally introduce bias into the results.'),
(73900, 2008, 'bio', 'Figaro: a novel statistical method for vector sequence removal', 'White, James Robert|Roberts, Michael|Yorke, James A|Pop, Mihai', 'Center for Bioinformatics and Computational Biology, University of Maryland - College Park, MD 20742, USA.|Center for Bioinformatics and Computational Biology, University of Maryland - College Park, MD 20742, USA.|Center for Bioinformatics and Computational Biology, University of Maryland - College Park, MD 20742, USA.|Center for Bioinformatics and Computational Biology, University of Maryland - College Park, MD 20742, USA.', 'United States|United States|United States|United States', 28, 'Animals|Base Sequence|Computational Biology|Drosophila|Genetic Vectors|Genome, Bacterial|Molecular Sequence Data|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btm632', '18202027', 'Sequences produced by automated Sanger sequencing machines frequently contain fragments of the cloning vector on their ends. Software tools currently available for identifying and removing the vector sequence require knowledge of the vector sequence, specific splice sites and any adapter sequences used in the experiment-information often omitted from public databases. Furthermore, the clipping coordinates themselves are missing or incorrectly reported. As an example, within the approximately 1.24 billion shotgun sequences deposited in the NCBI Trace Archive, as many as approximately 735 million (approximately 60%) lack vector clipping information. Correct clipping information is essential to scientists attempting to validate, improve and even finish the increasingly large number of genomes released at a draft quality level.'),
(73901, 2008, 'bio', 'The SGN comparative map viewer', 'Mueller, Lukas A|Mills, Adri A|Skwarecki, Beth|Buels, Robert M|Menda, Naama|Tanksley, Steven D', 'Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu|Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu|Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu|Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu|Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu|Department of Plant Breeding and Genetics, Cornell University, Ithaca, NY 14853, USA. lam87@cornell.edu', 'United States|United States|United States|United States|United States|United States', 21, 'Algorithms|Chromosome Mapping|Computer Graphics|Evolution, Molecular|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm597', '18202028', 'With the rapid accumulation of genetic data for a multitude of different species, the availability of intuitive comparative genomic tools becomes an important requirement for the research community. Here we describe a web-based comparative viewer for mapping data, including genetic, physical and cytological maps, that is part of the SGN website (http://sgn.cornell.edu/) but that can also be installed and adapted for other websites. In addition to viewing and comparing different maps stored in the SGN database, the viewer allows users to upload their own maps and compare them to other maps in the system. The viewer is implemented in object oriented Perl, with a simple extensible interface to write data adapters for other relational database schemas and flat file formats.'),
(73902, 2008, 'bio', 'QTLNetwork: mapping and visualizing genetic architecture of complex traits in experimental populations', 'Yang, Jian|Hu, Chengcheng|Hu, Han|Yu, Rongdong|Xia, Zhen|Ye, Xiuzi|Zhu, Jun', 'Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.|Institute of Bioinformatics, Zhejiang University, Hangzhou, China, 310029.', 'China|China|China|China|China|China|China', 305, 'Programming Languages|Quantitative Trait Loci|Recombination, Genetic', 'Journal Article', '10.1093/bioinformatics/btm494', '18202029', 'QTLNetwork is a software package for mapping and visualizing the genetic architecture underlying complex traits for experimental populations derived from a cross between two inbred lines. It can simultaneously map quantitative trait loci (QTL) with individual effects, epistasis and QTL-environment interaction. Currently, it is able to handle data from F(2), backcross, recombinant inbred lines and double-haploid populations, as well as populations from specific mating designs (immortalized F(2) and BC(n)F(n) populations). The Windows version of QTLNetwork was developed with a graphical user interface. Alternatively, the command-line versions have the facility to be run in other prevalent operating systems, such as Linux, Unix and MacOS.'),
(73903, 2008, 'bio', 'Inferring horizontal transfers in the presence of rearrangements by the minimum evolution criterion', 'Birin, Hadas|Gal-Or, Zohar|Elias, Isaac|Tuller, Tamir', 'School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Tel Aviv University, Tel Aviv, Israel.|School of Computer Science, Tel Aviv University, Tel Aviv, Israel.', 'Israel|Israel|Israel|Israel', 8, 'Algorithms|Bacterial Proteins|Base Sequence|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Gene Rearrangement, T-Lymphocyte|Gene Transfer, Horizontal|Genetic Variation|Models, Genetic|Molecular Sequence Data|Plant Proteins|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btn024', '18203769', 'The evolution of viruses is very rapid and in addition to local point mutations (insertion, deletion, substitution) it also includes frequent recombinations, genome rearrangements and horizontal transfer of genetic materials (HGTS). Evolutionary analysis of viral sequences is therefore a complicated matter for two main reasons: First, due to HGTs and recombinations, the right model of evolution is a network and not a tree. Second, due to genome rearrangements, an alignment of the input sequences is not guaranteed. These facts encourage developing methods for inferring phylogenetic networks that do not require aligned sequences as input.'),
(73904, 2008, 'bio', 'Sparse representation and Bayesian detection of genome copy number alterations from microarray data', 'Pique-Regi, Roger|Monso-Varona, Jordi|Ortega, Antonio|Seeger, Robert C|Triche, Timothy J|Asgharzadeh, Shahab', 'Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu|Signal and Image Processing Institute, Ming Hsieh Department of Electrical Engineering, Viterbi School of Engineering, University of Southern California, EEB 400, 3740 McClintock Ave, Los Angeles, CA 90089-2564, USA. jpei@chop.swmed.edu', 'United States|United States|United States|United States|United States|United States', 95, 'Artificial Intelligence|Bayes Theorem|Chromosome Mapping|DNA Mutational Analysis|DNA, Neoplasm|Gene Dosage|Genetic Predisposition to Disease|Genetic Variation|Humans|Mutation|Neuroblastoma|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/btm601', '18203770', 'Genomic instability in cancer leads to abnormal genome copy number alterations (CNA) that are associated with the development and behavior of tumors. Advances in microarray technology have allowed for greater resolution in detection of DNA copy number changes (amplifications or deletions) across the genome. However, the increase in number of measured signals and accompanying noise from the array probes present a challenge in accurate and fast identification of breakpoints that define CNA. This article proposes a novel detection technique that exploits the use of piece wise constant (PWC) vectors to represent genome copy number and sparse Bayesian learning (SBL) to detect CNA breakpoints.'),
(73905, 2008, 'bio', 'BEN: a novel domain in chromatin factors and DNA viral proteins', 'Abhiman, Saraswathi|Iyer, Lakshminarayan M|Aravind, L', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA.', 'United States|United States|United States', 54, 'Amino Acid Sequence|Animals|Chromatin|Chromosomal Proteins, Non-Histone|DNA Viruses|Drosophila Proteins|Evolution, Molecular|Molecular Sequence Data|Protein Structure, Tertiary|Sequence Alignment|Viral Proteins', 'Journal Article', '10.1093/bioinformatics/btn007', '18203771', 'We report a previously uncharacterized alpha-helical module, the BEN domain, in diverse animal proteins such as BANP/SMAR1, NAC1 and the Drosophila mod(mdg4) isoform C, in the chordopoxvirus virosomal protein E5R and in several proteins of polydnaviruses. Contextual analysis suggests that the BEN domain mediates protein-DNA and protein-protein interactions during chromatin organization and transcription. The presence of BEN domains in a poxviral early virosomal protein and in polydnaviral proteins also suggests a possible role for them in organization of viral DNA during replication or transcription.'),
(73906, 2008, 'bio', 'Predicting disulfide bond connectivity in proteins by correlated mutations analysis', 'Rubinstein, Rotem|Fiser, Andras', 'Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA. rrubinst@aecom.yu.edu|Department of Biochemistry, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA. rrubinst@aecom.yu.edu', 'United States|United States', 37, 'Amino Acid Sequence|Computational Biology|Conserved Sequence|Cysteine|Disulfides|Humans|Molecular Sequence Data|Mutation|Oxidation-Reduction|Pepsin A|Proteins|Sequence Alignment|beta-Lactamases', 'Journal Article', '10.1093/bioinformatics/btm637', '18203772', 'Prediction of disulfide bond connectivity facilitates structural and functional annotation of proteins. Previous studies suggest that cysteines of a disulfide bond mutate in a correlated manner.'),
(73907, 2008, 'bio', 'Multiple testing on the directed acyclic graph of gene ontology', 'Goeman, Jelle J|Mansmann, Ulrich', 'Department of Medical Statistics, Postzone S5-P, P.O. Box 9600, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Postzone S5-P, P.O. Box 9600, 2300 RC Leiden, The Netherlands. j.j.goeman@lumc.nl', 'Netherlands|Netherlands', 59, 'Algorithms|Breast Neoplasms|Computational Biology|Female|Genes, Neoplasm|Humans|Leukemia, Myeloid, Acute', 'Journal Article', '10.1093/bioinformatics/btm628', '18203773', 'Current methods for multiplicity adjustment do not make use of the graph structure of Gene Ontology (GO) when testing for association of expression profiles of GO terms with a response variable.'),
(73908, 2008, 'bio', 'GENESIS: genome evolution scenarios', 'Gog, Simon|Bader, Martin|Ohlebusch, Enno', 'Institute of Theoretical Computer Science, University of Ulm, D-89069 Ulm, Germany. simon.gog@uni-ulm.de|Institute of Theoretical Computer Science, University of Ulm, D-89069 Ulm, Germany. simon.gog@uni-ulm.de|Institute of Theoretical Computer Science, University of Ulm, D-89069 Ulm, Germany. simon.gog@uni-ulm.de', 'Germany|Germany|Germany', 2, 'Algorithms|Animals|Anopheles|Biological Evolution|DNA|Drosophila melanogaster|Genome', 'Journal Article', '10.1093/bioinformatics/btn026', '18204053', 'We implemented a software tool called GENESIS for three different genome rearrangement problems: Sorting a unichromosomal genome by weighted reversals and transpositions (SwRT), sorting a multichromosomal genome by reversals, translocations, fusions and fissions (SRTl), and sorting a multichromosomal genome by weighted reversals, translocations, fusions, fissions and transpositions (SwRTTl).'),
(73909, 2008, 'bio', 'Using repeated measurements to validate hierarchical gene clusters', 'Bréhélin, Laurent|Gascuel, Olivier|Martin, Olivier', 'Méthodes et Algorithmes pour la Bioinformatique, LIRMM, CNRS - University Montpellier II, France. brehelin@lirmm.fr|Méthodes et Algorithmes pour la Bioinformatique, LIRMM, CNRS - University Montpellier II, France. brehelin@lirmm.fr|Méthodes et Algorithmes pour la Bioinformatique, LIRMM, CNRS - University Montpellier II, France. brehelin@lirmm.fr', 'France|France|France', 12, 'Animals|Databases, Genetic|Humans|Multigene Family|Protein Binding|Proteins', 'Journal Article', '10.1093/bioinformatics/btn017', '18204054', 'Hierarchical clustering is a common approach to study protein and gene expression data. This unsupervised technique is used to find clusters of genes or proteins which are expressed in a coordinated manner across a set of conditions. Because of both the biological and technical variability, experimental repetitions are generally performed. In this work, we propose an approach to evaluate the stability of clusters derived from hierarchical clustering by taking repeated measurements into account.'),
(73910, 2008, 'bio', 'Estimation and assessment of raw copy numbers at the single locus level', 'Bengtsson, H|Irizarry, R|Carvalho, B|Speed, T P', 'Department of Statistics, University of California, Berkeley, USA, Department of Biostatistics, Johns Hopkins University, Baltimore, USA.|Department of Statistics, University of California, Berkeley, USA, Department of Biostatistics, Johns Hopkins University, Baltimore, USA.|Department of Statistics, University of California, Berkeley, USA, Department of Biostatistics, Johns Hopkins University, Baltimore, USA.|Department of Statistics, University of California, Berkeley, USA, Department of Biostatistics, Johns Hopkins University, Baltimore, USA.', 'United States|United States|United States|United States', 111, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|Markov Chains|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Quantitative Trait Loci|Software', 'Evaluation Studies', '10.1093/bioinformatics/btn016', '18204055', 'Although copy-number aberrations are known to contribute to the diversity of the human DNA and cause various diseases, many aberrations and their phenotypes are still to be explored. The recent development of single-nucleotide polymorphism (SNP) arrays provides researchers with tools for calling genotypes and identifying chromosomal aberrations at an order-of-magnitude greater resolution than possible a few years ago. The fundamental problem in array-based copy-number (CN) analysis is to obtain CN estimates at a single-locus resolution with high accuracy and precision such that downstream segmentation methods are more likely to succeed.'),
(73911, 2008, 'bio', 'TreeMos: a high-throughput phylogenomic approach to find and visualize phylogenetic mosaicism', 'Moore, J D|Allaby, R G', 'Warwick HRI, University of Warwick, Warwick, CV35 9EF, UK. jonathan.moore@warwick.ac.uk|Warwick HRI, University of Warwick, Warwick, CV35 9EF, UK. jonathan.moore@warwick.ac.uk', 'United Kingdom|United Kingdom', 0, 'Computer Graphics|Genomics|Information Storage and Retrieval|Mosaicism|Phylogeny|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btn027', '18204056', 'TreeMos is a novel high-throughput graphical analysis application that allows the user to search for phylogenetic mosaicism among one or more DNA or protein sequence multiple alignments and additional unaligned sequences. TreeMos uses a sliding window and local alignment algorithm to identify the nearest neighbour of each sequence segment, and visualizes instances of sequence segments whose nearest neighbour is anomalous to that identified using the global alignment. Data sets can include whole genome sequences allowing phylogenomic analyses in which mosaicism may be attributed to recombination between any two points in the genome. TreeMos can be run from the command line, or within a web browser allowing the relationships between taxa to be explored by drill-through.'),
(73912, 2008, 'bio', 'TagFinder for the quantitative analysis of gas chromatography--mass spectrometry (GC-MS)-based metabolite profiling experiments', 'Luedemann, Alexander|Strassburg, Katrin|Erban, Alexander|Kopka, Joachim', 'Department Prof. L. Willmitzer, Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, D-14476 Potsdam-Golm, Germany.|Department Prof. L. Willmitzer, Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, D-14476 Potsdam-Golm, Germany.|Department Prof. L. Willmitzer, Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, D-14476 Potsdam-Golm, Germany.|Department Prof. L. Willmitzer, Max Planck Institute of Molecular Plant Physiology, Am Muehlenberg 1, D-14476 Potsdam-Golm, Germany.', 'Germany|Germany|Germany|Germany', 149, 'Gas Chromatography-Mass Spectrometry|Metabolism|Programming Languages', 'Journal Article', '10.1093/bioinformatics/btn023', '18204057', 'Typical GC-MS-based metabolite profiling experiments may comprise hundreds of chromatogram files, which each contain up to 1000 mass spectral tags (MSTs). MSTs are the characteristic patterns of approximately 25-250 fragment ions and respective isotopomers, which are generated after gas chromatography (GC) by electron impact ionization (EI) of the separated chemical molecules. These fragment ions are subsequently detected by time-of-flight (TOF) mass spectrometry (MS). MSTs of profiling experiments are typically reported as a list of ions, which are characterized by mass, chromatographic retention index (RI) or retention time (RT), and arbitrary abundance. The first two parameters allow the identification, the later the quantification of the represented chemical compounds. Many software tools have been reported for the pre-processing, the so-called curve resolution and deconvolution, of GC-(EI-TOF)-MS files. Pre-processing tools generate numerical data matrices, which contain all aligned MSTs and samples of an experiment. This process, however, is error prone mainly due to (i) the imprecise RI or RT alignment of MSTs and (ii) the high complexity of biological samples. This complexity causes co-elution of compounds and as a consequence non-selective, in other words impure MSTs. The selection and validation of optimal fragment ions for the specific and selective quantification of simultaneously eluting compounds is, therefore, mandatory. Currently validation is performed in most laboratories under human supervision. So far no software tool supports the non-targeted and user-independent quality assessment of the data matrices prior to statistical analysis. TagFinder may fill this gap.'),
(73913, 2008, 'bio', 'DiMoVo: a Voronoi tessellation-based method for discriminating crystallographic and biological protein-protein interactions', 'Bernauer, Julie|Bahadur, Ranjit Prasad|Rodier, Francis|Janin, Joël|Poupon, Anne', 'Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.|Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.|Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.|Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.|Department of Structural Biology, Fairchild Science Building, Stanford University School of Medicine, Stanford, CA 94305-5126, USA.', 'United States|United States|United States|United States|United States', 0, 'Crystallography|Models, Theoretical|Protein Binding|Proteins|ROC Curve|Reproducibility of Results', 'Journal Article', '10.1093/bioinformatics/btn022', '18204058', 'Knowledge of the oligomeric state of a protein is often essential for understanding its function and mechanism. Within a protein crystal, each protein monomer is in contact with many others, forming many small interfaces and a few larger ones that are biologically significant if the protein is a homodimer in solution, but not if the protein is monomeric. Telling such crystal dimers from real ones remains a difficult task.'),
(73914, 2008, 'bio', 'A segmental maximum a posteriori approach to genome-wide copy number profiling', 'Andersson, Robin|Bruder, Carl E G|Piotrowski, Arkadiusz|Menzel, Uwe|Nord, Helena|Sandgren, Johanna|Hvidsten, Torgeir R|Diaz de Ståhl, Teresita|Dumanski, Jan P|Komorowski, Jan', 'The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.|The Linnaeus Centre for Bioinformatics, Uppsala University, 751 24 Uppsala, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden|Sweden', 26, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|Gene Dosage|Gene Expression Profiling|Markov Chains|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Evaluation Studies', '10.1093/bioinformatics/btn003', '18204059', 'Copy number profiling methods aim at assigning DNA copy numbers to chromosomal regions using measurements from microarray-based comparative genomic hybridizations. Among the proposed methods to this end, Hidden Markov Model (HMM)-based approaches seem promising since DNA copy number transitions are naturally captured in the model. Current discrete-index HMM-based approaches do not, however, take into account heterogeneous information regarding the genomic overlap between clones. Moreover, the majority of existing methods are restricted to chromosome-wise analysis.'),
(73915, 2008, 'bio', 'HCGene: a software tool to support the hierarchical classification of genes', 'Valentini, Giorgio|Cesa-Bianchi, Nicolò', 'Dip. di Scienze dellInformazione, Università degli Studi di Milano, Via Comelico 39, Italy. valentini@dsi.unimi.it|Dip. di Scienze dellInformazione, Università degli Studi di Milano, Via Comelico 39, Italy. valentini@dsi.unimi.it', 'Italy|Italy', 0, 'Databases, Genetic|Genes|Software', 'Journal Article', '10.1093/bioinformatics/btn015', '18204060', 'The R package HCGene (Hierarchical Classification of Genes) implements methods to process and analyze the Gene Ontology and the FunCat taxonomy in order to support the functional classification of genes. HCGene allows the extraction of subgraphs and subtrees related to specific biological problems, the labeling of genes and gene products with multiple and hierarchical functional classes, and the association of different types of bio-molecular data to genes for learning to predict their functions.'),
(73916, 2008, 'bio', 'PGMapper: a web-based tool linking phenotype to genes', 'Xiong, Qing|Qiu, Yuhui|Gu, Weikuan', 'Department of Orthopedic Surgery-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA. qxiong@utmem.edu|Department of Orthopedic Surgery-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA. qxiong@utmem.edu|Department of Orthopedic Surgery-Campbell Clinic, University of Tennessee Health Science Center, Memphis, TN 38163, USA. qxiong@utmem.edu', 'United States|United States|United States', 38, 'Algorithms|Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Phenotype|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn002', '18204061', 'With the availability of whole genome sequence in many species, linkage analysis, positional cloning and microarray are gradually becoming powerful tools for investigating the links between phenotype and genotype or genes. However, in these methods, causative genes underlying a quantitative trait locus, or a disease, are usually located within a large genomic region or a large set of genes. Examining the function of every gene is very time consuming and needs to retrieve and integrate the information from multiple databases or genome resources. PGMapper is a software tool for automatically matching phenotype to genes from a defined genome region or a group of given genes by combining the mapping information from the Ensembl database and gene function information from the OMIM and PubMed databases. PGMapper is currently available for candidate gene search of human, mouse, rat, zebrafish and 12 other species.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(73917, 2008, 'bio', 'Reconstruction of genetic association networks from microarray data: a partial least squares approach', 'Pihur, Vasyl|Datta, Somnath|Datta, Susmita', 'Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA.|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA.|Department of Bioinformatics and Biostatistics, University of Louisville, Louisville, KY 40292, USA.', 'United States|United States|United States', 43, 'Algorithms|Computer Simulation|Databases, Genetic|Gene Regulatory Networks|Genes, Fungal|Least-Squares Analysis|Oligonucleotide Array Sequence Analysis|ROC Curve|Saccharomyces cerevisiae|Software', 'Journal Article', '10.1093/bioinformatics/btm640', '18204062', 'Gene association/interaction networks provide vast amounts of information about essential processes inside the cell. A complete picture of gene-gene associations/interactions would open new horizons for biologists, ranging from pure appreciation to successful manipulation of biological pathways for therapeutic purposes. Therefore, identification of important biological complexes whose members (genes and their products proteins) interact with each other is of prime importance. Numerous experimental methods exist but, for the most part, they are costly and labor intensive. Computational techniques, such as the one proposed in this work, provide a quick budget solution that can be used as a screening tool before more expensive techniques are attempted. Here, we introduce a novel computational method based on the partial least squares (PLS) regression technique for reconstruction of genetic networks from microarray data.'),
(73918, 2008, 'bio', 'A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments', 'Hong, Fangxin|Breitling, Rainer', 'Department of Biostatistics, Division of Information Sciences, City of Hope National Medical Center, Beckman Research Institute, 1500 Duarte Rd, Duarte, CA 91010, USA. fxhong@jimmy.harvard.edu|Department of Biostatistics, Division of Information Sciences, City of Hope National Medical Center, Beckman Research Institute, 1500 Duarte Rd, Duarte, CA 91010, USA. fxhong@jimmy.harvard.edu', 'United States|United States', 170, 'Data Interpretation, Statistical|Databases, Protein|Gene Expression Profiling|Meta-Analysis as Topic|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btm620', '18204063', 'The proliferation of public data repositories creates a need for meta-analysis methods to efficiently evaluate, integrate and validate related datasets produced by independent groups. A t-based approach has been proposed to integrate effect size from multiple studies by modeling both intra- and between-study variation. Recently, a non-parametric rank product method, which is derived based on biological reasoning of fold-change criteria, has been applied to directly combine multiple datasets into one meta study. Fishers Inverse chi(2) method, which only depends on P-values from individual analyses of each dataset, has been used in a couple of medical studies. While these methods address the question from different angles, it is not clear how they compare with each other.'),
(73919, 2008, 'bio', 'A machine-learning approach to combined evidence validation of genome assemblies', 'Choi, Jeong-Hyeon|Kim, Sun|Tang, Haixu|Andrews, Justen|Gilbert, Don G|Colbourne, John K', 'The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.|The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.|The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.|The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.|The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.|The Center for Genomics and Bioinformatics, School of Informatics and Department of Biology, Indiana University, IN 47405, USA.', 'India|India|India|India|India|India', 5, 'Algorithms|Animals|Artificial Intelligence|Base Sequence|Contig Mapping|Drosophila|Molecular Sequence Data|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btm608', '18204064', 'While it is common to refer to the genome sequence as if it were a single, complete and contiguous DNA string, it is in fact an assembly of millions of small, partially overlapping DNA fragments. Sophisticated computer algorithms (assemblers and scaffolders) merge these DNA fragments into contigs, and place these contigs into sequence scaffolds using the paired-end sequences derived from large-insert DNA libraries. Each step in this automated process is susceptible to producing errors, hence, the resulting draft assembly represents (in practice) only a likely assembly that requires further validation. Knowing which parts of the draft assembly are likely free of errors is critical if researchers are to draw reliable conclusions from the assembled sequence data.'),
(73920, 2008, 'bio', 'Precise score for the prediction of peptides cleaved by the proteasome', 'Ginodi, Ido|Vider-Shalit, Tal|Tsaban, Lea|Louzoun, Yoram', 'Department of Mathematics and Statistics, Bar-Ilan University, Ramat-Gan, Israel, 52900.|Department of Mathematics and Statistics, Bar-Ilan University, Ramat-Gan, Israel, 52900.|Department of Mathematics and Statistics, Bar-Ilan University, Ramat-Gan, Israel, 52900.|Department of Mathematics and Statistics, Bar-Ilan University, Ramat-Gan, Israel, 52900.', 'Israel|Israel|Israel|Israel', 16, 'Algorithms|Computational Biology|Humans|Peptides|Proteasome Endopeptidase Complex', 'Journal Article', '10.1093/bioinformatics/btm616', '18216070', 'An 8-10mer can become a cytotoxic T lymphocyte epitope only if it is cleaved by the proteasome, transported by TAP and presented by MHC-I molecules. Thus most of the epitopes presented to cytotoxic T cells in the context of MHC-I molecules are products of intracellular proteasomal cleavage. These products are not random, as peptide production is a function of the precise sequence of the proteins processed by the proteasome.'),
(73921, 2008, 'bio', 'Observation of multiple folding pathways of beta-hairpin trpzip2 from independent continuous folding trajectories', 'Chen, Changjun|Xiao, Yi', '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', 0, 'Amino Acid Sequence|Computer Simulation|Hydrogen Bonding|Molecular Sequence Data|Peptides|Protein Conformation|Protein Folding', 'Journal Article', '10.1093/bioinformatics/btn029', '18216071', 'After 10-year investigations, the folding mechanisms of beta-hairpins are still under debate. Experiments strongly support zip-out pathway, while most simulations prefer the hydrophobic collapse model (including middle-out and zip-in pathways). In this article, we show that all pathways can occur during the folding of beta-hairpins but with different probabilities. The zip-out pathway is the most probable one. This is in agreement with the experimental results. We came to our conclusions by 38 100-ns room-temperature all-atom molecular dynamics simulations of the beta-hairpin trpzip2. Our results may help to clarify the inconsistencies in the current pictures of beta-hairpin folding mechanisms.'),
(73922, 2008, 'bio', 'A discrete view on fold space', 'Sippl, Manfred J|Suhrer, Stefan J|Gruber, Markus|Wiederstein, Markus', 'Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at|Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at|Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at|Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at', 'Austria|Austria|Austria|Austria', 15, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Folding|Proteins|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn020', '18218654', 'The database of known protein structures contains an overwhelming number of structural similarities that frequently point to intriguing biological relationships. The similarities are often difficult to spot, and once detected their comprehension needs proper visualization. Here we introduce the new concept of a Fold Space Navigator, a user interface enabling the efficient navigation through fold space and the instantaneous visualization of pairwise structure similarities.'),
(73923, 2008, 'bio', 'Flexible informatics for linking experimental data to mathematical models via DataRail', 'Saez-Rodriguez, Julio|Goldsipe, Arthur|Muhlich, Jeremy|Alexopoulos, Leonidas G|Millard, Bjorn|Lauffenburger, Douglas A|Sorger, Peter K', 'Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.|Center for Cell Decision Processes, Department of Systems Biology, Harvard Medical School, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States|United States', 58, 'Algorithms|Computational Biology|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Biological|Programming Languages|Proteome|Research Design|Software', 'Evaluation Studies', '10.1093/bioinformatics/btn018', '18218655', 'Linking experimental data to mathematical models in biology is impeded by the lack of suitable software to manage and transform data. Model calibration would be facilitated and models would increase in value were it possible to preserve links to training data along with a record of all normalization, scaling, and fusion routines used to assemble the training data from primary results.'),
(73924, 2008, 'bio', 'Using native and syntenically mapped cDNA alignments to improve de novo gene finding', 'Stanke, Mario|Diekhans, Mark|Baertsch, Robert|Haussler, David', 'Center for Biomolecular Science and Engineering, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA. mstanke@gwdg.de|Center for Biomolecular Science and Engineering, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA. mstanke@gwdg.de|Center for Biomolecular Science and Engineering, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA. mstanke@gwdg.de|Center for Biomolecular Science and Engineering, University of California Santa Cruz (UCSC), Santa Cruz, CA 95064, USA. mstanke@gwdg.de', 'United States|United States|United States|United States', 531, 'Alternative Splicing|Animals|DNA, Complementary|Expressed Sequence Tags|Humans|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btn013', '18218656', 'Computational annotation of protein coding genes in genomic DNA is a widely used and essential tool for analyzing newly sequenced genomes. However, current methods suffer from inaccuracy and do poorly with certain types of genes. Including additional sources of evidence of the existence and structure of genes can improve the quality of gene predictions. For many eukaryotic genomes, expressed sequence tags (ESTs) are available as evidence for genes. Related genomes that have been sequenced, annotated, and aligned to the target genome provide evidence of existence and structure of genes.'),
(73925, 2008, 'bio', 'Colorstock, SScolor, Ratón: RNA alignment visualization tools', 'Bendaña, Yuri R|Holmes, Ian H', 'Department of Bioengineering, UC Berkeley, Berkeley, CA, USA.|Department of Bioengineering, UC Berkeley, Berkeley, CA, USA.', 'United States|United States', 0, 'Base Sequence|Computational Biology|Molecular Sequence Data|RNA, Viral|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/btm635', '18218657', 'Interactive examination of RNA multiple alignments for covariant mutations is a useful step in non-coding RNA sequence analysis. We present three parallel implementations of an RNA visualization metaphor: Colorstock, a command-line script using ANSI terminal color, SScolor, a Perl script that generates static HTML pages, and Ratón, an AJAX web application generating dynamic HTML. Each tool can be used to color RNA alignments by secondary structure and to visually highlight compensatory mutations in stems.'),
(73926, 2008, 'bio', 'Jenti: an efficient tool for mining complex inbred genealogies', 'Falchi, Mario|Fuchsberger, Christian', 'Twin Research & Genetic Epidemiology Unit, Kings College London, UK. m.falchi@imperial.ac.uk|Twin Research & Genetic Epidemiology Unit, Kings College London, UK. m.falchi@imperial.ac.uk', 'United Kingdom|United Kingdom', 0, 'Genealogy and Heraldry|Information Storage and Retrieval|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm617', '18222918', 'An efficient tool for mining complex inbred genealogies that identify clusters of individuals sharing the same expected amount of relatedness is described. Additionally it allows for the reconstruction of sub-pedigrees suitable for genetic mapping in a systematic way.'),
(73927, 2008, 'bio', 'On distance and similarity in fold space', 'Sippl, Manfred J', 'Center of Applied Molecular Engineering, Division of Bioinformatics, Department of Molecular Biology, University of Salzburg, Hellbrunnerstr. 34, 5020 Salzburg, Austria. sippl@came.sbg.ac.at', 'Austria', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn040', '18227113', 'Metric information on similarities and distances in fold space is essential for quantitative work in structural bioinformatics and structural biology. Here we derive a suitable metric for protein structures from the fundamental axioms of similarity. Derivation of the metric also clarifies the relationship between the interrelated concepts of distance and similarity.'),
(73928, 2008, 'bio', 'SOAP: short oligonucleotide alignment program', 'Li, Ruiqiang|Li, Yingrui|Kristiansen, Karsten|Wang, Jun', 'Beijing Genomics Institute at Shenzhen, Shenzhen 518083, China.|Beijing Genomics Institute at Shenzhen, Shenzhen 518083, China.|Beijing Genomics Institute at Shenzhen, Shenzhen 518083, China.|Beijing Genomics Institute at Shenzhen, Shenzhen 518083, China.', 'China|China|China|China', 0, 'Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Amino Acid', 'Journal Article', '10.1093/bioinformatics/btn025', '18227114', 'We have developed a program SOAP for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The program is designed to handle the huge amounts of short reads generated by parallel sequencing using the new generation Illumina-Solexa sequencing technology. SOAP is compatible with numerous applications, including single-read or pair-end resequencing, small RNA discovery and mRNA tag sequence mapping. SOAP is a command-driven program, which supports multi-threaded parallel computing, and has a batch module for multiple query sets.'),
(73929, 2008, 'bio', 'Compressed indexing and local alignment of DNA', 'Lam, T W|Sung, W K|Tam, S L|Wong, C K|Yiu, S M', 'Department of Computer Science, University of Hong Kong, Hong Kong, China. twlam@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. twlam@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. twlam@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. twlam@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. twlam@cs.hku.hk', 'China|China|China|China|China', 80, 'Algorithms|Base Sequence|Chromosome Mapping|DNA|Data Compression|Genome, Human|Humans|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/btn032', '18227115', 'Recent experimental studies on compressed indexes (BWT, CSA, FM-index) have confirmed their practicality for indexing very long strings such as the human genome in the main memory. For example, a BWT index for the human genome (with about 3 billion characters) occupies just around 1 G bytes. However, these indexes are designed for exact pattern matching, which is too stringent for biological applications. The demand is often on finding local alignments (pairs of similar substrings with gaps allowed). Without indexing, one can use dynamic programming to find all the local alignments between a text T and a pattern P in O(|T||P|) time, but this would be too slow when the text is of genome scale (e.g. aligning a gene with the human genome would take tens to hundreds of hours). In practice, biologists use heuristic-based software such as BLAST, which is very efficient but does not guarantee to find all local alignments.'),
(73930, 2008, 'bio', 'TaxonGap: a visualization tool for intra- and inter-species variation among individual biomarkers', 'Slabbinck, B|Dawyndt, P|Martens, M|De Vos, P|De Baets, B', 'KERMIT, Research Unit Knowledge-based Systems, Ghent University, Coupure links 653, Ghent, Belgium. Bram.Slabbinck@UGent.be|KERMIT, Research Unit Knowledge-based Systems, Ghent University, Coupure links 653, Ghent, Belgium. Bram.Slabbinck@UGent.be|KERMIT, Research Unit Knowledge-based Systems, Ghent University, Coupure links 653, Ghent, Belgium. Bram.Slabbinck@UGent.be|KERMIT, Research Unit Knowledge-based Systems, Ghent University, Coupure links 653, Ghent, Belgium. Bram.Slabbinck@UGent.be|KERMIT, Research Unit Knowledge-based Systems, Ghent University, Coupure links 653, Ghent, Belgium. Bram.Slabbinck@UGent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Animals|Biomarkers|Computer Graphics|Gene Expression Profiling|Humans|Software|Species Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn031', '18227116', 'Selection of optimal biomarkers for the identification of different operational taxonomic units (OTUs) may be a hard and tedious task, especially when phylogenetic trees for multiple genes need to be compared. With TaxonGap we present a novel and easy-to-handle software tool that allows visual comparison of the discriminative power of multiple biomarkers for a set of OTUs. The compact graphical output allows for easy comparison and selection of individual biomarkers.'),
(73931, 2008, 'bio', 'Estimating large-scale signaling networks through nested effect models with intervention effects from microarray data', 'Fröhlich, Holger|Fellmann, Mark|Sültmann, Holger|Poustka, Annemarie|Beissbarth, Tim', 'German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de|German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de|German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de|German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de|German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. h.froehlich@dkfz-heidelberg.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Cell Line, Tumor|Computer Simulation|Estrogen Receptor alpha|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|RNA Interference|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btm634', '18227117', 'Targeted interventions using RNA interference in combination with the measurement of secondary effects with DNA microarrays can be used to computationally reverse engineer features of upstream non-transcriptional signaling cascades based on the nested structure of effects.'),
(73932, 2008, 'bio', 'Utility library for structural bioinformatics', 'Gront, Dominik|Kolinski, Andrzej', 'CUniversity of Warsaw, Faculty of Chemistry, Pasteura 1 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl|CUniversity of Warsaw, Faculty of Chemistry, Pasteura 1 02-093 Warsaw, Poland. dgront@chem.uw.edu.pl', 'Poland|Poland', 0, 'Computational Biology|Libraries|Software', 'Journal Article', '10.1093/bioinformatics/btm627', '18227118', 'In this Note we present a new software library for structural bioinformatics. The library contains programs, computing sequence- and profile-based alignments and a variety of structural calculations with user-friendly handling of various data formats. The software organization is very flexible. Algorithms are written in Java language and may be used by Java programs. Moreover the modules can be accessed from Jython (Python scripting language implemented in Java) scripts. Finally, the new version of BioShell delivers several utility programs that can do typical bioinformatics task from a command-line level. Availability The software is available for download free of charge from its website: http://bioshell.chem.uw.edu.pl. This website provides also numerous examples, code snippets and API documentation.'),
(73933, 2008, 'bio', 'Jane: suggesting journals, finding experts', 'Schuemie, Martijn J|Kors, Jan A', 'Department of Medical Informatics, Erasmus University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl|Department of Medical Informatics, Erasmus University Medical Center Rotterdam, 3000 CA, Rotterdam, The Netherlands. m.schuemie@erasmusmc.nl', 'Netherlands|Netherlands', 35, 'Information Storage and Retrieval|Internet|Publishing', 'Journal Article', '10.1093/bioinformatics/btn006', '18227119', 'With an exponentially growing number of articles being published every year, scientists can use some help in determining which journal is most appropriate for publishing their results, and which other scientists can be called upon to review their work. Jane (Journal/Author Name Estimator) is a freely available web-based application that, on the basis of a sample text (e.g. the title and abstract of a manuscript), can suggest journals and experts who have published similar articles.'),
(73934, 2008, 'bio', 'Phyutility: a phyloinformatics tool for trees, alignments and molecular data', 'Smith, Stephen A|Dunn, Casey W', 'Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA. stephen.smith@yale.edu|Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA. stephen.smith@yale.edu', 'United States|United States', 0, 'Computational Biology|Phylogeny|Sequence Alignment|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btm619', '18227120', 'Phyutility provides a set of phyloinformatics tools for summarizing and manipulating phylogenetic trees, manipulating molecular data and retrieving data from NCBI. Its simple command-line interface allows for easy integration into scripted analyses, and is able to handle large datasets with an integrated database.'),
(73935, 2008, 'bio', 'GenomeVx: simple web-based creation of editable circular chromosome maps', 'Conant, Gavin C|Wolfe, Kenneth H', 'Smurfit Institute of Genetics, Trinity College, University of Dublin, Dublin 2, Ireland. conantg@tcd.ie|Smurfit Institute of Genetics, Trinity College, University of Dublin, Dublin 2, Ireland. conantg@tcd.ie', 'Ireland|Ireland', 207, 'Chromosome Mapping|Computer Graphics|Documentation|Internet|Software|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/btm598', '18227121', 'We describe GenomeVx, a web-based tool for making editable, publication-quality, maps of mitochondrial and chloroplast genomes and of large plasmids. These maps show the location of genes and chromosomal features as well as a position scale. The program takes as input either raw feature positions or GenBank records. In the latter case, features are automatically extracted and colored, an example of which is given. Output is in the Adobe Portable Document Format (PDF) and can be edited by programs such as Adobe Illustrator.'),
(73936, 2008, 'bio', 'Prophinder: a computational tool for prophage prediction in prokaryotic genomes', 'Lima-Mendez, Gipsi|Van Helden, Jacques|Toussaint, Ariane|Leplae, Raphaël', 'Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, 1050 Bruxelles, Belgium. gipsi@scmbb.ulb.ac.be|Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, 1050 Bruxelles, Belgium. gipsi@scmbb.ulb.ac.be|Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, 1050 Bruxelles, Belgium. gipsi@scmbb.ulb.ac.be|Laboratoire de Bioinformatique des Génomes et des Réseaux (BiGRe), Université Libre de Bruxelles, 1050 Bruxelles, Belgium. gipsi@scmbb.ulb.ac.be', 'Belgium|Belgium|Belgium|Belgium', 130, 'Algorithms|Base Sequence|Chromosome Mapping|DNA, Viral|Genome, Viral|Molecular Sequence Data|Prokaryotic Cells|Prophages|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn043', '18238785', 'Prophinder is a prophage prediction tool coupled with a prediction database, a web server and web service. Predicted prophages will help to fill the gaps in the current sparse phage sequence space, which should cover an estimated 100 million species. Systematic and reliable predictions will enable further studies of prophages contribution to the bacteriophage gene pool and to better understand gene shuffling between prophages and phages infecting the same host.'),
(73937, 2008, 'bio', 'Biological pathway kinetic rate constants are scale-invariant', 'Grandison, Scott|Morris, Richard J', 'Department of Computational & Systems Biology, John Innes Centre, Norwich Research Park, Colney Lane, NR4 7UH Norwich, UK.|Department of Computational & Systems Biology, John Innes Centre, Norwich Research Park, Colney Lane, NR4 7UH Norwich, UK.', 'United Kingdom|United Kingdom', 9, 'Algorithms|Computer Simulation|Gene Expression Regulation|Kinetics|Metabolic Clearance Rate|Models, Biological|Numerical Analysis, Computer-Assisted|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/btn041', '18238786', 'Scale-free networks have had a profound impact in Biology. Network theory is now used routinely to visualize, navigate through, and help understand gene networks, protein-protein interactions, regulatory networks and metabolic pathways. Here we analyse the numerical rather than topological properties of biological networks and focus on the study of kinetic rate constants within pathways.'),
(73938, 2008, 'bio', 'Bayesian models based on test statistics for multiple hypothesis testing problems', 'Ji, Yuan|Lu, Yiling|Mills, Gordon B', 'Department of Bioinformatics and Computational Biology, The University of Texas, M. D. Anderson Cancer Center, Houston, TX 77030, USA. yuanji@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas, M. D. Anderson Cancer Center, Houston, TX 77030, USA. yuanji@mdanderson.org|Department of Bioinformatics and Computational Biology, The University of Texas, M. D. Anderson Cancer Center, Houston, TX 77030, USA. yuanji@mdanderson.org', 'United States|United States|United States', 0, 'Algorithms|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Models, Biological|Models, Statistical|Pattern Recognition, Automated|Research Design', 'Journal Article', '10.1093/bioinformatics/btn049', '18245123', 'We propose a Bayesian method for the problem of multiple hypothesis testing that is routinely encountered in bioinformatics research, such as the differential gene expression analysis. Our algorithm is based on modeling the distributions of test statistics under both null and alternative hypotheses. We substantially reduce the complexity of the process of defining posterior model probabilities by modeling the test statistics directly instead of modeling the full data. Computationally, we apply a Bayesian FDR approach to control the number of rejections of null hypotheses. To check if our model assumptions for the test statistics are valid for various bioinformatics experiments, we also propose a simple graphical model-assessment tool.'),
(73939, 2008, 'bio', 'ONTO-PERL: an API for supporting the development and analysis of bio-ontologies', 'Antezana, Eric|Egaña, Mikel|De Baets, Bernard|Kuiper, Martin|Mironov, Vladimir', 'Department of Plant Systems Biology, VIB, Department of Molecular Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. erick.antezana@psb.ugent.be|Department of Plant Systems Biology, VIB, Department of Molecular Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. erick.antezana@psb.ugent.be|Department of Plant Systems Biology, VIB, Department of Molecular Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. erick.antezana@psb.ugent.be|Department of Plant Systems Biology, VIB, Department of Molecular Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. erick.antezana@psb.ugent.be|Department of Plant Systems Biology, VIB, Department of Molecular Genetics, Ghent University, Technologiepark 927, 9052 Gent, Belgium. erick.antezana@psb.ugent.be', 'Belgium|Belgium|Belgium|Belgium|Belgium', 21, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Factual|Natural Language Processing|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn042', '18245124', 'Many biomedical ontologies use OBO or OWL as knowledge representation language. The rapid increase of such ontologies calls for adequate tools to facilitate their use. In particular, there is a pressing need to programmatically deal with such ontologies in many applications, including data integration, text mining, as well as semantic applications supporting translational research.'),
(73940, 2008, 'bio', 'De novo identification of highly diverged protein repeats by probabilistic consistency', 'Biegert, A|Söding, J', 'Department for Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany.|Department for Protein Evolution, Max Planck Institute for Developmental Biology, Spemannstr. 35, 72076 Tübingen, Germany.', 'Germany|Germany', 0, 'Algorithms|Amino Acid Sequence|Data Interpretation, Statistical|Molecular Sequence Data|Proteins|Repetitive Sequences, Amino Acid|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btn039', '18245125', 'An estimated 25% of all eukaryotic proteins contain repeats, which underlines the importance of duplication for evolving new protein functions. Internal repeats often correspond to structural or functional units in proteins. Methods capable of identifying diverged repeated segments or domains at the sequence level can therefore assist in predicting domain structures, inferring hypotheses about function and mechanism, and investigating the evolution of proteins from smaller fragments.'),
(73941, 2008, 'bio', 'Model-based Bayesian clustering (MBBC)', 'Joo, Yongsung|Booth, James G|Namkoong, Younghwan|Casella, George', 'Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32611, USA.|Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32611, USA.|Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32611, USA.|Biostatistics, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States|United States|United States', 4, 'Algorithms|Artificial Intelligence|Bayes Theorem|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Models, Biological|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Journal Article', '10.1093/bioinformatics/btn030', '18245126', 'The program MBBC 2.0 clusters time-course microarray data using a Bayesian product partition model.'),
(73942, 2008, 'bio', 'SVM-HUSTLE--an iterative semi-supervised machine learning approach for pairwise protein remote homology detection', 'Shah, Anuj R|Oehmen, Christopher S|Webb-Robertson, Bobbie-Jo', 'Scientific Data Management and Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, WA, USA.|Scientific Data Management and Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, WA, USA.|Scientific Data Management and Computational Biology and Bioinformatics, Pacific Northwest National Laboratory, Richland, WA, USA.', 'United States|United States|United States', 34, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/btn028', '18245127', 'As the amount of biological sequence data continues to grow exponentially we face the increasing challenge of assigning function to this enormous molecular parts list. The most popular approaches to this challenge make use of the simplifying assumption that similar functional molecules, or proteins, sometimes have similar composition, or sequence. However, these algorithms often fail to identify remote homologs (proteins with similar function but dissimilar sequence) which often are a significant fraction of the total homolog collection for a given sequence. We introduce a Support Vector Machine (SVM)-based tool to detect homology using semi-supervised iterative learning (SVM-HUSTLE) that identifies significantly more remote homologs than current state-of-the-art sequence or cluster-based methods. As opposed to building profiles or position specific scoring matrices, SVM-HUSTLE builds an SVM classifier for a query sequence by training on a collection of representative high-confidence training sets, recruits additional sequences and assigns a statistical measure of homology between a pair of sequences. SVM-HUSTLE combines principles of semi-supervised learning theory with statistical sampling to create many concurrent classifiers to iteratively detect and refine, on-the-fly, patterns indicating homology.'),
(73943, 2008, 'bio', 'Using flowViz to visualize flow cytometry data', 'Sarkar, D|Le Meur, N|Gentleman, R', 'Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA. dsarkar@fhcrc.org|Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA. dsarkar@fhcrc.org|Fred Hutchinson Cancer Research Center, 1100 Fairview Avenue North, Seattle, WA 98109, USA. dsarkar@fhcrc.org', 'United States|United States|United States', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Factual|Flow Cytometry|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn021', '18245128', 'Automated analysis of flow cytometry (FCM) data is essential for it to become successful as a high throughput technology. We believe that the principles of Trellis graphics can be adapted to provide useful visualizations that can aid such automation. In this article, we describe the R/Bioconductor package flowViz that implements such visualizations.'),
(73944, 2008, 'bio', 'Prediction of zinc-binding sites in proteins from sequence', 'Shu, Nanjiang|Zhou, Tuping|Hovmöller, Sven', 'Structural Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden.|Structural Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden.|Structural Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 84, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Metalloproteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Sequence Analysis, Protein|Zinc', 'Evaluation Studies', '10.1093/bioinformatics/btm618', '18245129', 'Motivated by the abundance, importance and unique functionality of zinc, both biologically and physiologically, we have developed an improved method for the prediction of zinc-binding sites in proteins from their amino acid sequences.'),
(73945, 2008, 'bio', 'LibSBML: an API library for SBML', 'Bornstein, Benjamin J|Keating, Sarah M|Jouraku, Akiya|Hucka, Michael', 'NASA Jet Propulsion Laboratory, Biological Network Modeling Center, California Institute of Technology, Pasadena, CA, USA.|NASA Jet Propulsion Laboratory, Biological Network Modeling Center, California Institute of Technology, Pasadena, CA, USA.|NASA Jet Propulsion Laboratory, Biological Network Modeling Center, California Institute of Technology, Pasadena, CA, USA.|NASA Jet Propulsion Laboratory, Biological Network Modeling Center, California Institute of Technology, Pasadena, CA, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Models, Biological|Programming Languages|Proteome|Signal Transduction|Software|Systems Biology|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn051', '18252737', 'LibSBML is an application programming interface library for reading, writing, manipulating and validating content expressed in the Systems Biology Markup Language (SBML) format. It is written in ISO C and C++, provides language bindings for Common Lisp, Java, Python, Perl, MATLAB and Octave, and includes many features that facilitate adoption and use of both SBML and the library. Developers can embed libSBML in their applications, saving themselves the work of implementing their own SBML parsing, manipulation and validation software.'),
(73946, 2008, 'bio', 'Prediction of recursive convex hull class assignments for protein residues', 'Stout, Michael|Bacardit, Jaume|Hirst, Jonathan D|Krasnogor, Natalio', 'Automated Scheduling, Optimization and Planning research group, School of Computer Science, University of Nottingham, UK.|Automated Scheduling, Optimization and Planning research group, School of Computer Science, University of Nottingham, UK.|Automated Scheduling, Optimization and Planning research group, School of Computer Science, University of Nottingham, UK.|Automated Scheduling, Optimization and Planning research group, School of Computer Science, University of Nottingham, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 40, 'Algorithms|Amino Acid Sequence|Amino Acids|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Protein Folding|Proteins|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btn050', '18252738', 'We introduce a new method for designating the location of residues in folded protein structures based on the recursive convex hull (RCH) of a point set of atomic coordinates. The RCH can be calculated with an efficient and parameterless algorithm.'),
(73947, 2008, 'bio', 'ITALICS: an algorithm for normalization and DNA copy number calling for Affymetrix SNP arrays', 'Rigaill, Guillem|Hupé, Philippe|Almeida, Anna|La Rosa, Philippe|Meyniel, Jean-Philippe|Decraene, Charles|Barillot, Emmanuel', 'Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.|Institut Curie, Service de Bioinformatique, INSERM, U900, CNRS UMR144, Institut Curie, Translational Research Department, 26 rue dUlm, Paris F-75248, France.', 'France|France|France|France|France|France|France', 22, 'Algorithms|Artificial Intelligence|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Gene Dosage|Gene Expression Profiling|Markov Chains|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Software', 'Comparative Study', '10.1093/bioinformatics/btn048', '18252739', 'Affymetrix SNP arrays can be used to determine the DNA copy number measurement of 11 000-500 000 SNPs along the genome. Their high density facilitates the precise localization of genomic alterations and makes them a powerful tool for studies of cancers and copy number polymorphism. Like other microarray technologies it is influenced by non-relevant sources of variation, requiring correction. Moreover, the amplitude of variation induced by non-relevant effects is similar or greater than the biologically relevant effect (i.e. true copy number), making it difficult to estimate non-relevant effects accurately without including the biologically relevant effect.'),
(73948, 2008, 'bio', 'Prediction of neuropeptide cleavage sites in insects', 'Southey, Bruce R|Sweedler, Jonathan V|Rodriguez-Zas, Sandra L', 'Department of Chemistry and Department of Animal Sciences, University of Illinois, Urbana, IL, USA.|Department of Chemistry and Department of Animal Sciences, University of Illinois, Urbana, IL, USA.|Department of Chemistry and Department of Animal Sciences, University of Illinois, Urbana, IL, USA.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Animals|Artificial Intelligence|Binding Sites|Computer Simulation|Enzymes|Insect Proteins|Insecta|Models, Chemical|Molecular Sequence Data|Neuropeptides|Pattern Recognition, Automated|Protein Binding|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/btn044', '18252740', 'The production of neuropeptides from their precursor proteins is the result of a complex series of enzymatic processing steps. Often, the annotation of new neuropeptide genes from sequence information outstrips biochemical assays and so bioinformatics tools can provide rapid information on the most likely peptides produced by a gene. Predicting the final bioactive neuropeptides from precursor proteins requires accurate algorithms to determine which locations in the protein are cleaved.'),
(73949, 2008, 'bio', 'Statistical search on the Semantic Web', 'Kobayashi, Norio|Toyoda, Tetsuro', 'Integrative Omics Research Team, Computational and Experimental Systems Biology Group, Genomic Sciences Center, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.|Integrative Omics Research Team, Computational and Experimental Systems Biology Group, Genomic Sciences Center, RIKEN, 1-7-22 Suehiro, Tsurumi, Yokohama, Kanagawa 230-0045, Japan.', 'Japan|Japan', 0, 'Abstracting and Indexing as Topic|Artificial Intelligence|Data Interpretation, Statistical|Information Storage and Retrieval|Internet|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Semantics', 'Evaluation Studies', '10.1093/bioinformatics/btn054', '18263641', 'Statistical analysis of links on the Semantic Web is important for various evaluation purposes such as quantifying an individuals scientific research output based on citation links. SPARQL has been proposed as a standardized query language for the Semantic Web and is intuitively understandable, however, it does not adequately support statistical evaluation of semantic links.'),
(73950, 2008, 'bio', 'Interactive visualization software for exploring phylogenetic trees and clades', 'Derthick, Mark', 'Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, PA, 15213, USA. mad@cs.cmu.edu', 'United States', 3, 'Algorithms|Animals|Chromosome Mapping|Computer Graphics|Computer Simulation|Humans|Models, Genetic|Phylogeny|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btn038', '18263642', 'The Summary Tree Explorer (STE) is a Java application for interactively exploring sets of phylogenetic trees using two coupled representations: a node-and-link diagram and a textual list of common clades. Selection, pruning, filtering or re-rooting in one representation is immediately reflected in the other. While summary trees are more effective at showing the relationship among clades, they can only show a consistent subset of those that appear in the textual list. Working with both representations mitigates the disadvantages of having to choose just one.'),
(73951, 2008, 'bio', 'ConFunc--functional annotation in the twilight zone', 'Wass, Mark N|Sternberg, Michael J E', 'Structural Bioinformatics Group, Biochemistry Building, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK.|Structural Bioinformatics Group, Biochemistry Building, Division of Molecular Biosciences, Imperial College London, London SW7 2AZ, UK.', 'United Kingdom|United Kingdom', 84, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/btn037', '18263643', 'The success of genome sequencing has resulted in many protein sequences without functional annotation. We present ConFunc, an automated Gene Ontology (GO)-based protein function prediction approach, which uses conserved residues to generate sequence profiles to infer function. ConFunc split sets of sequences identified by PSI-BLAST into sub-alignments according to their GO annotations. Conserved residues are identified for each GO term sub-alignment for which a position specific scoring matrix is generated. This combination of steps produces a set of feature (GO annotation) derived profiles from which protein function is predicted.'),
(73952, 2008, 'bio', 'Integrative analysis reveals the direct and indirect interactions between DNA copy number aberrations and gene expression changes', 'Lee, Hyunju|Kong, Sek Won|Park, Peter J', 'Harvard-Partners Center for Genetics and Genomics, Informatics Program, Childrens Hospital, Department of Cardiology, Childrens Hospital, Boston, MA, USA.|Harvard-Partners Center for Genetics and Genomics, Informatics Program, Childrens Hospital, Department of Cardiology, Childrens Hospital, Boston, MA, USA.|Harvard-Partners Center for Genetics and Genomics, Informatics Program, Childrens Hospital, Department of Cardiology, Childrens Hospital, Boston, MA, USA.', 'United States|United States|United States', 0, 'Computer Simulation|DNA Mutational Analysis|DNA, Neoplasm|Gene Dosage|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Neoplasm Proteins|Neoplasms|Systems Integration', 'Journal Article', '10.1093/bioinformatics/btn034', '18263644', 'DNA copy number aberrations (CNAs) and gene expression (GE) changes provide valuable information for studying chromosomal instability and its consequences in cancer. While it is clear that the structural aberrations and the transcript levels are intertwined, their relationship is more complex and subtle than initially suspected. Most studies so far have focused on how a CNA affects the expression levels of those genes contained within that CNA.');
