INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71810, 2005, 'bio', 'Quantile smoothing of array CGH data', 'Eilers, Paul H C|de Menezes, Renée X', 'Department of Medical Statistics, Leiden University Medical Centre PO Box 9604, 2300 RC, Leiden, The Netherlands. p.eilers@lumc.nl|Department of Medical Statistics, Leiden University Medical Centre PO Box 9604, 2300 RC, Leiden, The Netherlands. p.eilers@lumc.nl', 'Netherlands|Netherlands', 48, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Expression Profiling|In Situ Hybridization|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti148', '15572474', 'Plots of array Comparative Genomic Hybridization (CGH) data often show special patterns: stretches of constant level (copy number) with sharp jumps between them. There can also be much noise. Classic smoothing algorithms do not work well, because they introduce too much rounding. To remedy this, we introduce a fast and effective smoothing algorithm based on penalized quantile regression. It can compute arbitrary quantile curves, but we concentrate on the median to show the trend and the lower and upper quartile curves showing the spread of the data. Two-fold cross-validation is used for optimizing the weight of the penalties.'),
(71811, 2005, 'bio', 'MapLinker: a software tool that aids physical map-linked whole genome shotgun assembly', 'Xu, Jian|Gordon, Jeffrey I', 'Center for Genome Sciences and Department of Molecular Biology and Pharmacology, Washington University School of Medicine, St. Louis, MO 63108, USA. jxu@watson.wustl.edu|Center for Genome Sciences and Department of Molecular Biology and Pharmacology, Washington University School of Medicine, St. Louis, MO 63108, USA. jxu@watson.wustl.edu', 'United States|United States', 0, 'Algorithms|Chromosome Mapping|Cloning, Molecular|Computer Graphics|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti122', '15572475', 'MapLinker is an analysis tool, as well as a browsing interface, that facilitates integration of whole genome sequence assembly with a clone-based physical map. Using the locations of sequence markers on the physical map, MapLinker generates a tentative sequence map of the genome that serves to verify the map and to guide genome-wide finishing.'),
(71812, 2005, 'bio', 'Metabolic pathway analysis web service (Pathway Hunter Tool at CUBIC)', 'Rahman, S A|Advani, P|Schunk, R|Schrader, R|Schomburg, Dietmar', 'Cologne University BioInformatics Center (CUBIC) and Institute of Biochemistry, Zülpicher Strasse 47, 50674 Köln, Germany.|Cologne University BioInformatics Center (CUBIC) and Institute of Biochemistry, Zülpicher Strasse 47, 50674 Köln, Germany.|Cologne University BioInformatics Center (CUBIC) and Institute of Biochemistry, Zülpicher Strasse 47, 50674 Köln, Germany.|Cologne University BioInformatics Center (CUBIC) and Institute of Biochemistry, Zülpicher Strasse 47, 50674 Köln, Germany.|Cologne University BioInformatics Center (CUBIC) and Institute of Biochemistry, Zülpicher Strasse 47, 50674 Köln, Germany.', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Databases, Factual|Energy Metabolism|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation|Internet|Models, Biological|Protein Interaction Mapping|Signal Transduction|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti116', '15572476', 'Pathway Hunter Tool (PHT), is a fast, robust and user-friendly tool to analyse the shortest paths in metabolic pathways. The user can perform shortest path analysis for one or more organisms or can build virtual organisms (networks) using enzymes. Using PHT, the user can also calculate the average shortest path (Jungnickel, 2002 Graphs, Network and Algorithm. Springer-Verlag, Berlin), average alternate path and the top 10 hubs in the metabolic network. The comparative study of metabolic connectivity and observing the cross talk between metabolic pathways among various sequenced genomes is possible.'),
(71813, 2005, 'bio', 'LongSAGE analysis revealed the presence of a large number of novel antisense genes in the mouse genome', 'Wahl, Matthias B|Heinzmann, Ulrich|Imai, Kenji', 'Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.', 'Germany|Germany|Germany', 13, 'Algorithms|Animals|Chromosome Mapping|DNA, Antisense|Databases, Genetic|Gene Expression Profiling|Mice|Mice, Inbred C57BL|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti205', '15585522', 'Despite the increasing notions of the functional importance of antisense transcripts in gene regulation, the genome-wide overview on the ontology of antisense genes has not been obtained. Therefore, we tried to find novel antisense genes genome-wide by using our LongSAGE dataset of 202 015 tags (consisting of 41 718 unique tags), experimentally generated from mouse embryonic tail libraries.'),
(71814, 2005, 'bio', 'Convergent evolution of domain architectures (is rare)', 'Gough, Julian', 'RIKEN Genomic Sciences Centre, 1-7-22 Suehiro-cho, Tsurumi-ku, Yokohama 230-0045, Japan. gough@supfam.org', 'Japan', 0, 'Conserved Sequence|Evolution, Molecular|Genetic Variation|Phylogeny|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti204', '15585523', 'In this paper, we shall examine the evolution of domain architectures across 62 genomes of known phylogeny including all kingdoms of life. We look in particular at the possibility of convergent evolution, with a view to determining the extent to which the architectures observed in the genomes are due to functional necessity or evolutionary descent. We used domains of known structure, because from this and other information we know their evolutionary relationships. We use a range of methods including phylogenetic grouping, sequence similarity/alignment, mutation rates and comparative genomics to approach this difficult problem from several angles.'),
(71815, 2005, 'bio', 'Porter: a new, accurate server for protein secondary structure prediction', 'Pollastri, Gianluca|McLysaght, Aoife', 'Computer Science Department, University College Dublin, Belfield, Dublin 4, Ireland. gianluca.pollastri@ucd.ie|Computer Science Department, University College Dublin, Belfield, Dublin 4, Ireland. gianluca.pollastri@ucd.ie', 'Ireland|Ireland', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Internet|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bti203', '15585524', 'Porter is a new system for protein secondary structure prediction in three classes. Porter relies on bidirectional recurrent neural networks with shortcut connections, accurate coding of input profiles obtained from multiple sequence alignments, second stage filtering by recurrent neural networks, incorporation of long range information and large-scale ensembles of predictors. Porters accuracy, tested by rigorous 5-fold cross-validation on a large set of proteins, exceeds 79%, significantly above a copy of the state-of-the-art SSpro server, better than any system published to date.'),
(71816, 2005, 'bio', 'CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs', 'Ao, S I|Yip, Kevin|Ng, Michael|Cheung, David|Fong, Pui-Yee|Melhado, Ian|Sham, Pak C', 'Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.|Department of Mathematics, The University of Hong Kong, Pokfulam, Hong Kong.', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong|Hong Kong', 60, 'Algorithms|Chromosome Mapping|Cluster Analysis|DNA Mutational Analysis|Expressed Sequence Tags|Genetics, Population|Genome, Human|Humans|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Software', 'Journal Article', '10.1093/bioinformatics/bti201', '15585525', 'Cluster and set-cover algorithms are developed to obtain a set of tag single nucleotide polymorphisms (SNPs) that can represent all the known SNPs in a chromosomal region, subject to the constraint that all SNPs must have a squared correlation R2>C with at least one tag SNP, where C is specified by the user.'),
(71817, 2005, 'bio', 'Support vector machines for separation of mixed plant-pathogen EST collections based on codon usage', 'Friedel, Caroline C|Jahn, Katharina H V|Sommer, Selina|Rudd, Stephen|Mewes, Hans W|Tetko, Igor V', 'Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de|Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de|Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de|Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de|Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de|Institut fuer Informatik, Ludwig-Maximilians-Universitaet Muenchen, Oettingenstrasse 67, 80538 Muenchen, Germany. friedel@informatik.uni-muenchen.de', 'Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Artificial Intelligence|Ascomycota|Chromosome Mapping|Codon|DNA, Plant|Hordeum|Host-Parasite Interactions|Pattern Recognition, Automated|Plants|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti200', '15585526', 'Discovery of host and pathogen genes expressed at the plant-pathogen interface often requires the construction of mixed libraries that contain sequences from both genomes. Sequence identification requires high-throughput and reliable classification of genome origin. When using single-pass cDNA sequences difficulties arise from the short sequence length, the lack of sufficient taxonomically relevant sequence data in public databases and ambiguous sequence homology between plant and pathogen genes.'),
(71818, 2005, 'bio', 'OLIN: optimized normalization, visualization and quality testing of two-channel microarray data', 'Futschik, Matthias E|Crompton, Toni', 'Institute for Theoretical Biology, Humboldt-Universität, Invalidenstrasse 43, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de|Institute for Theoretical Biology, Humboldt-Universität, Invalidenstrasse 43, 10115 Berlin, Germany. m.futschik@biologie.hu-berlin.de', 'Germany|Germany', 32, 'Algorithms|Computer Graphics|Gene Expression Profiling|Internet|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Regression Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti199', '15585527', 'Microarray data are generated in complex experiments and frequently compromised by a variety of systematic errors. Subsequent data normalization aims to correct these errors. Although several normalization methods have recently been proposed, they frequently fail to account for the variability of systematic errors within and between microarray experiments. However, optimal adjustment of normalization procedures to the underlying data structure is crucial for the efficiency of normalization. To overcome this restriction of current methods, we have developed two normalization schemes based on iterative local regression combined with model selection. The schemes have been demonstrated to improve considerably the quality of normalization. They are implemented in a freely available R package. Additionally, functions for visualization and detection of systematic errors in microarray data have been incorporated in the software package. A graphical user interface is also available.'),
(71819, 2005, 'bio', 'Characterizing the dynamic connectivity between genes by variable parameter regression and Kalman filtering based on temporal gene expression data', 'Cui, Qinghua|Liu, Bing|Jiang, Tianzi|Ma, Songde', 'National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, Peoples Republic of China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, Peoples Republic of China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, Peoples Republic of China.|National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100080, Peoples Republic of China.', 'China|China|China|China', 6, 'Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Proteins|Regression Analysis|Signal Transduction|Statistics as Topic|Systems Theory|Time Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti197', '15585528', 'One popular method for analyzing functional connectivity between genes is to cluster genes with similar expression profiles. The most popular metrics measuring the similarity (or dissimilarity) among genes include Pearsons correlation, linear regression coefficient and Euclidean distance. As these metrics only give some constant values, they can only depict a stationary connectivity between genes. However, the functional connectivity between genes usually changes with time. Here, we introduce a novel insight for characterizing the relationship between genes and find out a proper mathematical model, variable parameter regression and Kalman filtering to model it.'),
(71820, 2005, 'bio', 'RBT--a tool for building refined Buneman trees', 'Besenbacher, Søren|Mailund, Thomas|Westh-Nielsen, Lasse|Pedersen, Christian N S', 'Bioinformatics Research Center, Department of Computer Science, University of Aarhus, Høegh-Guldbergs Gade 10, Building 090, DK-8000 Arhus C, Denmark. besen@daimi.au.dk|Bioinformatics Research Center, Department of Computer Science, University of Aarhus, Høegh-Guldbergs Gade 10, Building 090, DK-8000 Arhus C, Denmark. besen@daimi.au.dk|Bioinformatics Research Center, Department of Computer Science, University of Aarhus, Høegh-Guldbergs Gade 10, Building 090, DK-8000 Arhus C, Denmark. besen@daimi.au.dk|Bioinformatics Research Center, Department of Computer Science, University of Aarhus, Høegh-Guldbergs Gade 10, Building 090, DK-8000 Arhus C, Denmark. besen@daimi.au.dk', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Animals|Biological Evolution|Computer Simulation|Genetic Variation|Humans|Kinetics|Models, Genetic|Models, Statistical|Phylogeny|Software|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bti195', '15585529', 'We have developed a tool implementing an efficient algorithm for refined Buneman tree reconstruction. The algorithm--which has the same complexity as the neighbour-joining method and the (plain) Buneman tree construction--enables refined Buneman tree reconstruction on large taxa sets.'),
(71821, 2005, 'bio', 'A score matrix to reveal the hidden links in glycans', 'Aoki, Kiyoko F|Mamitsuka, Hiroshi|Akutsu, Tatsuya|Kanehisa, Minoru', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.', 'Japan|Japan|Japan|Japan', 31, 'Algorithms|Carbohydrate Conformation|Carbohydrate Sequence|Conserved Sequence|Databases, Factual|Molecular Sequence Data|Pattern Recognition, Automated|Polysaccharides|Sequence Alignment|Sequence Analysis|Sequence Homology|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti193', '15585530', 'Glycans are the third major class of biomolecules following DNA and proteins. They are extremely vital for the functioning of multicellular organisms. However, comparing the fast development of sequence analysis techniques, informatics work on glycans have a long way to go. Alignment algorithms for glycan tree structures are one of the foremost concerns. In addition, the statistical analysis of these algorithms in terms of biological significance needs to be addressed.'),
(71822, 2005, 'bio', 'HykGene: a hybrid approach for selecting marker genes for phenotype classification using microarray gene expression data', 'Wang, Yuhang|Makedon, Fillia S|Ford, James C|Pearlman, Justin', 'Department of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755-3510, USA. wyh@cs.dartmouth.edu|Department of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755-3510, USA. wyh@cs.dartmouth.edu|Department of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755-3510, USA. wyh@cs.dartmouth.edu|Department of Computer Science, Dartmouth College, 6211 Sudikoff Laboratory, Hanover, NH 03755-3510, USA. wyh@cs.dartmouth.edu', 'United States|United States|United States|United States', 150, 'Algorithms|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Genetic Markers|Models, Genetic|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Phenotype|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti192', '15585531', 'Recent studies have shown that microarray gene expression data are useful for phenotype classification of many diseases. A major problem in this classification is that the number of features (genes) greatly exceeds the number of instances (tissue samples). It has been shown that selecting a small set of informative genes can lead to improved classification accuracy. Many approaches have been proposed for this gene selection problem. Most of the previous gene ranking methods typically select 50-200 top-ranked genes and these genes are often highly correlated. Our goal is to select a small set of non-redundant marker genes that are most relevant for the classification task.'),
(71823, 2005, 'bio', 'TERMINUS--Telomeric End-Read Mining IN Unassembled Sequences', 'Li, Weixi|Rehmeyer, Cathryn J|Staben, Chuck|Farman, Mark L', 'Department of Biological Sciences, University of Kentucky, Lexington, KY 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, KY 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, KY 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, KY 40546, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Sequence Analysis, DNA|Software|Telomere|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti181', '15585532', 'TERMINUS is a set of tools to map telomeres on draft sequences of whole genome shotgun sequencing projects. It mines raw sequence reads (from a trace archive) for telomeric reads, assembles them into contigs representing individual chromosome ends and BLASTs the resulting consensus sequences against the genome assembly to identify telomere-proximal genomic contigs. Finally, it estimates the sizes of telomeric gaps and identifies clones for gap closure. TERMINUS is implemented as a set of Perl scripts that requires two sets of inputs: the NCBI Trace Archive files for a given genome project, and ancillary genome assembly information. Results are output in spreadsheets containing information that facilitates manual validation.'),
(71824, 2005, 'bio', 'Cysteine separations profiles on protein sequences infer disulfide connectivity', 'Zhao, East|Liu, Hsuan-Liang|Tsai, Chi-Hung|Tsai, Huai-Kuang|Chan, Chen-hsiung|Kao, Cheng-Yan', 'Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.|Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.|Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.|Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.|Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.|Bioinformatics Laboratory, Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Rd., Taipei, Taiwan 106.', '-|-|-|-|-|-', 37, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Cysteine|Databases, Protein|Disulfides|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti179', '15585533', 'Disulfide bonds play an important role in protein folding. A precise prediction of disulfide connectivity can strongly reduce the conformational search space and increase the accuracy in protein structure prediction. Conventional disulfide connectivity predictions use sequence information, and prediction accuracy is limited. Here, by using an alternative scheme with global information for disulfide connectivity prediction, higher performance is obtained with respect to other approaches.'),
(71825, 2005, 'bio', 'Bayesian models for the analysis of genetic structure when populations are correlated', 'Fu, Rongwei|Dey, Dipak K|Holsinger, Kent E', 'Department of Statistics, U-4120, University of Connecticut, Storrs, CT 06269-4120, USA. fur@ohsu.edu|Department of Statistics, U-4120, University of Connecticut, Storrs, CT 06269-4120, USA. fur@ohsu.edu|Department of Statistics, U-4120, University of Connecticut, Storrs, CT 06269-4120, USA. fur@ohsu.edu', 'United States|United States|United States', 15, 'Bayes Theorem|Computer Simulation|DNA Mutational Analysis|Gene Expression Profiling|Gene Frequency|Genetic Variation|Genetics, Population|Genome, Human|Humans|Models, Genetic|Models, Statistical|Phenotype|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bti178', '15585534', 'Population allele frequencies are correlated when populations have a shared history or when they exchange genes. Unfortunately, most models for allele frequency and inference about population structure ignore this correlation. Recent analytical results show that among populations, correlations can be very high, which could affect estimates of population genetic structure. In this study, we propose a mixture beta model to characterize the allele frequency distribution among populations. This formulation incorporates the correlation among populations as well as extending the model to data with different clusters of populations.'),
(71826, 2005, 'bio', 'Statistical detection of chromosomal homology using shared-gene density alone', 'Hampson, S E|Gaut, B S|Baldi, P', 'School of Information and Computer Science, University of California, Irvine, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, Irvine, CA 92697, USA.|School of Information and Computer Science, University of California, Irvine, Irvine, CA 92697, USA.', 'United States|United States|United States', 10, 'Algorithms|Base Sequence|Chromosome Mapping|Cluster Analysis|Conserved Sequence|Data Interpretation, Statistical|Genome, Plant|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Zea mays', 'Comparative Study', '10.1093/bioinformatics/bti168', '15585535', 'Over evolutionary time, various processes including point mutations and insertions, deletions and inversions of variable sized segments progressively degrade the homology of duplicated chromosomal regions making identification of the homologous regions correspondingly difficult. Existing algorithms that attempt to detect homology are based on shared-gene density and colinearity and possibly also strand information.'),
(71827, 2005, 'bio', 'Autoregressive modeling of analytical sensor data can yield classifiers in the predictor coefficient parameter space', 'Krebs, Melissa D|Tingley, Robert D|Zeskind, Julie E|Kang, Joung-Mo|Holmboe, Maria E|Davis, Cristina E', 'Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.|Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.|Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.|Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.|Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.|Mechanical and Instruments Division, Bioengineering Group, Cambridge, MA 02139, USA.', 'United States|United States|United States|United States|United States|United States', 6, 'Algorithms|Bacterial Proteins|Blood Proteins|Chromatography, Gas|Humans|Models, Biological|Models, Chemical|Pattern Recognition, Automated|Regression Analysis|Transducers', 'Comparative Study', '10.1093/bioinformatics/bti160', '15585536', 'The analysis of chromatographic data resulting from complex chemical mixtures is challenging. Components may co-elute, causing their signals to overlap. An algorithm that will increase the signal-to-noise ratio so compounds present in low abundance can be better distinguished from noise is useful in this type of analysis. The autoregressive (AR) filter offers the advantage of smoothing chromatograms to increase this ratio, while also offering data compression and increased resolution. Furthermore, this filter can be useful for classification, as the roots of the predictor coefficient vectors represent features present in the data and can therefore be used for pattern recognition. In this paper, we present a novel method for applying AR filtering to chromatogram data. We show that the AR filter outperforms the Savitzky-Golay filter for smoothing noise while retaining important information within chromatograms, and also that AR correlation coefficients have the potential to be used to classify chromatogram data into groups.'),
(71828, 2005, 'bio', 'In silico fine-mapping: narrowing disease-associated loci by intergenomics', 'Serrano-Fernández, Pablo|Ibrahim, Saleh M|Koczan, Dirk|Zettl, Uwe K|Möller, Steffen', 'Institute of Immunology, University of Rostock, Schillingallee 70, D-18057 Rostock, Germany. serrano@pzr.uni-rostock.de|Institute of Immunology, University of Rostock, Schillingallee 70, D-18057 Rostock, Germany. serrano@pzr.uni-rostock.de|Institute of Immunology, University of Rostock, Schillingallee 70, D-18057 Rostock, Germany. serrano@pzr.uni-rostock.de|Institute of Immunology, University of Rostock, Schillingallee 70, D-18057 Rostock, Germany. serrano@pzr.uni-rostock.de|Institute of Immunology, University of Rostock, Schillingallee 70, D-18057 Rostock, Germany. serrano@pzr.uni-rostock.de', 'Germany|Germany|Germany|Germany|Germany', 2, 'Animals|Chromosome Mapping|Genetic Predisposition to Disease|Genetic Testing|Genomics|Humans|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti209', '15591355', 'Genetic linkage and association studies define quantitative trait loci (QTLs) and susceptibility loci (SLs) that influence the phenotype of polygenic traits. A web-accessible application was created to identify intergenomic consensuses to fine map QTLs and SLs in silico and select particularly promising candidate genes for such traits. Furthermore, this approach offers an empirical evaluation of animal models for their applicability to the study of human traits.'),
(71829, 2005, 'bio', 'LongSAGE analysis significantly improves genome annotation: identifications of novel genes and alternative transcripts in the mouse', 'Wahl, Matthias B|Heinzmann, Ulrich|Imai, Kenji', 'Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.|Institute of Developmental Genetics, GSF-National Research Center for Environment and Health, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany.', 'Germany|Germany|Germany', 12, 'Algorithms|Alternative Splicing|Animals|Chromosome Mapping|DNA, Antisense|Databases, Genetic|Exons|Gene Expression Profiling|Mice|Mice, Inbred C57BL|Sequence Alignment|Sequence Analysis, DNA|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti207', '15591356', 'Owing to its increased tag length, LongSAGE tags are expected to be more reliable in direct assignment to genome sequences. Therefore, we evaluated the use of LongSAGE data in genome annotation by using our LongSAGE dataset of 202 015 tags (consisting of 41 718 unique tags), experimentally generated from mouse embryonic tail libraries.'),
(71830, 2005, 'bio', 'Highly specific and accurate selection of siRNAs for high-throughput functional assays', 'Santoyo, Javier|Vaquerizas, Juan M|Dopazo, Joaquín', 'Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO) and Functional Genomics Node, INB, Melchor Fernández Almagro, 3, 28029 Madrid, Spain.|Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO) and Functional Genomics Node, INB, Melchor Fernández Almagro, 3, 28029 Madrid, Spain.|Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO) and Functional Genomics Node, INB, Melchor Fernández Almagro, 3, 28029 Madrid, Spain.', 'Spain|Spain|Spain', 41, 'Algorithms|Base Sequence|Gene Silencing|Molecular Sequence Data|RNA, Small Interfering|Sequence Alignment|Sequence Analysis, RNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti196', '15591357', 'Small interfering RNA (siRNA) is widely used in functional genomics to silence genes by decreasing their expression to study the resulting phenotypes. The possibility of performing large-scale functional assays by gene silencing accentuates the necessity of a software capable of the high-throughput design of highly specific siRNA. The main objective sought was the design of a large number of siRNAs with appropriate thermodynamic properties and, especially, high specificity. Since all the available procedures require, to some extent, manual processing of the results to guarantee specific results, specificity constitutes to date, the major obstacle to the complete automation of all the steps necessary for the selection of optimal candidate siRNAs.'),
(71831, 2005, 'bio', 'HESAS: HERVs Expression and Structure Analysis System', 'Kim, Tae-Hyung|Jeon, Yeo-Jin|Kim, Woo-Yeon|Kim, Heui-Soo', 'PBBRC, Interdisciplinary Research Program of Bioinformatics, College of Natural Sciences, Pusan National University, Busan 609-735, Korea.|PBBRC, Interdisciplinary Research Program of Bioinformatics, College of Natural Sciences, Pusan National University, Busan 609-735, Korea.|PBBRC, Interdisciplinary Research Program of Bioinformatics, College of Natural Sciences, Pusan National University, Busan 609-735, Korea.|PBBRC, Interdisciplinary Research Program of Bioinformatics, College of Natural Sciences, Pusan National University, Busan 609-735, Korea.', '-|-|-|-', 0, 'Algorithms|Chromosome Mapping|Database Management Systems|Databases, Nucleic Acid|Endogenous Retroviruses|Expressed Sequence Tags|Genome, Human|Humans|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti194', '15591358', 'HESAS (HERVs Expression and Structure Analysis System) database was developed to understand the human endogenous retroviruses (HERVs) that have an effect on the expression of human functional genes. The database products are generated by the exon-based expressed sequence tag clustering and reconstructing of partial HERV structures that result from various mutations during primate evolution. The expression types were classified according to the existence of splicing, transcriptional start and polyadenylation signal sites. The database currently contains HERV information on 26,981 human genes of exon-intron structure. The HERV elements were inserted into 17,317 of these genes and linked to expression with 898 genes.'),
(71832, 2005, 'bio', 'Statistical evaluation and comparison of a pairwise alignment algorithm that a priori assigns the number of gaps rather than employing gap penalties', 'Nozaki, Yasuyuki|Bellgard, Matthew', 'Centre for Bioinformatics and Biological Computing, Murdoch University, Murdoch, WA 6150, Australia.|Centre for Bioinformatics and Biological Computing, Murdoch University, Murdoch, WA 6150, Australia.', 'Australia|Australia', 0, 'Algorithms|Conserved Sequence|Data Interpretation, Statistical|Models, Chemical|Models, Genetic|Models, Statistical|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/bti198', '15591359', 'Although pairwise sequence alignment is essential in comparative genomic sequence analysis, it has proven difficult to precisely determine the gap penalties for a given pair of sequences. A common practice is to employ default penalty values. However, there are a number of problems associated with using gap penalties. First, alignment results can vary depending on the gap penalties, making it difficult to explore appropriate parameters. Second, the statistical significance of an alignment score is typically based on a theoretical model of non-gapped alignments, which may be misleading. Finally, there is no way to control the number of gaps for a given pair of sequences, even if the number of gaps is known in advance.'),
(71833, 2003, 'bio', 'Intergenic sequence inspector: searching and identifying bacterial RNAs', 'Pichon, Christophe|Felden, Brice', 'Université de Rennes I, UPRES Jeune Equipe 2311, 35043 Rennes, France.|Université de Rennes I, UPRES Jeune Equipe 2311, 35043 Rennes, France.', 'France|France', 36, 'DNA, Intergenic|Internet|Introns|RNA, Bacterial|Software|Software Design', 'Journal Article', '10.1093/bioinformatics/btg235', '15593399', 'Intergenic Sequence Inspector (ISI) is a program that helps in identifying bacterial ribonucleic acids (RNAs). It automatically extracts, selects and visualizes candidate intergenic regions (IGRs) that bear conservations between phylogenetically related species, displaying sequence and structural signatures of RNA genes encompassing putative promoters, terminators, RNA secondary structure predictions and the G+C percent of the selected sequences. ISI is intentionally modular to analyze various bacterial genomes according to their intrinsic specificities and to the available data. ISI provides a sum of information to the user who can evaluate whether or not an IGR is susceptible to express RNAs.'),
(71834, 2003, 'bio', 'Detecting putative orthologs', 'Wall, D P|Fraser, H B|Hirsh, A E', 'Department of Biological Sciences, Stanford University, CA 94305, USA. dpwall@stanford.edu|Department of Biological Sciences, Stanford University, CA 94305, USA. dpwall@stanford.edu|Department of Biological Sciences, Stanford University, CA 94305, USA. dpwall@stanford.edu', 'United States|United States|United States', 0, 'Algorithms|Candida albicans|Evolution, Molecular|Likelihood Functions|Saccharomyces cerevisiae|Sequence Alignment', 'Journal Article', '10.1093/bioinformatics/btg213', '15593400', 'We developed an algorithm that improves upon the common procedure of taking reciprocal best blast hits(rbh) in the identification of orthologs. The method-reciprocal smallest distance algorithm (rsd)-relies on global sequence alignment and maximum likelihood estimation of evolutionary distances to detect orthologs between two genomes. rsd finds many putative orthologs missed by rbh because it is less likely than rbh to be misled by the presence of a close paralog.'),
(71835, 2003, 'bio', 'GFPE: gene-finding program evaluation', 'Wang, Jian|Kraemer, Eileen', 'Computer Science Department, The University of Georgia, Athens, GA 30602, USA.|Computer Science Department, The University of Georgia, Athens, GA 30602, USA.', 'Georgia|Georgia', 2, 'Computational Biology|Databases, Genetic|Gene Expression Profiling|Genomics|Internet|Sequence Analysis|Software|Software Validation', 'Evaluation Studies', '10.1093/bioinformatics/btg216', '15593401', 'Gene-finding program evaluation (GFPE) is a set of Java classes for evaluating gene-finding programs. A command-line interface is also provided. Inputs to the program include the sequence data (in FASTA format), annotations of actual sequence features, and annotations of predicted sequence features. Annotation files are in the General Feature Format promoted by the Sanger center. GFPE calculates a number of metrics of accuracy of predictions at three levels:the coding level, the exon level, and the protein level.'),
(71836, 2003, 'bio', 'CGH-Plotter: MATLAB toolbox for CGH-data analysis', 'Autio, Reija|Hautaniemi, Sampsa|Kauraniemi, Päivikki|Yli-Harja, Olli|Astola, Jaakko|Wolf, Maija|Kallioniemi, Anne', 'Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.|Institute of Signal Processing, Tampere University of Technology, 33101 Finland.', 'Finland|Finland|Finland|Finland|Finland|Finland|Finland', 0, 'Cluster Analysis|Data Display|Data Interpretation, Statistical|Hybridization, Genetic|Internet|Protein Array Analysis|Research Design|Signal Processing, Computer-Assisted|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg230', '15593402', 'CGH-Plotter is a MATLAB toolbox with a graphical user interface for the analysis of comparative genomic hybridization (CGH) microarray data. CGH-Plotter provides a tool for rapid visualization of CGH-data according to the locations of the genes along the genome. In addition, the CGH-Plotter identifies regions of amplifications and deletions, using k-means clustering and dynamic programming. The application offers a convenient way to analyze CGH-data and can also be applied for the analysis of cDNA microarray expression data. CGH-Plotter toolbox is platform independent and requires MATLAB 6.1 or higher to operate.'),
(71837, 2003, 'bio', 'SignalViewer: analyzing microarray images', 'Laws, R J|Bergemann, T L|Quiaoit, F|Zhao, L P', 'Quantitative Genetic Epidemiology, Fred Hutchinson Cancer Research Center, Seattle 98109-1024, USA.|Quantitative Genetic Epidemiology, Fred Hutchinson Cancer Research Center, Seattle 98109-1024, USA.|Quantitative Genetic Epidemiology, Fred Hutchinson Cancer Research Center, Seattle 98109-1024, USA.|Quantitative Genetic Epidemiology, Fred Hutchinson Cancer Research Center, Seattle 98109-1024, USA.', 'United States|United States|United States|United States', 0, 'Artifacts|Data Display|Image Processing, Computer-Assisted|Internet|Microarray Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg208', '15593405', 'Microarray technology is now routinely used to monitor genome-wide expression profiles. However, current microarray imaging and analysis packages typically require manual intervention and assumptions on alignments. Unfortunately, limitations and assumptions are typically undisclosed and methods are not published. To facilitate exploration of image data, we developed SignalViewer. This paper presents a description of the application.'),
(71838, 2003, 'bio', 'FindGDPs: identification of primers for labeling microbial transcriptomes for DNA microarray analysis', 'Blick, Robert J|Revel, Andrew T|Hansen, Eric J', 'Department of Microbiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9048, USA.|Department of Microbiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9048, USA.|Department of Microbiology, University of Texas Southwestern Medical Center, Dallas, TX 75390-9048, USA.', 'United States|United States|United States', 7, 'Algorithms|Base Sequence|DNA Primers|DNA, Bacterial|Genetics, Microbial|Genome Components|Genome, Bacterial|Internet|Oligonucleotide Array Sequence Analysis|Open Reading Frames|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg218', '15593406', 'FindGDPs is a program that uses a greedy algorithm to quickly identify a set of genome-directed primers that specifically anneal to all of the open reading frames ina genome and that do not exhibit full-length complementarity to the members of another user-supplied set of nucleotide sequences.'),
(71839, 2003, 'bio', 'ESTAP--an automated system for the analysis of EST data', 'Mao, Chunhong|Cushman, John C|May, Gregory D|Weller, Jennifer W', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. chmao@vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. chmao@vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. chmao@vt.edu|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA. chmao@vt.edu', 'United States|United States|United States|United States', 0, 'Base Sequence|Data Interpretation, Statistical|Expressed Sequence Tags|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg205', '15593407', 'The EST Analysis Pipeline (ESTAP) is a set of analytical procedures that automatically verify, cleanse, store and analyze ESTs generated on high-throughput platforms. It uses a relational database to store sequence data and analysis results, which facilitates both the search for specific information and statistical analysis. ESTAP provides for easy viewing of the original and cleansed data, as well as the analysis results via a Web browser. It also allows the data owner to submit selected sequences to dbEST in a semi-automated fashion.'),
(71840, 2003, 'bio', 'ProSAT: functional annotation of protein 3D structures', 'Gabdoulline, Razif R|Hoffmann, René|Leitner, Florian|Wade, Rebecca C', 'European Media Laboratory, 69118 Heidelberg, Germany. razif.gabdoulline@eml.villa-bosch.de|European Media Laboratory, 69118 Heidelberg, Germany. razif.gabdoulline@eml.villa-bosch.de|European Media Laboratory, 69118 Heidelberg, Germany. razif.gabdoulline@eml.villa-bosch.de|European Media Laboratory, 69118 Heidelberg, Germany. razif.gabdoulline@eml.villa-bosch.de', 'Germany|Germany|Germany|Germany', 11, 'Chromosome Mapping|Data Display|Imaging, Three-Dimensional|Internet|Molecular Structure|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg220', '15593408', 'ProSAT (for Protein Structure Annotation Tool) is a tool to facilitate interactive visualization of non-structure-based functional annotations in protein 3D structures. It performs automated mapping of the functional annotations onto the protein structure and allows functional sites to be readily identified upon visualization. The current version of ProSAT can be applied to large datasets of protein structures for fast visual identification of active and other functional sites derived from the SwissProt and Prosite databases.'),
(71841, 2003, 'bio', 'CRANN: detecting adaptive evolution in protein-coding DNA sequences', 'Creevey, C J|McInerney, J O', 'Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland. chris.creevey@may.ie.|Department of Biology, National University of Ireland, Maynooth, Co. Kildare, Ireland. chris.creevey@may.ie.', 'Ireland|Ireland', 31, 'Base Sequence|Evolution, Molecular|Open Reading Frames|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/btg225', '15593409', 'A software program CRANN has been developed in order to detect adaptive evolution in protein-coding DNA sequences.'),
(71842, 2003, 'bio', 'E-Cell 2: multi-platform E-Cell simulation system', 'Takahashi, K|Ishikawa, N|Sadamoto, Y|Sasamoto, H|Ohta, S|Shiozawa, A|Miyoshi, F|Naito, Y|Nakayama, Y|Tomita, M', 'Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa 252-8520, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan', 108, 'Algorithms|Cells|Data Display|Models, Biological|Programming Languages|Software|Software Design|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg221', '15593410', 'A new version of the E-Cell simulation system,which runs on Windows as well as Linux, has been released as free software under the terms of the GNU General Public License.'),
(71843, 2003, 'bio', 'Web-based exchange of biochemical information', 'Güler, Sinan|Eberhart, Andreas|Rojas, Isabel', 'Lion Bioscience AG, International University, Heidelberg, Germany.|Lion Bioscience AG, International University, Heidelberg, Germany.|Lion Bioscience AG, International University, Heidelberg, Germany.', 'Germany|Germany|Germany', 4, 'Databases, Factual|Information Storage and Retrieval|Internet|Models, Biological|Programming Languages|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg234', '15593411', 'In this paper we present a web-based system for the semantic integration of biological data using a database model and an XML exchange format. The prototype developed integrates data related to enzymes.'),
(71844, 2005, 'bio', 'SITEBLAST--rapid and sensitive local alignment of genomic sequences employing motif anchors', 'Michael, Morris|Dieterich, Christoph|Vingron, Martin', 'Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.|Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Berlin, Germany.', 'Germany|Germany|Germany', 14, 'Algorithms|Amino Acid Motifs|Chromosome Mapping|Consensus Sequence|Documentation|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti224', '15598827', 'Comparative sequence analysis is the essence of many approaches to genome annotation. Heuristic alignment algorithms utilize similar seed pairs to anchor an alignment. Some applications of local alignment algorithms (e.g. phylogenetic footprinting) would benefit from including prior knowledge (e.g. binding site motifs) in the alignment building process.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71845, 2005, 'bio', 'Dynamic simulation of protein complex formation on a genomic scale', 'Beyer, A|Wilhelm, T', 'Theoretical Systems Biology, Institute of Molecular Biotechnology, Beutenbergstr. 11, 07745 Jena, Germany. beyer@imb-jena.de|Theoretical Systems Biology, Institute of Molecular Biotechnology, Beutenbergstr. 11, 07745 Jena, Germany. beyer@imb-jena.de', 'Germany|Germany', 10, 'Computer Simulation|Gene Expression Regulation, Fungal|Genomics|Models, Biological|Protein Binding|Protein Interaction Mapping|Proteome|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti223', '15598828', 'One of the central questions in the post-genomic era is the understanding of protein-protein interactions and of protein complex formation. It has been observed that protein complex size distributions of the yeast Saccharomyces cerevisiae decay exponentially. The shape of these size distributions reflects mechanisms of protein complex association and dissociation.'),
(71846, 2005, 'bio', 'CARHTA GENE: multipopulation integrated genetic and radiation hybrid mapping', 'de Givry, Simon|Bouchez, Martin|Chabrier, Patrick|Milan, Denis|Schiex, Thomas', 'INRA, Biométrie et Intelligence Artificielle/Génétique Cellulaire, BP 27, 31326 Castanet-Tolosan Cedex, France.|INRA, Biométrie et Intelligence Artificielle/Génétique Cellulaire, BP 27, 31326 Castanet-Tolosan Cedex, France.|INRA, Biométrie et Intelligence Artificielle/Génétique Cellulaire, BP 27, 31326 Castanet-Tolosan Cedex, France.|INRA, Biométrie et Intelligence Artificielle/Génétique Cellulaire, BP 27, 31326 Castanet-Tolosan Cedex, France.|INRA, Biométrie et Intelligence Artificielle/Génétique Cellulaire, BP 27, 31326 Castanet-Tolosan Cedex, France.', 'France|France|France|France|France', 309, 'Chromosome Mapping|Computer Graphics|Computer Simulation|Crosses, Genetic|Genetics, Population|Models, Genetic|Models, Statistical|Radiation Hybrid Mapping|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti222', '15598829', 'CAR(H)(T)A GENE: is an integrated genetic and radiation hybrid (RH) mapping tool which can deal with multiple populations, including mixtures of genetic and RH data. CAR(H)(T)A GENE: performs multipoint maximum likelihood estimations with accelerated expectation-maximization algorithms for some pedigrees and has sophisticated algorithms for marker ordering. Dedicated heuristics for framework mapping are also included. CAR(H)(T)A GENE: can be used as a C++ library, through a shell command and a graphical interface. The XML output for companion tools is integrated.'),
(71847, 2005, 'bio', 'The WHy domain mediates the response to desiccation in plants and bacteria', 'Ciccarelli, Francesca D|Bork, Peer', 'European Molecular Biology Laboratory, 69012 Heidelberg, Meyerhofstrasse 1, Germany. francesca.ciccarelli@embl.de|European Molecular Biology Laboratory, 69012 Heidelberg, Meyerhofstrasse 1, Germany. francesca.ciccarelli@embl.de', 'Germany|Germany', 25, 'Adaptation, Physiological|Bacteria|Bacterial Proteins|Conserved Sequence|Desiccation|Heat-Shock Response|Plant Diseases|Plant Proteins|Plants|Protein Structure, Tertiary|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti221', '15598830', 'The hypersensitive response (HR) is a process activated by plants after microbial infection. Its main phenotypic effects are both a programmed death of the plant cells near the infection site and a reduction of the microbial proliferation. Although many resistance genes (R genes) associated to HR have been identified, very little is known about the molecular mechanisms activated after their expression.'),
(71848, 2005, 'bio', 'MultiPLX: automatic grouping and evaluation of PCR primers', 'Kaplinski, Lauris|Andreson, Reidar|Puurand, Tarmo|Remm, Maido', 'Department of Bioinformatics, University of Tartu, Tartu, Estonia.|Department of Bioinformatics, University of Tartu, Tartu, Estonia.|Department of Bioinformatics, University of Tartu, Tartu, Estonia.|Department of Bioinformatics, University of Tartu, Tartu, Estonia.', 'Estonia|Estonia|Estonia|Estonia', 45, 'Algorithms|DNA Primers|Pattern Recognition, Automated|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti219', '15598831', 'MultiPLX is a new program for automatic grouping of PCR primers. It can use many different parameters to estimate the compatibility of primers, such as primer-primer interactions, primer-product interactions, difference in melting temperatures, difference in product length and the risk of generating alternative products from the template. A unique feature of the MultiPLX is the ability to perform automatic grouping of large number (thousands) of primer pairs.'),
(71849, 2005, 'bio', 'DbW: automatic update of a functional family-specific multiple alignment', 'Prigent, V|Thierry, J C|Poch, O|Plewniak, F', 'Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, (CNRS/INSERM/ULP) BP 10142, 67404 Illkirch, Cedex, France. prigent@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, (CNRS/INSERM/ULP) BP 10142, 67404 Illkirch, Cedex, France. prigent@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, (CNRS/INSERM/ULP) BP 10142, 67404 Illkirch, Cedex, France. prigent@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, (CNRS/INSERM/ULP) BP 10142, 67404 Illkirch, Cedex, France. prigent@igbmc.u-strasbg.fr', 'France|France|France|France', 4, 'Algorithms|Amino Acyl-tRNA Synthetases|Databases, Protein|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti218', '15598832', 'Recent advances in gene sequencing have provided complete sequence information for a number of genomes and as a result the amount of data in the sequence databases is growing at an exponential rate. We introduce here a new program, DbW, to automate the update of a functional family-specific multiple alignment that tries to include relevant sequences. The program is based on the use of different sources of information: sequences and annotations in databases.'),
(71850, 2005, 'bio', 'Differential gene expression detection using penalized linear regression models: the improved SAM statistics', 'Wu, Baolin', 'Division of Biostatistics, School of Public Health, University of Minnesota, A460 Mayo Building, MMC 303, Minneapolis, MN 55455, USA. baolin@biostat.umn.edu', 'United States', 43, 'Cell Line, Tumor|Gene Expression Profiling|Gene Expression Regulation|Humans|Linear Models|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Radiation, Ionizing|Regression Analysis|Software', 'Comparative Study', '10.1093/bioinformatics/bti217', '15598833', 'Differential gene expression detection using microarrays has received lots of research interests recently. Many methods have been proposed, including variants of F-statistics, non-parametric approaches and empirical Bayesian methods etc. The SAM statistics has been shown to have good performance in empirical studies. SAM is more like an ad hoc shrinkage method. The idea is that for small sample microarray data, it is often useful to pool information across genes to improve efficiency. Under Bayesian framework Smyth formally derived the test statistics with shrinkage using the hierarchical models. In this paper we cast differential gene expression detection in the familiar framework of linear regression model. Commonly used test statistics correspond to using least squares to estimate the regression parameters. Based on the vast literature of research on linear models, we can naturally consider other alternatives. Here we explore the penalized linear regression. We propose the penalized t-/F-statistics for two-class microarray data based on [Formula: see text] penalty. We will show that the penalized test statistics intuitively makes sense and through applications we illustrate its good performance.'),
(71851, 2005, 'bio', 'LS Bound based gene selection for DNA microarray data', 'Zhou, Xin|Mao, K Z', 'School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang avenue, Singapore 639798.|School of Electrical and Electronic Engineering, Nanyang Technological University, Nanyang avenue, Singapore 639798.', 'Singapore|Singapore', 66, 'Biomarkers, Tumor|Discriminant Analysis|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Journal Article', '10.1093/bioinformatics/bti216', '15598834', 'One problem with discriminant analysis of DNA microarray data is that each sample is represented by quite a large number of genes, and many of them are irrelevant, insignificant or redundant to the discriminant problem at hand. Methods for selecting important genes are, therefore, of much significance in microarray data analysis. In the present study, a new criterion, called LS Bound measure, is proposed to address the gene selection problem. The LS Bound measure is derived from leave-one-out procedure of LS-SVMs (least squares support vector machines), and as the upper bound for leave-one-out classification results it reflects to some extent the generalization performance of gene subsets.'),
(71852, 2005, 'bio', 'Balancing protein similarity and gene co-expression reveals new links between genetic conservation and developmental diversity in invertebrates', 'Lefebvre, Céline|Aude, Jean-Christophe|Glémet, Eric|Néri, Christian', 'INSERM, Avenir Group, Laboratory of Genomic Biology, Centre Paul Broca, 75014 Paris, France.|INSERM, Avenir Group, Laboratory of Genomic Biology, Centre Paul Broca, 75014 Paris, France.|INSERM, Avenir Group, Laboratory of Genomic Biology, Centre Paul Broca, 75014 Paris, France.|INSERM, Avenir Group, Laboratory of Genomic Biology, Centre Paul Broca, 75014 Paris, France.', 'France|France|France|France', 12, 'Animals|Caenorhabditis elegans Proteins|Conserved Sequence|Drosophila Proteins|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation, Developmental|Invertebrates|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bti215', '15598835', 'To identify genetic conservation relative to precise aspects of developmental diversity, an essential question in computational biology, we developed a new comparative method that allows conserved modules for the best balance between protein sequence similarity and gene co-expression to be constructed, in invertebrates.'),
(71853, 2005, 'bio', 'Boolean relationships among genes responsive to ionizing radiation in the NCI 60 ACDS', 'Pal, Ranadip|Datta, Aniruddha|Fornace, Albert J|Bittner, Michael L|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX 77843, USA.', 'United States|United States|United States|United States|United States', 14, 'Cell Line, Tumor|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Logistic Models|Models, Biological|Multivariate Analysis|Neoplasm Proteins|Neoplasms|Radiation, Ionizing|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bti214', '15598836', 'An early use of gene-expression data coming from microarrays was to discover non-linear multivariate intergene relationships. Pursuing this direction, the motivation for this paper is 2-fold: (1) to discover and elucidate multivariate logical predictive relations among gene expressions in a dataset arising from radiation studies using the NCI 60 Anti-Cancer Drug Screen (ACDS) cell lines, and (2) to demonstrate how these logical relations based on coarse quantization reflect corresponding relations in the continuous data.'),
(71854, 2005, 'bio', 'Implicit motif distribution based hybrid computational kernel for sequence classification', 'Atalay, Volkan|Cetin-Atalay, Rengul', 'Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.|Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship|Subcellular Fractions', 'Evaluation Studies', '10.1093/bioinformatics/bti212', '15598837', 'We designed a general computational kernel for classification problems that require specific motif extraction and search from sequences. Instead of searching for explicit motifs, our approach finds the distribution of implicit motifs and uses as a feature for classification. Implicit motif distribution approach may be used as modus operandi for bioinformatics problems that require specific motif extraction and search, which is otherwise computationally prohibitive.'),
(71855, 2005, 'bio', 'TargetFinder: a software for antisense oligonucleotide target site selection based on MAST and secondary structures of target mRNA', 'Bo, Xiaochen|Wang, Shengqi', 'Beijing Institute of Radiation Medicine, 27 Taiping Road, Haidian District, Beijing 100850, China.|Beijing Institute of Radiation Medicine, 27 Taiping Road, Haidian District, Beijing 100850, China.', 'China|China', 36, 'Algorithms|Computer Graphics|Gene Targeting|Nucleic Acid Conformation|Oligonucleotides, Antisense|RNA, Messenger|Sequence Alignment|Sequence Analysis, RNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti211', '15598838', 'TargetFinder is a PC/Windows program for interactive effective antisense oligonucleotide (AO) selection based on mRNA accessible site tagging (MAST) and secondary structures of target mRNA. To make MAST result intuitive, both the alignment result and tag frequency profile is illustrated. As theoretical reference, secondary structure and single strand probability profile of target mRNA is also represented. All of these sequences and profiles are displayed in aligned mode, which facilitates identification of the accessible sites in target mRNA. Graphical, user-friendly interface makes TargetFinder a useful tool in AO target site selection.'),
(71856, 2005, 'bio', 'Visualizing information across multidimensional post-genomic structured and textual databases', 'Tao, Ying|Friedman, Carol|Lussier, Yves A', 'Department of Biomedical Informatics, Columbia University, 622 West 168th Street, Vanderbilt Clinic, 5th Floor, New York, NY 10032, USA.|Department of Biomedical Informatics, Columbia University, 622 West 168th Street, Vanderbilt Clinic, 5th Floor, New York, NY 10032, USA.|Department of Biomedical Informatics, Columbia University, 622 West 168th Street, Vanderbilt Clinic, 5th Floor, New York, NY 10032, USA.', 'United States|United States|United States', 12, 'Computer Graphics|Database Management Systems|Databases, Bibliographic|Databases, Genetic|Documentation|Gene Expression Profiling|Genomics|Humans|Information Storage and Retrieval|Models, Biological|Natural Language Processing|Periodicals as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti210', '15598839', 'Visualizing relationships among biological information to facilitate understanding is crucial to biological research during the post-genomic era. Although different systems have been developed to view gene-phenotype relationships for specific databases, very few have been designed specifically as a general flexible tool for visualizing multidimensional genotypic and phenotypic information together. Our goal is to develop a method for visualizing multidimensional genotypic and phenotypic information and a model that unifies different biological databases in order to present the integrated knowledge using a uniform interface.'),
(71857, 2005, 'bio', 'GeneContent: software for whole-genome phylogenetic analysis', 'Gu, Xun|Huang, Wei|Xu, Dongping|Zhang, Hongmei', 'Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA. xgu@iastate.edu|Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA. xgu@iastate.edu|Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA. xgu@iastate.edu|Department of Genetics, Development and Cell Biology, Iowa State University, Ames, IA 50011, USA. xgu@iastate.edu', 'United States|United States|United States|United States', 9, 'Algorithms|Animals|Chromosome Mapping|Computer Graphics|Computer Simulation|Evolution, Molecular|Genetic Variation|Humans|Kinetics|Models, Genetic|Phylogeny|Software|Species Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti208', '15598840', 'GeneContent is a software system to infer the genome phylogeny based on an additive genome distance that can be estimated from the extended gene content data, which contains the genome-wide information (absence of a gene family, presence as single copy or presence as duplicates) across multiple species. GeneContent can also be used to explore the genome-wide evolutionary pattern of gene loss and proliferation.'),
(71858, 2005, 'bio', 'The G5 domain: a potential N-acetylglucosamine recognition domain involved in biofilm formation', 'Bateman, Alex|Holden, Matthew T G|Yeats, Corin', 'The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. agb@sanger.ac.uk|The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. agb@sanger.ac.uk|The Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SA, UK. agb@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 58, 'Acetylglucosamine|Amino Acid Sequence|Bacterial Physiological Phenomena|Bacterial Proteins|Binding Sites|Biofilms|Molecular Sequence Data|Protein Binding|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti206', '15598841', 'Biofilms are complex microbial communities found at surfaces that are often associated with extracellular polysaccharides. Biofilm formation is a complex process that is being understood at the molecular level only recently. We have identified a novel domain that we call the G5 domain (named after its conserved glycine residues), which is found in a variety of enzymes such as Streptococcal IgA peptidases and various glycosyl hydrolases in bacteria. The G5 domain is found in the Accumulation Associated Protein (AAP), which is an important component in biofilm formation in Staphylococcus aureus. A common feature of the proteins containing G5 domains is N-acetylglucosamine binding, and we attribute this function to the G5 domain.'),
(71859, 2005, 'bio', 'Structural drift: a possible path to protein fold change', 'Krishna, S Sri|Grishin, Nick V', 'Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA.', 'United States|United States', 0, 'Carrier Proteins|Evolution, Molecular|Ferredoxins|Formate Dehydrogenases|Genetic Drift|Membrane Proteins|Models, Chemical|Models, Molecular|Protein Folding|Protein Structure, Tertiary|Protein Subunits|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti227', '15604105', 'Along with their mutating sequences, protein structures change in time. Analyzing a formate dehydrogenase domain that is evolutionarily related to ferredoxin, but simultaneously contains all the structural elements of a beta-Grasp fold, we illustrate here a mechanism termed as structural drift, by which changes to a protein fold can occur.'),
(71860, 2005, 'bio', 'Investigating the dynamic behavior of biochemical networks using model families', 'Haunschild, Marc Daniel|Freisleben, Bernd|Takors, Ralf|Wiechert, Wolfgang', 'Department of Simulation, University of Siegen, Paul-Bonatz-Strasse 9-11, D-57068 Siegen, Germany.|Department of Simulation, University of Siegen, Paul-Bonatz-Strasse 9-11, D-57068 Siegen, Germany.|Department of Simulation, University of Siegen, Paul-Bonatz-Strasse 9-11, D-57068 Siegen, Germany.|Department of Simulation, University of Siegen, Paul-Bonatz-Strasse 9-11, D-57068 Siegen, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Biochemistry|Cell Physiological Phenomena|Computer Simulation|Evolution, Molecular|Gene Expression Regulation|Kinetics|Models, Biological|Models, Chemical|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/bti225', '15604106', 'Supporting the evolutionary modeling process of dynamic biochemical networks based on sampled in vivo data requires more than just simulation. In the course of the modeling process, the modeler is typically concerned not only with a single model but also with sequences, alternatives and structural variants of models. Powerful automatic methods are then required to assist the modeler in the organization and the evaluation of alternative models. Moreover, the structure and peculiarities of the data require dedicated tool support.'),
(71861, 2005, 'bio', 'RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees', 'Stamatakis, A|Ludwig, T|Meier, H', 'Department of Computer Science, Technical University of Munich Boltzmannstrasse 3, D-85748 München, Germany. stamatak@cs.tum.edu|Department of Computer Science, Technical University of Munich Boltzmannstrasse 3, D-85748 München, Germany. stamatak@cs.tum.edu|Department of Computer Science, Technical University of Munich Boltzmannstrasse 3, D-85748 München, Germany. stamatak@cs.tum.edu', 'Germany|Germany|Germany', 1062, 'Algorithms|Artificial Intelligence|Biological Evolution|Computer Simulation|Computing Methodologies|Genetics, Population|Likelihood Functions|Models, Genetic|Models, Statistical|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/bti191', '15608047', 'The computation of large phylogenetic trees with statistical models such as maximum likelihood or bayesian inference is computationally extremely intensive. It has repeatedly been demonstrated that these models are able to recover the true tree or a tree which is topologically closer to the true tree more frequently than less elaborate methods such as parsimony or neighbor joining. Due to the combinatorial and computational complexity the size of trees which can be computed on a Biologists PC workstation within reasonable time is limited to trees containing approximately 100 taxa.'),
(71862, 2005, 'bio', 'An integrated tool for microarray data clustering and cluster validity assessment', 'Bolshakova, Nadia|Azuaje, Francisco|Cunningham, Pádraig', 'Department of Computer Science, Trinity College, Dublin, Ireland. Nadia.Bolshakova@cs.tcd.ie|Department of Computer Science, Trinity College, Dublin, Ireland. Nadia.Bolshakova@cs.tcd.ie|Department of Computer Science, Trinity College, Dublin, Ireland. Nadia.Bolshakova@cs.tcd.ie', 'Ireland|Ireland|Ireland', 0, 'Algorithms|Benchmarking|Cluster Analysis|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software|Systems Integration|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti190', '15608048', 'In this paper we present a data mining system, which allows the application of different clustering and cluster validity algorithms for DNA microarray data. This tool may improve the quality of the data analysis results, and may support the prediction of the number of relevant clusters in the microarray datasets. This systematic evaluation approach may significantly aid genome expression analyses for knowledge discovery applications. The developed software system may be effectively used for clustering and validating not only DNA microarray expression analysis applications but also other biomedical and physical data with no limitations.'),
(71863, 2005, 'bio', 'Finding differentially expressed genes for pattern generation', 'Abul, Osman|Alhajj, Reda|Polat, Faruk|Barker, Ken', 'Department of Computer Science, University of Calgary Calgary, Alberta, Canada.|Department of Computer Science, University of Calgary Calgary, Alberta, Canada.|Department of Computer Science, University of Calgary Calgary, Alberta, Canada.|Department of Computer Science, University of Calgary Calgary, Alberta, Canada.', 'Canada|Canada|Canada|Canada', 0, 'Algorithms|Artificial Intelligence|BRCA2 Protein|Biomarkers, Tumor|Breast Neoplasms|Carrier Proteins|Cluster Analysis|Computing Methodologies|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Ubiquitin-Protein Ligases', 'Comparative Study', '10.1093/bioinformatics/bti189', '15608049', 'It is important to consider finding differentially expressed genes in a dataset of microarray experiments for pattern generation.'),
(71864, 2005, 'bio', 'Multidimensional support vector machines for visualization of gene expression data', 'Komura, D|Nakamura, H|Tsutsumi, S|Aburatani, H|Ihara, S', 'Research Center for Advanced Science and Technology, University of Tokyo Tokyo 153-8904, Japan. komura@hal.rcast.u-tokyo.ac.jp|Research Center for Advanced Science and Technology, University of Tokyo Tokyo 153-8904, Japan. komura@hal.rcast.u-tokyo.ac.jp|Research Center for Advanced Science and Technology, University of Tokyo Tokyo 153-8904, Japan. komura@hal.rcast.u-tokyo.ac.jp|Research Center for Advanced Science and Technology, University of Tokyo Tokyo 153-8904, Japan. komura@hal.rcast.u-tokyo.ac.jp|Research Center for Advanced Science and Technology, University of Tokyo Tokyo 153-8904, Japan. komura@hal.rcast.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan|Japan', 30, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computing Methodologies|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Leukemia|Lung Neoplasms|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti188', '15608050', 'Since DNA microarray experiments provide us with huge amount of gene expression data, they should be analyzed with statistical methods to extract the meanings of experimental results. Some dimensionality reduction methods such as Principal Component Analysis (PCA) are used to roughly visualize the distribution of high dimensional gene expression data. However, in the case of binary classification of gene expression data, PCA does not utilize class information when choosing axes. Thus clearly separable data in the original space may not be so in the reduced space used in PCA.'),
(71865, 2005, 'bio', 'An architecture for biological information extraction and representation', 'Vailaya, Aditya|Bluvas, Peter|Kincaid, Robert|Kuchinsky, Allan|Creech, Michael|Adler, Annette', 'Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com|Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com|Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com|Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com|Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com|Agilent Laboratories 3500 Deer Creek Road, MS 26U-16, Palo Alto, CA 94304, USA. aditya_vailaya@agilent.com', 'United States|United States|United States|United States|United States|United States', 59, 'Abstracting and Indexing as Topic|Artificial Intelligence|Computational Biology|Database Management Systems|Databases, Factual|Documentation|Information Storage and Retrieval|Models, Biological|Natural Language Processing|Periodicals as Topic|Software|User-Computer Interface|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti187', '15608051', 'Technological advances in biomedical research are generating a plethora of heterogeneous data at a high rate. There is a critical need for extraction, integration and management tools for information discovery and synthesis from these heterogeneous data.'),
(71866, 2005, 'bio', 'Clustering of diverse genomic data using information fusion', 'Kasturi, Jyotsna|Acharya, Raj', 'Department of Computer Science and Engineering, Pennsylvania State University University Park, PA 16802, USA. jkasturi@cse.psu.edu|Department of Computer Science and Engineering, Pennsylvania State University University Park, PA 16802, USA. jkasturi@cse.psu.edu', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Cluster Analysis|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Genome, Fungal|Genomics|Information Storage and Retrieval|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins', 'Comparative Study', '10.1093/bioinformatics/bti186', '15608052', 'Genome sequencing projects and high-through-put technologies like DNA and Protein arrays have resulted in a very large amount of information-rich data. Microarray experimental data are a valuable, but limited source for inferring gene regulation mechanisms on a genomic scale. Additional information such as promoter sequences of genes/DNA binding motifs, gene ontologies, and location data, when combined with gene expression analysis can increase the statistical significance of the finding. This paper introduces a machine learning approach to information fusion for combining heterogeneous genomic data. The algorithm uses an unsupervised joint learning mechanism that identifies clusters of genes using the combined data.'),
(71867, 2005, 'bio', 'Improved prediction of protein-protein binding sites using a support vector machines approach', 'Bradford, James R|Westhead, David R', 'School of Biochemistry and Molecular Biology, University of Leeds, Leeds, LS2 9JT, UK.|School of Biochemistry and Molecular Biology, University of Leeds, Leeds, LS2 9JT, UK.', 'United Kingdom|United Kingdom', 288, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Pattern Recognition, Automated|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti242', '15613384', 'Structural genomics projects are beginning to produce protein structures with unknown function, therefore, accurate, automated predictors of protein function are required if all these structures are to be properly annotated in reasonable time. Identifying the interface between two interacting proteins provides important clues to the function of a protein and can reduce the search space required by docking algorithms to predict the structures of complexes.'),
(71868, 2005, 'bio', 'Methodological aspects of the genetic dissection of gene expression', 'Carlborg, O|De Koning, D J|Manly, K F|Chesler, E|Williams, R W|Haley, C S', 'Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.|Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.|Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.|Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.|Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.|Roslin Institute, Roslin, Midlothian EH25 9 PS, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 50, 'Algorithms|Animals|Chromosome Mapping|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Mice|Mice, Inbred C57BL|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Proteome|Quantitative Trait Loci|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti241', '15613385', 'Dissection of the genetics underlying gene expression utilizes techniques from microarray analyses as well as quantitative trait loci (QTL) mapping. Available QLT mapping methods are not tailored for the highly automated analyses required to deal with the thousand of gene transcripts encountered in the mapping of QTL affecting gene expression (sometimes referred to as eQTL). This report focuses on the adaptation of QTL mapping methodology to perform automated mapping of QTL affecting gene expression.'),
(71869, 2005, 'bio', 'Architecture of basic building blocks in protein and domain structural interaction networks', 'Moon, Hyun S|Bhak, Jonghwa|Lee, Kwang H|Lee, Doheon', 'Division of Computer Science, KAIST, Daejeon, Korea.|Division of Computer Science, KAIST, Daejeon, Korea.|Division of Computer Science, KAIST, Daejeon, Korea.|Division of Computer Science, KAIST, Daejeon, Korea.', '-|-|-|-', 23, 'Animals|Binding Sites|Computer Simulation|Humans|Models, Biological|Models, Chemical|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Analysis, Protein|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti240', '15613386', 'The structural interaction of proteins and their domains in networks is one of the most basic molecular mechanisms for biological cells. Topological analysis of such networks can provide an understanding of and solutions for predicting properties of proteins and their evolution in terms of domains. A single paradigm for the analysis of interactions at different layers, such as domain and protein layers, is needed.'),
(71870, 2005, 'bio', 'Quantifying the relevance of different mediators in the human immune cell network', 'Tieri, P|Valensin, S|Latora, V|Castellani, G C|Marchiori, M|Remondini, D|Franceschi, C', 'Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.|Dipartimento di Patologia Sperimentale, Università di Bologna, Via San Giacomo 12, 40126 Bologna, Italy.', 'Italy|Italy|Italy|Italy|Italy|Italy|Italy', 32, 'Antigen-Antibody Complex|Antigen-Presenting Cells|Cell Communication|Computer Simulation|Cytokines|Gene Expression Regulation|Humans|Immunity, Innate|Inflammation Mediators|Lymphocytes|Models, Immunological|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti239', '15613387', 'Immune cells coordinate their efforts for the correct and efficient functioning of the immune system (IS). Each cell type plays a distinct role and communicates with other cell types through mediators such as cytokines, chemokines and hormones, among others, that are crucial for the functioning of the IS and its fine tuning. Nevertheless, a quantitative analysis of the topological properties of an immunological network involving this complex interchange of mediators among immune cells is still lacking.'),
(71871, 2005, 'bio', 'An enhanced Java graph applet interface for visualizing interactomes', 'Chang, Aaron N|McDermott, Jason|Samudrala, Ram', 'Biomedical and Health Informatics, University of Washington, Seattle, WA 98195, USA.|Biomedical and Health Informatics, University of Washington, Seattle, WA 98195, USA.|Biomedical and Health Informatics, University of Washington, Seattle, WA 98195, USA.', 'United States|United States|United States', 3, 'Animals|Computer Graphics|Gene Expression Regulation|Humans|Programming Languages|Protein Interaction Mapping|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti237', '15613388', 'We have developed several new navigation features for a Java graph applet previously released for visualizing protein-protein interactions. This graph viewer can be used to navigate any molecular interactome dataset. We have successfully implemented this tool for exploring protein networks stored in the Bioverse interaction database.'),
(71872, 2005, 'bio', 'GMD@CSBDB: the Golm Metabolome Database', 'Kopka, Joachim|Schauer, Nicolas|Krueger, Stephan|Birkemeyer, Claudia|Usadel, Björn|Bergmüller, Eveline|Dörmann, Peter|Weckwerth, Wolfram|Gibon, Yves|Stitt, Mark|Willmitzer, Lothar|Fernie, Alisdair R|Steinhauser, Dirk', 'Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.|Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germ', 905, 'Database Management Systems|Databases, Protein|Documentation|Gas Chromatography-Mass Spectrometry|Gene Expression Profiling|Information Dissemination|Information Storage and Retrieval|Internet|Natural Language Processing|Proteome|Publications|Structure-Activity Relationship|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti236', '15613389', 'Metabolomics, in particular gas chromatography-mass spectrometry (GC-MS) based metabolite profiling of biological extracts, is rapidly becoming one of the cornerstones of functional genomics and systems biology. Metabolite profiling has profound applications in discovering the mode of action of drugs or herbicides, and in unravelling the effect of altered gene expression on metabolism and organism performance in biotechnological applications. As such the technology needs to be available to many laboratories. For this, an open exchange of information is required, like that already achieved for transcript and protein data. One of the key-steps in metabolite profiling is the unambiguous identification of metabolites in highly complex metabolite preparations from biological samples. Collections of mass spectra, which comprise frequently observed metabolites of either known or unknown exact chemical structure, represent the most effective means to pool the identification efforts currently performed in many laboratories around the world. Here we present GMD, The Golm Metabolome Database, an open access metabolome database, which should enable these processes. GMD provides public access to custom mass spectral libraries, metabolite profiling experiments as well as additional information and tools, e.g. with regard to methods, spectral information or compounds. The main goal will be the representation of an exchange platform for experimental research activities and bioinformatics to develop and improve metabolomics by multidisciplinary cooperation.'),
(71873, 2005, 'bio', 'GPSDB: a new database for synonyms expansion of gene and protein names', 'Pillet, Violaine|Zehnder, Marc|Seewald, Alexander K|Veuthey, Anne-Lise|Petrak, Johann', 'Swiss Institute of Bioinformatics, CMU-Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.|Swiss Institute of Bioinformatics, CMU-Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.|Swiss Institute of Bioinformatics, CMU-Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.|Swiss Institute of Bioinformatics, CMU-Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.|Swiss Institute of Bioinformatics, CMU-Rue Michel-Servet 1, 1211 Geneva 4, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland', 17, 'Database Management Systems|Databases, Protein|Documentation|Information Dissemination|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Proteins|Terminology as Topic|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti235', '15613390', 'We present a new database, GPSDB (Gene and Protein Synonyms DataBase) which collects gene/protein names, in a species specific way, from 14 main biological resources. A web-based search interface gives access to the database: given a gene/protein name, it retrieves all synonyms for this entity and queries Medline with a set of user-selected terms.'),
(71874, 2005, 'bio', 'A framework for scientific data modeling and automated software development', 'Fogh, Rasmus H|Boucher, Wayne|Vranken, Wim F|Pajon, Anne|Stevens, Tim J|Bhat, T N|Westbrook, John|Ionides, John M C|Laue, Ernest D', 'Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.|Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge, CB2 1GA, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Biopolymers|Computer Simulation|Database Management Systems|Documentation|Guidelines as Topic|Information Storage and Retrieval|Magnetic Resonance Spectroscopy|Models, Biological|Models, Chemical|Reference Standards|Science|Software|Unified Medical Language System', 'Journal Article', '10.1093/bioinformatics/bti234', '15613391', 'The lack of standards for storage and exchange of data is a serious hindrance for the large-scale data deposition, data mining and program interoperability that is becoming increasingly important in bioinformatics. The problem lies not only in defining and maintaining the standards, but also in convincing scientists and application programmers with a wide variety of backgrounds and interests to adhere to them.'),
(71875, 2005, 'bio', 'A structure-based method for protein sequence alignment', 'Kann, Maricel G|Thiessen, Paul A|Panchenko, Anna R|Schäffer, Alejandro A|Altschul, Stephen F|Bryant, Stephen H', 'National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.|National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Department of Health and Human Services, Bethesda, MD 20894, USA.', 'United States|United States|United States|United States|United States|United States', 16, 'Algorithms|Amino Acid Sequence|Databases, Protein|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti233', '15613392', 'With the continuing rapid growth of protein sequence data, protein sequence comparison methods have become the most widely used tools of bioinformatics. Among these methods are those that use position-specific scoring matrices (PSSMs) to describe protein families. PSSMs can capture information about conserved patterns within families, which can be used to increase the sensitivity of searches for related sequences. Certain types of structural information, however, are not generally captured by PSSM search methods. Here we introduce a program, Structure-based ALignment TOol (SALTO), that aligns protein query sequences to PSSMs using rules for placing and scoring gaps that are consistent with the conserved regions of domain alignments from NCBIs Conserved Domain Database.'),
(71876, 2005, 'bio', 'PreDs: a server for predicting dsDNA-binding site on protein molecular surfaces', 'Tsuchiya, Yuko|Kinoshita, Kengo|Nakamura, Haruki', 'Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.|Institute for Protein Research, Osaka University, 3-2 Yamadaoka, Suita, Osaka, 565-0871, Japan.', 'Japan|Japan|Japan', 36, 'Computer Graphics|Computer Simulation|DNA|DNA-Binding Proteins|Internet|Models, Chemical|Models, Molecular|Nucleic Acid Conformation|Protein Binding|Protein Conformation|Surface Properties|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti232', '15613393', 'PreDs is a WWW server that predicts the dsDNA-binding sites on protein molecular surfaces generated from the atomic coordinates in a PDB format. The prediction was done by evaluating the electrostatic potential, the local curvature and the global curvature on the surfaces. Results of the prediction can be interactively checked with our original surface viewer.'),
(71877, 2005, 'bio', 'Bloader--a batch loader application for MIAMExpress', 'Schwager, Christian|Blake, Jonathon', 'EMBL, Meyerhofstrasse 1, 67117 Heidelberg, Germany. schwager@embl.de|EMBL, Meyerhofstrasse 1, 67117 Heidelberg, Germany. schwager@embl.de', 'Germany|Germany', 0, 'Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti231', '15613394', 'BLoader is a client server application for annotating and loading large amounts of Microarray data into a local installation of the MIAMExpress database. A set of nested spreadsheets is used to collect the required MIAME annotation. Controlled vocabularies are downloaded from MIAMExpress and ArrayExpress databases to guarantee MIAME compliance.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71878, 2005, 'bio', 'Evaluation of HIV-1 kinetic models using quantitative discrimination analysis', 'Knorr, Andrea L|Srivastava, Ranjan', 'Department of Chemical Engineering, University of Connecticut, Storrs, CT 06269, USA.|Department of Chemical Engineering, University of Connecticut, Storrs, CT 06269, USA.', 'United States|United States', 10, 'Cohort Studies|Computer Simulation|Databases, Factual|Diagnosis, Computer-Assisted|Discriminant Analysis|HIV Infections|HIV-1|Humans|Kinetics|Models, Biological|Models, Statistical|T-Lymphocytes|Virus Replication', 'Comparative Study', '10.1093/bioinformatics/bti230', '15613395', 'Since the identification of human immunodeficiency virus (HIV) over twenty years ago, many mathematical models of HIV dynamics have been proposed. The purpose of this study was to evaluate intracellular and intercellular scale HIV models that best described the dynamics of viral and cell titers of a person, where parameters were determined using typically available patient data. In this case, best was defined as the model most capable of describing experimental patient data and was determined by Bayesian-based model discrimination analysis and the ability to provide realistic results.'),
(71879, 2005, 'bio', 'M-ZDOCK: a grid-based approach for Cn symmetric multimer docking', 'Pierce, Brian|Tong, Weiwei|Weng, Zhiping', 'Bioinformatics Program, Boston University, Boston, MA, USA.|Bioinformatics Program, Boston University, Boston, MA, USA.|Bioinformatics Program, Boston University, Boston, MA, USA.', 'United States|United States|United States', 118, 'Algorithms|Binding Sites|Crystallization|Crystallography|Dimerization|Models, Chemical|Models, Molecular|Multiprotein Complexes|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti229', '15613396', 'Computational protein docking is a useful technique for gaining insights into protein interactions. We have developed an algorithm M-ZDOCK for predicting the structure of cyclically symmetric (Cn) multimers based on the structure of an unbound (or partially bound) monomer. Using a grid-based Fast Fourier Transform approach, a space of exclusively symmetric multimers is searched for the best structure. This leads to improvements both in accuracy and running time over the alternative, which is to run a binary docking program ZDOCK and filter the results for near-symmetry. The accuracy is improved because fewer false positives are considered in the search, thus hits are not as easily overlooked. By searching four instead of six degrees of freedom, the required amount of computation is reduced. This program has been tested on several known multimer complexes from the Protein DataBank, including four unbound multimers: three trimers and a pentamer. For all of these cases, M-ZDOCK was able to find at least one hit, whereas only two of the four testcases had hits when using ZDOCK and a symmetry filter. In addition, the running times are 30-40% faster for M-ZDOCK.'),
(71880, 2005, 'bio', 'Expa: a program for calculating extreme pathways in biochemical reaction networks', 'Bell, Steven L|Palsson, Bernhard Ø', 'Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.|Department of Bioengineering, University of California, San Diego, La Jolla, CA 92093, USA.', 'United States|United States', 57, 'Animals|Biochemistry|Cell Physiological Phenomena|Energy Metabolism|Gene Expression Regulation|Humans|Proteome|Signal Transduction|Software', 'Journal Article', '10.1093/bioinformatics/bti228', '15613397', 'The set of extreme pathways, a generating set for all possible steady-state flux maps in a biochemical reaction network, can be computed from the stoichiometric matrix, an incidence-like matrix reflecting the network topology. Here, we describe the implementation of a well-known algorithm to compute these pathways and give a summary of the features of the available software.'),
(71881, 2005, 'bio', 'Dynamic network reconstruction from gene expression data applied to immune response during bacterial infection', 'Guthke, Reinhard|Möller, Ulrich|Hoffmann, Martin|Thies, Frank|Töpfer, Susanne', 'Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de|Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de|Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de|Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de|Hans Knoell Institute for Natural Products Research, D-07745 Jena, Beutenbergstrasse 11a, Germany. Reinhard.Guthke@hki-jena.de', 'Germany|Germany|Germany|Germany|Germany', 98, 'Algorithms|Computer Simulation|Cytokines|Escherichia coli Infections|Gene Expression Profiling|Gene Expression Regulation|HLA-D Antigens|Humans|Models, Immunological|Oligonucleotide Array Sequence Analysis|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bti226', '15613398', 'The immune response to bacterial infection represents a complex network of dynamic gene and protein interactions. We present an optimized reverse engineering strategy aimed at a reconstruction of this kind of interaction networks. The proposed approach is based on both microarray data and available biological knowledge.'),
(71882, 2005, 'bio', 'Mapping SNPs to protein sequence and structure data', 'Cavallo, A|Martin, A C R', 'Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.|Department of Biochemistry and Molecular Biology, University College London, Gower Street, London WC1E 6BT, UK.', 'United Kingdom|United Kingdom', 62, 'Algorithms|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Databases, Protein|Genome, Human|Humans|Information Storage and Retrieval|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment|Sequence Analysis, DNA|Statistics as Topic|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti220', '15613399', 'Data on both single nucleotide polymorphisms and disease-related mutations are being collected at ever-increasing rates. To understand the structural effects of missense mutations, we consider both classes under the term single amino acid polymorphisms (SAAPs) and we wish to map these to protein structure where their effects can be analyzed. Our initial aim therefore is to create a completely automatically maintained database of SAAPs mapped to individual residues in the Protein Data Bank (PDB) updated as new mutations or structures become available.'),
(71883, 2005, 'bio', 'Exploring the diversity of complex metabolic networks', 'Hatzimanikatis, Vassily|Li, Chunhui|Ionita, Justin A|Henry, Christopher S|Jankowski, Matthew D|Broadbelt, Linda J', 'Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu|Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu|Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu|Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu|Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu|Department of Chemical and Biological Engineering, McCormick School of Engineering and Applied Sciences, Northwestern University, Evanston, IL, USA. vassily@northwestern.edu', 'United States|United States|United States|United States|United States|United States', 221, 'Amino Acids, Aromatic|Animals|Biodiversity|Computer Graphics|Computer Simulation|Energy Metabolism|Feasibility Studies|Humans|Models, Biological|Models, Chemical|Multienzyme Complexes|Signal Transduction|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti213', '15613400', 'Metabolism, the network of chemical reactions that make life possible, is one of the most complex processes in nature. We describe here the development of a computational approach for the identification of every possible biochemical reaction from a given set of enzyme reaction rules that allows the de novo synthesis of metabolic pathways composed of these reactions, and the evaluation of these novel pathways with respect to their thermodynamic properties.'),
(71884, 2005, 'bio', 'Quick and simple: quality control of microarray data', 'Sauer, Ursula|Preininger, Claudia|Hany-Schmatzberger, Robert', 'ARC Seibersdorf research GmbH, Department Bio-resources, A-2444 Seibersdorf, Austria. Ursula.Sauer@arcs.ac.at|ARC Seibersdorf research GmbH, Department Bio-resources, A-2444 Seibersdorf, Austria. Ursula.Sauer@arcs.ac.at|ARC Seibersdorf research GmbH, Department Bio-resources, A-2444 Seibersdorf, Austria. Ursula.Sauer@arcs.ac.at', 'Austria|Austria|Austria', 31, 'Algorithms|Benchmarking|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti238', '15615693', 'Microarrays are high-throughput tools for parallel miniaturized detection of biomolecules. In contrast to experiments using ratios of signals in two channels, experiments with only one fluorescent dye cause special problems for data analysis. The present work compares algorithms for quality filtering on spot level as well as array/slide level.'),
(71885, 2005, 'bio', 'ALOHOMORA: a tool for linkage analysis using 10K SNP array data', 'Rüschendorf, Franz|Nürnberg, Peter', 'Bioinformatics Department, Gene Mapping Center, Max Delbrück Center (MDC) for Molecular Medicine Berlin-Buch, Germany. fruesch@mdc-berlin.de|Bioinformatics Department, Gene Mapping Center, Max Delbrück Center (MDC) for Molecular Medicine Berlin-Buch, Germany. fruesch@mdc-berlin.de', 'Germany|Germany', 143, 'Algorithms|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Gene Frequency|Genetics, Population|Humans|Linkage Disequilibrium|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti264', '15647291', 'ALOHOMORA is a software tool designed to facilitate genome-wide linkage studies performed with high-density single nucleotide polymorphism (SNP) marker panels such as the Affymetrix GeneChip(R) Human Mapping 10K Array. Genotype data are converted into appropriate formats for a number of common linkage programs and subjected to standard quality control routines before linkage runs are started. ALOHOMORA is written in Perl and may be used to perform state-of-the-art linkage scans in small and large families with any genetic model. Options for using different genetic maps or ethnicity-specific allele frequencies are implemented. Graphic outputs of whole-genome multipoint LOD score values are provided for the entire dataset as well as for individual families.'),
(71886, 2005, 'bio', 'ProtTest: selection of best-fit models of protein evolution', 'Abascal, Federico|Zardoya, Rafael|Posada, David', 'Department of Biochemistry, Genetics and Immunology, Universidad de Vigo, Spain. fabascal@uvigo.es|Department of Biochemistry, Genetics and Immunology, Universidad de Vigo, Spain. fabascal@uvigo.es|Department of Biochemistry, Genetics and Immunology, Universidad de Vigo, Spain. fabascal@uvigo.es', 'Spain|Spain|Spain', 2371, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Amino Acids|Computer Graphics|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Humans|Internet|Models, Genetic|Models, Molecular|Molecular Sequence Data|Mutagenesis, Site-Directed|Phylogeny|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti263', '15647292', 'Using an appropriate model of amino acid replacement is very important for the study of protein evolution and phylogenetic inference. We have built a tool for the selection of the best-fit model of evolution, among a set of candidate models, for a given protein sequence alignment.'),
(71887, 2005, 'bio', 'Significance analysis of functional categories in gene expression studies: a structured permutation approach', 'Barry, William T|Nobel, Andrew B|Wright, Fred A', 'Department of Biostatistics, University of North Carolina at Chapel Hill, 27599-7420, USA.|Department of Biostatistics, University of North Carolina at Chapel Hill, 27599-7420, USA.|Department of Biostatistics, University of North Carolina at Chapel Hill, 27599-7420, USA.', 'United States|United States|United States', 231, 'Algorithms|Biomarkers, Tumor|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Lung Neoplasms|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Software|Software Validation|Survival Analysis', 'Comparative Study', '10.1093/bioinformatics/bti260', '15647293', 'In high-throughput genomic and proteomic experiments, investigators monitor expression across a set of experimental conditions. To gain an understanding of broader biological phenomena, researchers have until recently been limited to post hoc analyses of significant gene lists.'),
(71888, 2005, 'bio', 'Selecton: a server for detecting evolutionary forces at a single amino-acid site', 'Doron-Faigenboim, Adi|Stern, Adi|Mayrose, Itay|Bacharach, Eran|Pupko, Tal', 'Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.|Department of Cell Research and Immunology, George S. Wise Faculty of Life Sciences, Tel Aviv University, Ramat Aviv, Israel.', 'Israel|Israel|Israel|Israel|Israel', 110, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Amino Acids|Computer Graphics|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|HIV Protease|Humans|Internet|Models, Genetic|Models, Molecular|Molecular Sequence Data|Mutagenesis, Site-Directed|Phylogeny|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti259', '15647294', 'We present an algorithmic tool for the identification of biologically significant amino acids in proteins of known three dimensional structure. We estimate the degree of purifying selection and positive Darwinian selection at each site and project these estimates onto the molecular surface of the protein. Thus, patches of functional residues (undergoing either positive or purifying selection), which may be discontinuous in the linear sequence, are revealed. We test for the statistical significance of the site-specific scores in order to obtain reliable and valid estimates.'),
(71889, 2005, 'bio', 'Robust estimation of protein expression ratios with lysate microarray technology', 'Mircean, Cristian|Shmulevich, Ilya|Cogdell, David|Choi, Woonyoung|Jia, Yu|Tabus, Ioan|Hamilton, Stanley R|Zhang, Wei', 'Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.|Department of Pathology, University of Texas M.D. Anderson Cancer Center, Houston, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 39, 'Algorithms|Biomarkers, Tumor|Cell Line, Tumor|Colonic Neoplasms|Gene Expression Profiling|Humans|Hydrolysis|Immunoassay|Least-Squares Analysis|Neoplasm Proteins|Protein Array Analysis|Software', 'Comparative Study', '10.1093/bioinformatics/bti258', '15647295', 'The protein lysate microarray is a developing proteomic technology for measuring protein expression levels in a large number of biological samples simultaneously. A challenge for accurate quantification is the relatively narrow dynamic range associated with the commonly used chromogenic signal detection system. To facilitate accurate measurement of the relative expression levels, each sample is serially diluted and each diluted version is spotted on a nitrocellulose-coated slide in triplicate. Thus, each sample yields multiple measurements in different dynamic ranges of the detection system. This study aims to develop suitable algorithms that yield accurate representations of the relative expression levels in different samples from multiple data points.'),
(71890, 2005, 'bio', 'Transcription factor binding site identification using the self-organizing map', 'Mahony, Shaun|Hendrix, David|Golden, Aaron|Smith, Terry J|Rokhsar, Daniel S', 'National Centre for Biomedical Engineering Science, NUI Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI Galway, Ireland. shaun.mahony@nuigalway.ie|National Centre for Biomedical Engineering Science, NUI Galway, Ireland. shaun.mahony@nuigalway.ie', 'Ireland|Ireland|Ireland|Ireland|Ireland', 59, 'Algorithms|Amino Acid Motifs|Artificial Intelligence|Binding Sites|Conserved Sequence|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti256', '15647296', 'The automatic identification of over-represented motifs present in a collection of sequences continues to be a challenging problem in computational biology. In this paper, we propose a self-organizing map of position weight matrices as an alternative method for motif discovery. The advantage of this approach is that it can be used to simultaneously characterize every feature present in the dataset, thus lessening the chance that weaker signals will be missed. Features identified are ranked in terms of over-representation relative to a background model.'),
(71891, 2005, 'bio', 'On the use of qualitative reasoning to simulate and identify metabolic pathways', 'King, Ross D|Garrett, Simon M|Coghill, George M', 'Department of Computer Science, University of Wales, Aberystwyth, UK. rdk@aber.ac.uk|Department of Computer Science, University of Wales, Aberystwyth, UK. rdk@aber.ac.uk|Department of Computer Science, University of Wales, Aberystwyth, UK. rdk@aber.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 44, 'Algorithms|Animals|Artificial Intelligence|Cell Physiological Phenomena|Computer Simulation|Energy Metabolism|Gene Expression Regulation|Glycolysis|Humans|Models, Biological|Multienzyme Complexes|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bti255', '15647297', 'Perhaps the greatest challenge of modern biology is to develop accurate in silico models of cells. To do this we require computational formalisms for both simulation (how according to the model the state of the cell evolves over time) and identification (learning a model cell from observation of states). We propose the use of qualitative reasoning (QR) as a unified formalism for both tasks. The two most commonly used alternative methods of modelling biochemical pathways are ordinary differential equations (ODEs), and logical/graph-based (LG) models.'),
(71892, 2005, 'bio', 'Computational analysis suggests that alternative first exons are involved in tissue-specific transcription in rice (Oryza sativa)', 'Kitagawa, Noriyuki|Washio, Takanori|Kosugi, Shunichi|Yamashita, Tomoya|Higashi, Kenji|Yanagawa, Hiroshi|Higo, Kenichi|Satoh, Koji|Ohtomo, Yasuhiro|Sunako, Tomomi|Murakami, Kazuo|Matsubara, Kenichi|Kawai, Jun|Carninci, Piero|Hayashizaki, Yoshihide|Kikuchi, Shoshi|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.|Institute for Advanced Biosciences, Keio University Tsuruoka, Yamagata, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japan|Japa', 23, 'Alternative Splicing|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Exons|Genetic Variation|Genome, Plant|Models, Genetic|Oryza|Plant Proteins|Plant Structures|Tissue Distribution|Transcription Initiation Site|Transcriptional Activation', 'Journal Article', '10.1093/bioinformatics/bti253', '15647298', 'Transcription start site selection and alternative splicing greatly contribute to diversifying gene expression. Recent studies have revealed the existence of alternative first exons, but most have involved mammalian genes, and as yet the regulation of usage of alternative first exons has not been clarified, especially in plants.'),
(71893, 2005, 'bio', 'GOAnno: GO annotation based on multiple alignment', 'Chalmel, F|Lardenois, A|Thompson, J D|Muller, J|Sahel, J-A|Léveillard, T|Poch, O', 'Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr|Laboratoire de Biologie et Génomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, CNRS/INSERM/ULP BP 163, Illkirch , France. chalmel@igbmc.u-strasbg.fr', 'France|France|France|France|France|France|France', 26, 'Algorithms|Databases, Protein|Documentation|Internet|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti252', '15647299', 'GOAnno is a web tool that automatically annotates proteins according to the Gene Ontology (GO) using evolutionary information available in hierarchized multiple alignments. GO terms present in the aligned functional subfamily can be cross-validated and propagated to obtain highly reliable predicted GO annotation based on the GOAnno algorithm.'),
(71894, 2005, 'bio', 'Detecting clusters of different geometrical shapes in microarray gene expression data', 'Kim, Dae-Won|Lee, Kwang H|Lee, Doheon', 'Department of BioSystems and Advanced Information Technology Research Center, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon.|Department of BioSystems and Advanced Information Technology Research Center, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon.|Department of BioSystems and Advanced Information Technology Research Center, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon.', '-|-|-', 39, 'Algorithms|Cluster Analysis|Fuzzy Logic|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming Languages|Saccharomyces cerevisiae Proteins|Software', 'Comparative Study', '10.1093/bioinformatics/bti251', '15647300', 'Clustering has been used as a popular technique for finding groups of genes that show similar expression patterns under multiple experimental conditions. Many clustering methods have been proposed for clustering gene-expression data, including the hierarchical clustering, k-means clustering and self-organizing map (SOM). However, the conventional methods are limited to identify different shapes of clusters because they use a fixed distance norm when calculating the distance between genes. The fixed distance norm imposes a fixed geometrical shape on the clusters regardless of the actual data distribution. Thus, different distance norms are required for handling the different shapes of clusters.'),
(71895, 2005, 'bio', 'Protein refinement: a new challenge for CASP in its 10th anniversary', 'Valencia, Alfonso', 'Department of BioSystems and Advanced Information Technology Research Center, Korea Advanced Institute of Science and Technology, Yuseong-gu, Daejeon.', '-', 0, 'Algorithms|Computational Biology|Databases, Protein|Models, Chemical|Models, Molecular|Molecular Biology|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Editorial', '10.1093/bioinformatics/bti249', '15647301', '-'),
(71896, 2005, 'bio', 'Design of a DNA chip for detection of unknown genetically modified organisms (GMOs)', 'Nesvold, Håvard|Kristoffersen, Anja Bråthen|Holst-Jensen, Arne|Berdal, Knut G', 'Department of Informatics, University of Oslo, Blindern, Norway.|Department of Informatics, University of Oslo, Blindern, Norway.|Department of Informatics, University of Oslo, Blindern, Norway.|Department of Informatics, University of Oslo, Blindern, Norway.', 'Norway|Norway|Norway|Norway', 31, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Computer Simulation|DNA Mutational Analysis|DNA Probes|Environmental Monitoring|Equipment Design|Equipment Failure Analysis|Gene Expression Profiling|Models, Genetic|Oligonucleotide Array Sequence Analysis|Organisms, Genetically Modified|Risk Assessment|Risk Factors', 'Comparative Study', '10.1093/bioinformatics/bti248', '15647302', 'Unknown genetically modified organisms (GMOs) have not undergone a risk evaluation, and hence might pose a danger to health and environment. There are, today, no methods for detecting unknown GMOs. In this paper we propose a novel method intended as a first step in an approach for detecting unknown genetically modified (GM) material in a single plant.'),
(71897, 2005, 'bio', 'MAGIC Tool: integrated microarray data analysis', 'Heyer, L J|Moskowitz, D Z|Abele, J A|Karnik, P|Choi, D|Campbell, A M|Oldham, E E|Akin, B K', 'Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu|Department of Mathematics, Davidson College, NC, USA. laheyer@davidson.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Computer Graphics|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti247', '15647303', 'Several programs are now available for analyzing the large datasets arising from cDNA microarray experiments. Most programs are expensive commercial packages or require expensive third party software. Some are freely available to academic researchers, but are limited to one operating system. MicroArray Genome Imaging and Clustering Tool (MAGIC Tool) is an open source program that works on all major platforms, and takes users from tiff to gif. Several unique features of MAGIC Tool are particularly useful for research and teaching.'),
(71898, 2005, 'bio', 'AGML Central: web based gel proteomic infrastructure', 'Stanislaus, Romesh|Chen, Chuming|Franklin, Jennifer|Arthur, John|Almeida, Jonas S', 'Department of Biostatistics, Bioinformatics and Epidemiology, Charleston, SC 29425, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Charleston, SC 29425, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Charleston, SC 29425, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Charleston, SC 29425, USA. stanisrc@musc.edu|Department of Biostatistics, Bioinformatics and Epidemiology, Charleston, SC 29425, USA. stanisrc@musc.edu', 'United States|United States|United States|United States|United States', 16, 'Database Management Systems|Databases, Protein|Electrophoresis, Gel, Two-Dimensional|Gene Expression Profiling|Information Dissemination|Information Storage and Retrieval|Internet|Proteome|Proteomics|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti246', '15647304', 'AGML Central is a web-based open-source public infrastructure for dissemination of two-dimensional Gel Electrophoresis (2-DE) proteomics data in AGML format (Annotated Gel Markup Language). It includes a growing collection of converters from proprietary formats such as those produced by PDQUEST (BioRad), PHORETIX 2-D (Nonlinear Dynamics) and Melanie (GenBio SA). The resulting unifying AGML formatted entry, with or without the raw gel images, is optionally stored in a database for future reference. AGML Central was developed to provide a common platform for data dissemination and development of 2-DE data analysis tools. This resource responds to an increasing use of AGML for 2-DE public source data representation which requires automated tools for conversion from proprietary formats. Conversion and short-term storage is made publicly available, permanent storage requires prior registering. A JAVA applet visualizer was developed to visualize the AGML data with cross-reference links. In order to facilitate automated access a SOAP web service is also included in the AGML Central infrastructure.'),
(71899, 2005, 'bio', 'On the quality of tree-based protein classification', 'Lazareva-Ulitsky, Betty|Diemer, Karen|Thomas, Paul D', 'Computational Biology Department, Applied Biosystems, Foster City, CA 94404, USA. betty.lazareva@fc.celera.com|Computational Biology Department, Applied Biosystems, Foster City, CA 94404, USA. betty.lazareva@fc.celera.com|Computational Biology Department, Applied Biosystems, Foster City, CA 94404, USA. betty.lazareva@fc.celera.com', 'United States|United States|United States', 14, 'Algorithms|Databases, Protein|Evolution, Molecular|Phylogeny|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bti244', '15647305', 'Phylogenetic analysis of protein sequences is widely used in protein function classification and delineation of subfamilies within larger families. In addition, the recent increase in the number of protein sequence entries with controlled vocabulary terms describing function (e.g. the Gene Ontology) suggests that it may be possible to overlay these terms onto phylogenetic trees to automatically locate functional divergence events in protein family evolution. Phylogenetic analysis of large datasets requires fast algorithms, and even fast, approximate distance matrix-based phylogenetic algorithms are slow on large datasets since they involve calculating maximum likelihood estimates of pairwise evolutionary distances. There have been many attempts to classify protein sequences on the family and subfamily level without reconstructing phylogenetic trees, but using hierarchical clustering with simpler distance measures, which also produce trees or dendrograms. How can these trees be compared in their ability to accurately classify protein sequences?'),
(71900, 2005, 'bio', 'Pairwise local structural alignment of RNA sequences with sequence similarity less than 40%', 'Havgaard, Jakob Hull|Lyngsø, Rune B|Stormo, Gary D|Gorodkin, Jan', 'Center for Bioinformatics and Division of Genetics, IBHV, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark.|Center for Bioinformatics and Division of Genetics, IBHV, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark.|Center for Bioinformatics and Division of Genetics, IBHV, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark.|Center for Bioinformatics and Division of Genetics, IBHV, The Royal Veterinary and Agricultural University, Frederiksberg, Denmark.', 'Denmark|Denmark|Denmark|Denmark', 0, 'Algorithms|Conserved Sequence|Nucleic Acid Conformation|RNA, Untranslated|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti279', '15657094', 'Searching for non-coding RNA (ncRNA) genes and structural RNA elements (eleRNA) are major challenges in gene finding today as these often are conserved in structure rather than in sequence. Even though the number of available methods is growing, it is still of interest to pairwise detect two genes with low sequence similarity, where the genes are part of a larger genomic region.'),
(71901, 2005, 'bio', 'Modeling of signal-response cascades using decision tree analysis', 'Hautaniemi, Sampsa|Kharait, Sourabh|Iwabu, Akihiro|Wells, Alan|Lauffenburger, Douglas A', 'Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA. sampsa@mit.edu|Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA. sampsa@mit.edu|Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA. sampsa@mit.edu|Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA. sampsa@mit.edu|Biological Engineering Division, Massachusetts Institute of Technology, Cambridge, 02139, USA. sampsa@mit.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Cell Movement|Computer Simulation|Decision Support Techniques|Extracellular Matrix Proteins|Gene Expression Regulation|Logistic Models|Mice|Models, Biological|NIH 3T3 Cells|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bti278', '15657095', 'Signal transduction cascades governing cell functional responses to stimulatory cues play crucial roles in cell regulatory systems and represent promising therapeutic targets for complex human diseases. however, mathematical analysis of how cell responses are governed by signaling activities is challenging due to their multivariate and non-linear nature. diverse computational methods are potentially available, but most are ineffective for protein-level data that is limited in extent and replication.'),
(71902, 2005, 'bio', 'PIBASE: a comprehensive database of structurally defined protein interfaces', 'Davis, Fred P|Sali, Andrej', 'Graduate Group in Biophysics, California Institute for Quantitative Biomedical Research, University of California, San Francisco, 94143, USA.|Graduate Group in Biophysics, California Institute for Quantitative Biomedical Research, University of California, San Francisco, 94143, USA.', 'United States|United States', 137, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Databases, Protein|Models, Chemical|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti277', '15657096', 'In recent years, the Protein Data Bank (PDB) has experienced rapid growth. To maximize the utility of the high resolution protein-protein interaction data stored in the PDB, we have developed PIBASE, a comprehensive relational database of structurally defined interfaces between pairs of protein domains. It is composed of binary interfaces extracted from structures in the PDB and the Probable Quaternary Structure server using domain assignments from the Structural Classification of Proteins and CATH fold classification systems.'),
(71903, 2005, 'bio', 'Dynamic model based algorithms for screening and genotyping over 100 K SNPs on oligonucleotide microarrays', 'Di, Xiaojun|Matsuzaki, Hajime|Webster, Teresa A|Hubbell, Earl|Liu, Guoying|Dong, Shoulian|Bartell, Dan|Huang, Jing|Chiles, Richard|Yang, Geoffrey|Shen, Mei-mei|Kulp, David|Kennedy, Giulia C|Mei, Rui|Jones, Keith W|Cawley, Simon', 'Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com|Affymetrix, Inc., Santa Clara, CA 95051, USA. xiaojun_di@affymetrix.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 150, 'Algorithms|Computer Simulation|DNA Mutational Analysis|Genetic Testing|Genotype|Humans|Models, Genetic|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti275', '15657097', 'A high density of single nucleotide polymorphism (SNP) coverage on the genome is desirable and often an essential requirement for population genetics studies. Region-specific or chromosome-specific linkage studies also benefit from the availability of as many high quality SNPs as possible. The availability of millions of SNPs from both Perlegen and the public domain and the development of an efficient microarray-based assay for genotyping SNPs has brought up some interesting analytical challenges. Effective methods for the selection of optimal subsets of SNPs spanning the genome and methods for accurately calling genotypes from probe hybridization patterns have enabled the development of a new microarray-based system for robustly genotyping over 100,000 SNPs per sample.'),
(71904, 2005, 'bio', 'Mtreemix: a software package for learning and using mixture models of mutagenetic trees', 'Beerenwinkel, Niko|Rahnenführer, Jörg|Kaiser, Rolf|Hoffmann, Daniel|Selbig, Joachim|Lengauer, Thomas', 'Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu|Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu|Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu|Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu|Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu|Max Planck Institute for Informatics, Saarbrücken, Germany. niko@math.berkeley.edu', 'Germany|Germany|Germany|Germany|Germany|Germany', 50, 'Algorithms|Artificial Intelligence|Computer Simulation|Genetic Variation|Models, Genetic|Mutagenesis|Mutation|Phylogeny|Software', 'Journal Article', '10.1093/bioinformatics/bti274', '15657098', 'Mixture models of mutagenetic trees constitute a class of probabilistic models for describing evolutionary processes that are characterized by the accumulation of permanent genetic changes. They have been applied to model the accumulation of chromosomal gains and losses in tumor development and the development of drug resistance-associated mutations in the HIV genome.Mtreemix is a software package for estimating mutagenetic trees mixture models from observed cross-sectional data and for using these models for predictions. We provide programs for model fitting, model selection, simulation, likelihood computation and waiting time estimation.'),
(71905, 2005, 'bio', 'Online predicted human interaction database', 'Brown, Kevin R|Jurisica, Igor', 'Division of Cancer Informatics, Ontario Cancer Institute, University of Toronto, Canada.|Division of Cancer Informatics, Ontario Cancer Institute, University of Toronto, Canada.', 'Canada|Canada', 445, 'Database Management Systems|Databases, Protein|Gene Expression Profiling|Genome, Human|Humans|Information Storage and Retrieval|Internet|Online Systems|Protein Interaction Mapping|Proteome|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti273', '15657099', 'High-throughput experiments are being performed at an ever-increasing rate to systematically elucidate protein-protein interaction (PPI) networks for model organisms, while the complexities of higher eukaryotes have prevented these experiments for humans.'),
(71906, 2005, 'bio', 'Integrative data analysis for functional prediction: a multi-objective optimization approach', 'Azuaje, F', 'School of Computing and Mathematics, University of Ulster, Jordanstown, UK.', 'Jordan', 1, 'Algorithms|Computer Simulation|Gene Expression Profiling|Mitochondrial Proteins|Models, Biological|Proteins|Proteome|Sequence Analysis, Protein|Structure-Activity Relationship|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bti272', '15657100', 'An integrative classification system for functional genomics is introduced. A comparison with a previous study of the yeast mitochondrial proteome is presented.'),
(71907, 2005, 'bio', 'IntegratedMap: a Web interface for integrating genetic map data', 'Yang, Hongyu|Wang, Hongyu|Gingle, Alan R', 'Center for Applied Genetic Technologies, University of Georgia, Athens, 30602, USA.|Center for Applied Genetic Technologies, University of Georgia, Athens, 30602, USA.|Center for Applied Genetic Technologies, University of Georgia, Athens, 30602, USA.', 'Georgia|Georgia|Georgia', 2, 'Algorithms|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Database Management Systems|Databases, Genetic|Gene Frequency|Genetics, Population|Information Storage and Retrieval|Internet|Linkage Disequilibrium|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti271', '15657101', 'IntegratedMap is a Web application and database schema for storing and interactively displaying genetic map data. Its Web interface includes a menu for direct chromosome/linkage group selection, a search form for selection based on mapped object location and linkage group displays. An overview display provides convenient access to the full range of mapped and anchored object types with genetic locus details, such as numbers, types and names of mapped/anchored objects displayed in a compact scrollable list box that automatically updates based on selected map location and object type. Also, multilinkage group and localized map views are available along with links that can be configured for integration with other Web resources.'),
(71908, 2005, 'bio', 'Use of within-array replicate spots for assessing differential expression in microarray experiments', 'Smyth, Gordon K|Michaud, Joëlle|Scott, Hamish S', 'Walter and Eliza Hall Institute of Medical Research, Melbourne, Vic, Australia. smyth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Melbourne, Vic, Australia. smyth@wehi.edu.au|Walter and Eliza Hall Institute of Medical Research, Melbourne, Vic, Australia. smyth@wehi.edu.au', 'Australia|Australia|Australia', 926, 'Algorithms|Gene Expression Profiling|Genetic Variation|In Situ Hybridization, Fluorescence|Linear Models|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|RNA, Messenger|Software', 'Comparative Study', '10.1093/bioinformatics/bti270', '15657102', 'Spotted arrays are often printed with probes in duplicate or triplicate, but current methods for assessing differential expression are not able to make full use of the resulting information. The usual practice is to average the duplicate or triplicate results for each probe before assessing differential expression. This results in the loss of valuable information about genewise variability.'),
(71909, 2005, 'bio', 'EPIMHC: a curated database of MHC-binding peptides for customized computational vaccinology', 'Reche, Pedro A|Zhang, Hong|Glutting, John-Paul|Reinherz, Ellis L', 'Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. reche@research.dfci.harvard.edu|Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. reche@research.dfci.harvard.edu|Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. reche@research.dfci.harvard.edu|Laboratory of Immunobiology and Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA. reche@research.dfci.harvard.edu', 'United States|United States|United States|United States', 55, 'Database Management Systems|Databases, Protein|Drug Design|Epitope Mapping|HLA Antigens|Histocompatibility Antigens|Information Storage and Retrieval|Major Histocompatibility Complex|Peptides|Protein Binding|Sequence Analysis, Protein|Software|User-Computer Interface|Vaccination', 'Journal Article', '10.1093/bioinformatics/bti269', '15657103', 'EPIMHC is a relational database of MHC-binding peptides and T cell epitopes that are observed in real proteins. Currently, the database contains 4867 distinct peptide sequences from various sources, including 84 tumor-associated antigens. The EPIMHC database is accessible through a web server that has been designed to facilitate research in computational vaccinology. Importantly, peptides resulting from a query can be selected to derive specific motif-matrices. Subsequently, these motif-matrices can be used in combination with a dynamic algorithm for predicting MHC-binding peptides from user-provided protein queries.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71910, 2005, 'bio', 'Co-occurrence based meta-analysis of scientific texts: retrieving biological relationships between genes', 'Jelier, R|Jenster, G|Dorssers, L C J|van der Eijk, C C|van Mulligen, E M|Mons, B|Kors, J A', 'Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl|Department of Medical Informatics, Erasmus MC-University Medical Center, Rotterdam, The Netherlands. r.jelier@erasmusmc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 51, 'Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|Meta-Analysis as Topic|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Proteins|PubMed|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti268', '15657104', 'The advent of high-throughput experiments in molecular biology creates a need for methods to efficiently extract and use information for large numbers of genes. Recently, the associative concept space (ACS) has been developed for the representation of information extracted from biomedical literature. The ACS is a Euclidean space in which thesaurus concepts are positioned and the distances between concepts indicates their relatedness. The ACS uses co-occurrence of concepts as a source of information. In this paper we evaluate how well the system can retrieve functionally related genes and we compare its performance with a simple gene co-occurrence method.'),
(71911, 2005, 'bio', 'Testing association of a pathway with survival using gene expression data', 'Goeman, Jelle J|Oosting, Jan|Cleton-Jansen, Anne-Marie|Anninga, Jakob K|van Houwelingen, Hans C', 'Department of Medical Statistics, Leiden University Medical Center, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, The Netherlands. j.j.goeman@lumc.nl|Department of Medical Statistics, Leiden University Medical Center, The Netherlands. j.j.goeman@lumc.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 108, 'Biomarkers, Tumor|Gene Expression Profiling|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Osteosarcoma|Proportional Hazards Models|Signal Transduction|Survival|Survival Analysis|Tumor Cells, Cultured', 'Journal Article', '10.1093/bioinformatics/bti267', '15657105', 'A recent surge of interest in survival as the primary clinical endpoint of microarray studies has called for an extension of the Global Test methodology to survival.'),
(71912, 2005, 'bio', 'Prediction of unfolded segments in a protein sequence based on amino acid composition', 'Coeytaux, Karen|Poupon, Anne', 'Yeast Structural Genomics, IBBMC, Université Paris-Sud, Orsay, France.|Yeast Structural Genomics, IBBMC, Université Paris-Sud, Orsay, France.', 'France|France', 103, 'Algorithms|Amino Acid Sequence|Amino Acids|Computer Simulation|Hydrophobic and Hydrophilic Interactions|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti266', '15657106', 'Partially and wholly unstructured proteins have now been identified in all kingdoms of life--more commonly in eukaryotic organisms. This intrinsic disorder is related to certain critical functions. Apart from their fundamental interest, unstructured regions in proteins may prevent crystallization. Therefore, the prediction of disordered regions is an important aspect for the understanding of protein function, but may also help to devise genetic constructs.'),
(71913, 2005, 'bio', 'Topology of small-world networks of protein-protein complex structures', 'del Sol, Antonio|Fujihashi, Hirotomo|OMeara, Paul', 'Bioinformatics Research Project, Research and Development Division, Fujirebio Inc., 51 Komiya-cho, Hachioji-shi, Tokyo 192-0031, Japan. ao-mesa@fujirebio.co.jp|Bioinformatics Research Project, Research and Development Division, Fujirebio Inc., 51 Komiya-cho, Hachioji-shi, Tokyo 192-0031, Japan. ao-mesa@fujirebio.co.jp|Bioinformatics Research Project, Research and Development Division, Fujirebio Inc., 51 Komiya-cho, Hachioji-shi, Tokyo 192-0031, Japan. ao-mesa@fujirebio.co.jp', 'Japan|Japan|Japan', 95, 'Binding Sites|Computer Simulation|Dimerization|Models, Biological|Models, Chemical|Multiprotein Complexes|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Signal Transduction|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti167', '15659419', 'The majority of real examples of small-world networks exhibit a power law distribution of edges among the nodes, therefore not fitting into the wiring model proposed by Watts and Strogatz. However, protein structures can be modeled as small-world networks, with a distribution of the number of links decaying exponentially as in the case of this wiring model. We approach the protein-protein interaction mechanism by viewing it as a particular rewiring occurring in the system of two small-world networks represented by the monomers, where a re-arrangement of links takes place upon dimerization leaving the small-world character in the dimer network. Due to this rewiring, the most central residues at the complex interfaces tend to form clusters, which are not homogenously distributed. We show that these highly central residues are strongly correlated with the presence of hot spots of binding free energy.'),
(71914, 2005, 'bio', 'Small, fuzzy and interpretable gene expression based classifiers', 'Vinterbo, Staal A|Kim, Eun-Young|Ohno-Machado, Lucila', 'Decision Systems Group, Brigham and Womens Hospital, Harvard Medical School/Massachusetts Institute of Technology, Boston, USA. staal@dsg.harvard.edu|Decision Systems Group, Brigham and Womens Hospital, Harvard Medical School/Massachusetts Institute of Technology, Boston, USA. staal@dsg.harvard.edu|Decision Systems Group, Brigham and Womens Hospital, Harvard Medical School/Massachusetts Institute of Technology, Boston, USA. staal@dsg.harvard.edu', 'United States|United States|United States', 49, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Cluster Analysis|Fuzzy Logic|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti287', '15661797', 'Interpretation of classification models derived from gene-expression data is usually not simple, yet it is an important aspect in the analytical process. We investigate the performance of small rule-based classifiers based on fuzzy logic in five datasets that are different in size, laboratory origin and biomedical domain.'),
(71915, 2005, 'bio', 'Concept-based annotation of enzyme classes', 'Hofmann, Oliver|Schomburg, Dietmar', 'Department of Biochemistry, University of Cologne, Germany. o.hofmann@smail.uni-koeln.de|Department of Biochemistry, University of Cologne, Germany. o.hofmann@smail.uni-koeln.de', 'Germany|Germany', 9, 'Algorithms|Animals|Artificial Intelligence|Database Management Systems|Databases, Protein|Documentation|Enzymes|Humans|Information Storage and Retrieval|Meta-Analysis as Topic|Metabolic Diseases|Natural Language Processing|Periodicals as Topic|PubMed|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti284', '15661799', 'Given the explosive growth of biomedical data as well as the literature describing results and findings, it is getting increasingly difficult to keep up to date with new information. Keeping databases synchronized with current knowledge is a time-consuming and expensive task-one which can be alleviated by automatically gathering findings from the literature using linguistic approaches. We describe a method to automatically annotate enzyme classes with disease-related information extracted from the biomedical literature for inclusion in such a database.'),
(71916, 2005, 'bio', 'Gene finding for the helical cytokines', 'Conklin, Darrell|Haldeman, Betty|Gao, Zeren', 'Department of Computing, City University, London, UK. conklin@city.ac.uk|Department of Computing, City University, London, UK. conklin@city.ac.uk|Department of Computing, City University, London, UK. conklin@city.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 10, 'Algorithms|Chromosome Mapping|Cytokines|Exons|Genome, Human|Humans|Protein Conformation|Protein Folding|Sequence Analysis, DNA|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti283', '15661800', 'Gene finding remains an open problem well after the sequencing of the human genome. The low gene sensitivity of current methods is a problem for divergent protein families, because fairly accurate exon assemblies are required before sensitive fold recognition algorithms can be applied. This paper presents a new genomic threading algorithm which integrates the gene finding and fold recognition steps into a single process. The method is applicable to evolutionarily divergent protein families that have retained some trace of their common ancestry, number and phase of introns, sizes of exons and placement of structural elements on specific exons. Such conserved structural signals may be visible despite dramatic evolution of protein sequence.'),
(71917, 2005, 'bio', 'TruMatch--a BLAST post-processor that identifies bona fide sequence matches to genome assemblies', 'Li, Weixi|Rehmeyer, Cathryn J|Staben, Chuck|Farman, Mark L', 'Department of Biological Sciences, University of Kentucky, Lexington, 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, 40546, USA.|Department of Biological Sciences, University of Kentucky, Lexington, 40546, USA.', 'United States|United States|United States|United States', 4, 'Algorithms|Chromosome Mapping|Databases, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti257', '15671115', 'BLAST is a widely used alignment tool for detecting matches between a query sequence and entries in nucleotide sequence databases. Matches (high-scoring pairs, HSPs) are assigned a score based on alignment length and quality and, by default, are reported with the top-scoring matches listed first. For certain types of searches, however, this method of reporting is not optimal. This is particularly true when searching a genome sequence with a query that was derived from the same genome, or a closely related one. If the genome is complex and the assembly is far from complete, correct matches are often relegated to low positions in the results, where they may be easily overlooked. To rectify this problem, we developed TruMatch--a program that parses standard BLAST outputs and identifies HSPs that involve query segments with unique matches to the assembly. Candidates for bona fide matches between a query sequence and a genome assembly are listed at the top of the TruMatch output.'),
(71918, 2005, 'bio', 'Investigating metabolite essentiality through genome-scale analysis of Escherichia coli production capabilities', 'Imielixc5x84ski, Marcin|Belta, Cxc4x83lin|Halxc3xa1sz, Adxc3xa1m|Rubin, Harvey', 'Genomics and Computational Biology Graduate Group, University of Pennsylvania School of Medicine, Philadelphia, 19104, USA. imielns@mail.med.upenn.edu|Genomics and Computational Biology Graduate Group, University of Pennsylvania School of Medicine, Philadelphia, 19104, USA. imielns@mail.med.upenn.edu|Genomics and Computational Biology Graduate Group, University of Pennsylvania School of Medicine, Philadelphia, 19104, USA. imielns@mail.med.upenn.edu|Genomics and Computational Biology Graduate Group, University of Pennsylvania School of Medicine, Philadelphia, 19104, USA. imielns@mail.med.upenn.edu', 'United States|United States|United States|United States', 0, 'Algorithms|Cell Survival|Chromosome Mapping|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Deletion|Gene Expression Regulation|Models, Biological|Mutagenesis, Site-Directed|Recombinant Proteins|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti245', '15671116', 'A phenotype mechanism is classically derived through the study of a set of mutants and comparison of their biochemical capabilities. One method of comparing mutant capabilities is to characterize producible and knocked out metabolites. However such an effect is difficult to manually assess, especially for a large biochemical network and a complex media. Current algorithmic approaches towards analyzing metabolic networks either do not address this specific property or are computationally infeasible on the genome-scale.'),
(71919, 2005, 'bio', 'A linear programming approach for identifying a consensus sequence on DNA sequences', 'Li, Han-Lin|Fu, Chang-Jui', 'Institute of Information Management, National Chiao Tung University, Taiwan, China. hlli@cc.nctu.edu.tw|Institute of Information Management, National Chiao Tung University, Taiwan, China. hlli@cc.nctu.edu.tw', 'China|China', 0, 'Algorithms|Consensus Sequence|Programming, Linear|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti286', '15671117', 'Maximum-likelihood methods for solving the consensus sequence identification (CSI) problem on DNA sequences may only find a local optimum rather than the global optimum. Additionally, such methods do not allow logical constraints to be imposed on their models. This study develops a linear programming technique to solve CSI problems by finding an optimum consensus sequence. This method is computationally more efficient and is guaranteed to reach the global optimum. The developed method can also be extended to treat more complicated CSI problems with ambiguous conserved patterns.'),
(71920, 2005, 'bio', 'Prediction of caspase cleavage sites using Bayesian bio-basis function neural networks', 'Yang, Zheng Rong', 'Department of Computer Science, Exeter University, Devonshire, UK. z.r.yang@ex.ac.uk', 'United Kingdom', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Caspases|Computer Simulation|Models, Chemical|Models, Statistical|Neural Networks (Computer)|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti281', '15671118', 'Apoptosis has drawn the attention of researchers because of its importance in treating some diseases through finding a proper way to block or slow down the apoptosis process. Having understood that caspase cleavage is the key to apoptosis, we find novel methods or algorithms are essential for studying the specificity of caspase cleavage activity and this helps the effective drug design. As bio-basis function neural networks have proven to outperform some conventional neural learning algorithms, there is a motivation, in this study, to investigate the application of bio-basis function neural networks for the prediction of caspase cleavage sites.'),
(71921, 2005, 'bio', 'Computational identification of human mitochondrial proteins based on homology to yeast mitochondrially targeted proteins', 'Cameron, J M|Hurd, T|Robinson, B H', 'Metabolism Programme, Research Institute, The Hospital for Sick Children, Toronto, ON Canada.|Metabolism Programme, Research Institute, The Hospital for Sick Children, Toronto, ON Canada.|Metabolism Programme, Research Institute, The Hospital for Sick Children, Toronto, ON Canada.', 'Canada|Canada|Canada', 6, 'Conserved Sequence|Databases, Protein|Gene Expression Profiling|Genome, Fungal|Genome, Human|Humans|Mitochondrial Proteins|Proteome|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bti280', '15671119', 'Patients with defects of the mitochondrial respiratory chain due to mutations in nuclear genes are often undiagnosable due to the lack of information about the role of these genes. We therefore sought to produce a novel dataset of human nuclear-encoded mitochondrial proteins.'),
(71922, 2005, 'bio', 'PERMOL: restraint-based protein homology modeling using DYANA or CNS', 'Möglich, Andreas|Weinfurtner, Daniel|Gronwald, Wolfram|Maurer, Till|Kalbitzer, Hans Robert', 'Institut für Biophysik und physikalische Biochemie, Universität Regensburg, Germany.|Institut für Biophysik und physikalische Biochemie, Universität Regensburg, Germany.|Institut für Biophysik und physikalische Biochemie, Universität Regensburg, Germany.|Institut für Biophysik und physikalische Biochemie, Universität Regensburg, Germany.|Institut für Biophysik und physikalische Biochemie, Universität Regensburg, Germany.', 'Germany|Germany|Germany|Germany|Germany', 6, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti276', '15671120', 'PERMOL is a new restraint-based program for homology modeling of proteins. Restraints are generated from the information contained in structures of homologous template proteins. Employing the restraints generated by PERMOL, three-dimensional structures are obtained using MD programs such as DYANA or CNS. In contrast to other programs PERMOL is mainly based on the use of dihedral angle information which is optimally suited to preserve the local secondary structure. The global arrangement of these elements is then facilitated by a small number of distance restraints. Using PERMOL homology, models of high quality are obtained. A key advantage of the proposed method is its flexibility, which allows the inclusion of data from other sources, such as experimental restraints and the use of modern molecular dynamics programs to calculate structures.'),
(71923, 2005, 'bio', 'Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum', 'Morris, Jeffrey S|Coombes, Kevin R|Koomen, John|Baggerly, Keith A|Kobayashi, Ryuji', 'Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, Houston, USA. jefmorris@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, Houston, USA. jefmorris@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, Houston, USA. jefmorris@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, Houston, USA. jefmorris@mdanderson.org|Department of Biostatistics and Applied Mathematics, The University of Texas MD Anderson Cancer Center, Houston, USA. jefmorris@mdanderson.org', 'United States|United States|United States|United States|United States', 228, 'Algorithms|Biomarkers, Tumor|Biomedical Engineering|Complex Mixtures|Computer Simulation|Gene Expression Profiling|Humans|Models, Biological|Models, Chemical|Neoplasm Proteins|Pancreatic Neoplasms|Pattern Recognition, Automated|Proteome|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Clinical Trial', '10.1093/bioinformatics/bti254', '15673564', 'Mass spectrometry yields complex functional data for which the features of scientific interest are peaks. A common two-step approach to analyzing these data involves first extracting and quantifying the peaks, then analyzing the resulting matrix of peak quantifications. Feature extraction and quantification involves a number of interrelated steps. It is important to perform these steps well, since subsequent analyses condition on these determinations. Also, it is difficult to compare the performance of competing methods for analyzing mass spectrometry data since the true expression levels of the proteins in the population are generally not known.'),
(71924, 2005, 'bio', 'Evidence for the regulation of alternative splicing via complementary DNA sequence repeats', 'Lian, Yun|Garner, Harold R', 'Department of Biochemistry, McDermott Center for Human Growth and Development and Center for Biomedical Inventions, The University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.|Department of Biochemistry, McDermott Center for Human Growth and Development and Center for Biomedical Inventions, The University of Texas Southwestern Medical Center, 5323 Harry Hines Boulevard, Dallas, TX 75390, USA.', 'United States|United States', 0, 'Alternative Splicing|Chromosome Mapping|DNA, Complementary|Evidence-Based Medicine|Gene Expression Regulation|Genetic Variation|Humans|Introns|Models, Genetic|Models, Statistical|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Journal Article', '10.1093/bioinformatics/bti180', '15673565', 'While the mechanism for regulating alternative splicing is poorly understood, secondary structure has been shown to be integral to this process. Due to their propensity for forming complementary hairpin loops and their elevated mutation rates, tandem repeated sequences have the potential to influence splicing regulation.'),
(71925, 2005, 'bio', 'Molecular decomposition of complex clinical phenotypes using biologically structured analysis of microarray data', 'Lottaz, Claudio|Spang, Rainer', 'Max Planck Institute for Molecular Genetics and Berlin Center for Genome Based Bioinformatics, Germany. Claudio.Lottaz@molgen.mpg.de|Max Planck Institute for Molecular Genetics and Berlin Center for Genome Based Bioinformatics, Germany. Claudio.Lottaz@molgen.mpg.de', 'Germany|Germany', 30, 'Biomarkers, Tumor|Databases, Genetic|Gene Expression Profiling|Genetic Testing|Humans|Natural Language Processing|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Phenotype|Reproducibility of Results|Sensitivity and Specificity|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti292', '15677704', 'Today, the characterization of clinical phenotypes by gene-expression patterns is widely used in clinical research. If the investigated phenotype is complex from the molecular point of view, new challenges arise and these have not been addressed systematically. For instance, the same clinical phenotype can be caused by various molecular disorders, such that one observes different characteristic expression patterns in different patients.'),
(71926, 2005, 'bio', 'A grid layout algorithm for automatic drawing of biochemical networks', 'Li, Weijiang|Kurata, Hiroyuki', 'Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka, Japan.|Department of Bioscience and Bioinformatics, Kyushu Institute of Technology, Fukuoka, Japan.', 'Japan|Japan', 46, 'Algorithms|Artificial Intelligence|Biochemistry|Cell Cycle|Cell Cycle Proteins|Computer Graphics|Computer Simulation|Gene Expression Regulation|Models, Biological|Signal Transduction|User-Computer Interface|Yeasts', 'Comparative Study', '10.1093/bioinformatics/bti290', '15677705', 'Visualization is indispensable in the research of complex biochemical networks. Available graph layout algorithms are not adequate for satisfactorily drawing such networks. New methods are required to visualize automatically the topological architectures and facilitate the understanding of the functions of the networks.'),
(71927, 2005, 'bio', 'ProfDist: a tool for the construction of large phylogenetic trees based on profile distances', 'Friedrich, Joachim|Dandekar, Thomas|Wolf, Matthias|Müller, Tobias', 'Department of Bioinformatics, Biocenter, University of Würzburg, Germany.|Department of Bioinformatics, Biocenter, University of Würzburg, Germany.|Department of Bioinformatics, Biocenter, University of Würzburg, Germany.|Department of Bioinformatics, Biocenter, University of Würzburg, Germany.', 'Germany|Germany|Germany|Germany', 52, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Expression Profiling|Linkage Disequilibrium|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti289', '15677706', 'ProfDist is a user-friendly software package using the profile-neighbor-joining method (PNJ) in inferring phylogenies based on profile distances on DNA or RNA sequences. It is a tool for reconstructing and visualizing large phylogenetic trees providing new and standard features with a special focus on time efficency, robustness and accuracy.'),
(71928, 2005, 'bio', 'TreeScan: a bioinformatic application to search for genotype/phenotype associations using haplotype trees', 'Posada, David|Maxwell, Taylor J|Templeton, Alan R', 'Variagenics, Inc., Cambridge, MA 02139, USA. dposada@uvigo.es|Variagenics, Inc., Cambridge, MA 02139, USA. dposada@uvigo.es|Variagenics, Inc., Cambridge, MA 02139, USA. dposada@uvigo.es', 'United States|United States|United States', 0, 'Chromosome Mapping|Computational Biology|Computer Simulation|Genotype|Haplotypes|Linkage Disequilibrium|Models, Genetic|Phenotype|Quantitative Trait Loci|Software', 'Journal Article', '10.1093/bioinformatics/bti293', '15681571', 'We present the software implementation of the tree scanning method to detect associations between genetic haplotypes and quantitative traits, utilizing the evolutionary history of the haplotypes, in samples of unrelated individuals.'),
(71929, 2005, 'bio', 'DictyMOLD-a Dictyostelium discoideum genome browser database', 'Felder, Marius|Szafranski, Karol|Lehmann, Rüdiger|Eichinger, Ludwig|Noegel, Angelika A|Platzer, Matthias|Glöckner, Gernot', 'IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.|IMB Jena, Department of Genome Analysis Beutenbergstrasse 11, 07745 Jena, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Animals|Chromosome Mapping|Database Management Systems|Databases, Nucleic Acid|Dictyostelium|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti250', '15681572', 'With the Dictyostelium Genome Project nearing completion, we initiated the construction of a data repository for all Dictyostelium discoideum genomic data. Up to now this database, called DictyMOLD (Dicty Map Of Linked Data), incorporates the recently completed D.discoideum chromosomes 1 and 2 sequences together with related annotations. To visualise maps, sequences and annotations and to provide access for the scientific community a perl-based browser was developed.'),
(71930, 2005, 'bio', 'CrossChip: a system supporting comparative analysis of different generations of Affymetrix arrays', 'Kong, Sek Won|Hwang, Kyu-Baek|Kim, Richard D|Zhang, Byoung-Tak|Greenberg, Steven A|Kohane, Isaac S|Park, Peter J', 'Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu|Bauer Center for Genomics Research, Harvard University, Cambridge, MA, USA. skong@cgr.harvard.edu', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|DNA Probes|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bti288', '15684227', 'To increase compatibility between different generations of Affymetrix GeneChip arrays, we propose a method of filtering probes based on their sequences. Our method is implemented as a web-based service for downloading necessary materials for converting the raw data files (*.CEL) for comparative analysis. The user can specify the appropriate level of filtering by setting the criteria for the minimum overlap length between probe sequences and the minimum number of usable probe pairs per probe set. Our website supports a within-species comparison for human and mouse GeneChip arrays.'),
(71931, 2005, 'bio', 'PROTEIOS: an open source proteomics initiative', 'Gärdén, Per|Alm, Rikard|Häkkinen, Jari', 'Complex Systems Division and Lund Swegene Bioinformatics Facility, Department of Theoretical Physics, Lund University, Sweden. per@thep.lu.se|Complex Systems Division and Lund Swegene Bioinformatics Facility, Department of Theoretical Physics, Lund University, Sweden. per@thep.lu.se|Complex Systems Division and Lund Swegene Bioinformatics Facility, Department of Theoretical Physics, Lund University, Sweden. per@thep.lu.se', 'Sweden|Sweden|Sweden', 21, 'Algorithms|Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Protein Interaction Mapping|Proteins|Proteomics|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti291', '15691852', 'PROTEIOS is an initiative for the development of a comprehensive open source system for storage, organization, analysis and annotation of proteomics experiments. The PROTEIOS platform is based on commonly acknowledged principles for proteomics data publishing.'),
(71932, 2005, 'bio', 'SNPsFinder--a web-based application for genome-wide discovery of single nucleotide polymorphisms in microbial genomes', 'Song, Jian|Xu, Yan|White, Scott|Miller, Kevin W P|Wolinsky, Murray', 'Bioscience Division, Los Alamos National Laboratory, NM 87545, USA.|Bioscience Division, Los Alamos National Laboratory, NM 87545, USA.|Bioscience Division, Los Alamos National Laboratory, NM 87545, USA.|Bioscience Division, Los Alamos National Laboratory, NM 87545, USA.|Bioscience Division, Los Alamos National Laboratory, NM 87545, USA.', 'United States|United States|United States|United States|United States', 26, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Genome, Bacterial|Genome, Fungal|Internet|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti176', '15691853', 'Single nucleotide polymorphisms (SNPs) are the most abundant form of genetic variations in closely related microbial species, strains or isolates. Some SNPs confer selective advantages for microbial pathogens during infection and many others are powerful genetic markers for distinguishing closely related strains or isolates that could not be distinguished otherwise. To facilitate SNP discovery in microbial genomes, we have developed a web-based application, SNPsFinder, for genome-wide identification of SNPs. SNPsFinder takes multiple genome sequences as input to identify SNPs within homologous regions. It can also take contig sequences and sequence quality scores from ongoing sequencing projects for SNP prediction. SNPsFinder will use genome sequence annotation if available and map the predicted SNP regions to known genes or regions to assist further evaluation of the predicted SNPs for their functional significance. SNPsFinder can generate PCR primers for all predicted SNP regions according to users input parameters to facilitate experimental validation. The results from SNPsFinder analysis are accessible through the World Wide Web.'),
(71933, 2005, 'bio', 'An improved hidden Markov model for transmembrane protein detection and topology prediction and its applications to complete genomes', 'Kahsay, Robel Y|Gao, Guang|Liao, Li', 'Delaware Biotechnology Institute, Newark, 19715, USA.|Delaware Biotechnology Institute, Newark, 19715, USA.|Delaware Biotechnology Institute, Newark, 19715, USA.', 'United States|United States|United States', 134, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Chromosome Mapping|Computer Simulation|Markov Chains|Membrane Proteins|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Conformation|Sequence Homology, Amino Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti303', '15691854', 'Knowledge of the transmembrane helical topology can help identify binding sites and infer functions for membrane proteins. However, because membrane proteins are hard to solubilize and purify, only a very small amount of membrane proteins have structure and topology experimentally determined. This has motivated various computational methods for predicting the topology of membrane proteins.'),
(71934, 2005, 'bio', 'Evaluation of the gene-specific dye bias in cDNA microarray experiments', 'Martin-Magniette, Marie-Laure|Aubert, Julie|Cabannes, Eric|Daudin, Jean-Jacques', 'URGV UMR INRA 1165--CNRS 8114--UEVE, Evry, France. mlmartin@inapg.fr|URGV UMR INRA 1165--CNRS 8114--UEVE, Evry, France. mlmartin@inapg.fr|URGV UMR INRA 1165--CNRS 8114--UEVE, Evry, France. mlmartin@inapg.fr|URGV UMR INRA 1165--CNRS 8114--UEVE, Evry, France. mlmartin@inapg.fr', 'France|France|France|France', 0, 'Algorithms|Artifacts|Fluorescent Dyes|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti302', '15691855', 'In cDNA microarray experiments all samples are labeled with either Cy3 or Cy5. Systematic and gene-specific dye bias effects have been observed in dual-color experiments. In contrast to systematic effects which can be corrected by a normalization method, the gene-specific dye bias is not completely suppressed and may alter the conclusions about the differentially expressed genes.'),
(71935, 2005, 'bio', 'Empirical Bayes screening of many p-values with applications to microarray studies', 'Datta, Susmita|Datta, Somnath', 'Department of Mathematics and Statistics, Department of Biology, Georgia State University, Atlanta, 30303, USA.|Department of Mathematics and Statistics, Department of Biology, Georgia State University, Atlanta, 30303, USA.', 'Georgia|Georgia', 28, 'Algorithms|Bayes Theorem|Biomarkers, Tumor|Colorectal Neoplasms|Computer Simulation|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prognosis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti301', '15691856', 'Statistical tests for the detection of differentially expressed genes lead to a large collection of p-values one for each gene comparison. Without any further adjustment, these p-values may lead to a large number of false positives, simply because the number of genes to be tested is huge, which might mean wastage of laboratory resources. To account for multiple hypotheses, these p-values are typically adjusted using a single step method or a step-down method in order to achieve an overall control of the error rate (the so-called familywise error rate). In many applications, this may lead to an overly conservative strategy leading to too few genes being flagged.'),
(71936, 2005, 'bio', 'SpecAlign--processing and alignment of mass spectra datasets', 'Wong, Jason W H|Cagney, Gerard|Cartwright, Hugh M', 'Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, UK. jason.wong@chem.ox.ac.uk|Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, UK. jason.wong@chem.ox.ac.uk|Chemistry Department, Oxford University, Physical and Theoretical Chemistry Laboratory, UK. jason.wong@chem.ox.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 148, 'Algorithms|Databases, Protein|Gene Expression Profiling|Mass Spectrometry|Pattern Recognition, Automated|Proteome|Software', 'Journal Article', '10.1093/bioinformatics/bti300', '15691857', 'Pre-processing of chromatographic profile or mass spectral data is an important aspect of many types of proteomics and biomarker discovery experiments. Here we present a graphical computational tool, SpecAlign, that enables simultaneous visualization and manipulation of multiple datasets. SpecAlign not only provides all common processing functions, but also uniquely implements an algorithm that enables the complete alignment of each mass spectrum within a loaded dataset. We demonstrate its utility by aligning two datasets each containing six spectra, one set was acquired prior to instrument calibration and the other following calibration.'),
(71937, 2005, 'bio', 'Identification of GPI anchor attachment signals by a Kohonen self-organizing map', 'Fankhauser, Niklaus|Mäser, Pascal', 'Institute of Cell Biology, University of Bern, Switzerland.|Institute of Cell Biology, University of Bern, Switzerland.', 'Switzerland|Switzerland', 190, 'Algorithms|Animals|Binding Sites|Cell Membrane|Glycosylphosphatidylinositols|Humans|Membrane Proteins|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Signal Transduction|Software|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bti299', '15691858', 'Anchoring of proteins to the extracytosolic leaflet of membranes via C-terminal attachment of glycosylphosphatidylinositol (GPI) is ubiquitous and essential in eukaryotes. The signal for GPI-anchoring is confined to the C-terminus of the target protein. In order to identify anchoring signals in silico, we have trained neural networks on known GPI-anchored proteins, systematically optimizing input parameters.'),
(71938, 2005, 'bio', 'Efficient implementation of a generalized pair hidden Markov model for comparative gene finding', 'Majoros, W H|Pertea, M|Salzberg, S L', 'Bioinformatics Department, The Institute for Genomic Research, Rockville, MD, USA. bmajoros@tigr.org|Bioinformatics Department, The Institute for Genomic Research, Rockville, MD, USA. bmajoros@tigr.org|Bioinformatics Department, The Institute for Genomic Research, Rockville, MD, USA. bmajoros@tigr.org', 'United States|United States|United States', 0, 'Algorithms|Aspergillus|Chromosome Mapping|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Plant Proteins|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti297', '15691859', 'The increased availability of genome sequences of closely related organisms has generated much interest in utilizing homology to improve the accuracy of gene prediction programs. Generalized pair hidden Markov models (GPHMMs) have been proposed as one means to address this need. However, all GPHMM implementations currently available are either closed-source or the details of their operation are not fully described in the literature, leaving a significant hurdle for others wishing to advance the state of the art in GPHMM design.'),
(71939, 2005, 'bio', 'BioIE: extracting informative sentences from the biomedical literature', 'Divoli, Anna|Attwood, Teresa K', 'Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk|Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk', 'United Kingdom|United Kingdom', 0, 'Database Management Systems|Documentation|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Proteins|Proteomics|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti296', '15691860', 'BioIE is a rule-based system that extracts informative sentences relating to protein families, their structures, functions and diseases from the biomedical literaturE. Based on manual definition of templates and rules, it aims at precise sentence extraction rather than wide recall. After uploading source text or retrieving abstracts from MEDLINE, users can extract sentences based on predefined or user-defined template categories. BioIE also provides a brief insight into the syntactic and semantic context of the source-text by looking at word, N-gram and MeSH-term distributions. Important Applications of BioIE are in, for example, annotation of microarray data and of protein databases.'),
(71940, 2005, 'bio', 'SuperDrug: a conformational drug database', 'Goede, Andrean|Dunkel, Mathias|Mester, Nina|Frommel, Cornelius|Preissner, Robert', 'Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk|Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk|Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk|Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk|Faculty of Life Sciences and School of Computer Science, University of Manchester, UK. divoli@bioinf.man.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Graphics|Database Management Systems|Databases, Factual|Dictionaries, Pharmaceutic as Topic|Information Dissemination|Information Storage and Retrieval|Molecular Conformation|Pharmaceutical Preparations|Pharmacopoeias as Topic|Software|User-Computer Interface', 'Letter', '10.1093/bioinformatics/bti295', '15691861', 'Different resources exist for experimentally determined and computed three-dimensional (3D)-structures of low molecular weight structures but for approved drugs, no free, publicly accessible source of 3D-structures and conformers is available. Furthermore, for selection purposes or for correlation of structural similarity with medical application, the assignment of the Anatomical Therapeutic Chemical (ATC) classification codes to each structure according to the WHO-scheme would be desirable.'),
(71941, 2005, 'bio', 'Estimating misclassification error with small samples via bootstrap cross-validation', 'Fu, Wenjiang J|Carroll, Raymond J|Wang, Suojin', 'Department of Statistics, Texas A & M University, College Station, 77843, USA. wfu@stat.tamu.edu|Department of Statistics, Texas A & M University, College Station, 77843, USA. wfu@stat.tamu.edu|Department of Statistics, Texas A & M University, College Station, 77843, USA. wfu@stat.tamu.edu', 'United States|United States|United States', 101, 'Algorithms|Biomarkers, Tumor|Breast Neoplasms|Data Interpretation, Statistical|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prognosis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti294', '15691862', 'Estimation of misclassification error has received increasing attention in clinical diagnosis and bioinformatics studies, especially in small sample studies with microarray data. Current error estimation methods are not satisfactory because they either have large variability (such as leave-one-out cross-validation) or large bias (such as resubstitution and leave-one-out bootstrap). While small sample size remains one of the key features of costly clinical investigations or of microarray studies that have limited resources in funding, time and tissue materials, accurate and easy-to-implement error estimation methods for small samples are desirable and will be beneficial.'),
(71942, 2005, 'bio', 'DNA polymorphism detector: an automated tool that searches for allelic matches in public databases for discrepancies found in clone or cDNA sequences', 'Chang, Chih-Yu|LaBaer, Joshua', 'Chemical Biology Platform, Broad Institute of Harvard and MIT Cambridge, MA 02141-2023, USA.|Chemical Biology Platform, Broad Institute of Harvard and MIT Cambridge, MA 02141-2023, USA.', 'United States|United States', 2, 'Cloning, Molecular|DNA Mutational Analysis|DNA, Complementary|Database Management Systems|Databases, Nucleic Acid|Gene Frequency|Information Storage and Retrieval|Polymorphism, Genetic|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti298', '15695424', 'DNA polymorphism detector (DPD) is a new web application developed to help automate the process of cDNA clone validation. DPD identifies and highlights discrepancies between any cDNA clone sequence and its expected reference sequence. To determine if these differences correspond to natural genetic polymorphisms (versus artifacts introduced during clone production or evaluation), DPD uses the discrepancies, along with flanking sequences, to search GenBank for identical matching strings. If matching DNA sequences are found, DPD verifies that they are from the same gene. The application then reports the discrepancy as a polymorphism along with the corresponding GenBank reference information.'),
(71943, 2005, 'bio', 'PSLpred: prediction of subcellular localization of bacterial proteins', 'Bhasin, Manoj|Garg, Aarti|Raghava, G P S', 'Institute of Microbial Technology, Sector 39A, Chandigarh, India.|Institute of Microbial Technology, Sector 39A, Chandigarh, India.|Institute of Microbial Technology, Sector 39A, Chandigarh, India.', 'India|India|India', 0, 'Algorithms|Artificial Intelligence|Bacterial Proteins|Databases, Protein|Gene Expression Profiling|Internet|Sequence Analysis, Protein|Software|Subcellular Fractions', 'Evaluation Studies', '10.1093/bioinformatics/bti309', '15699023', 'We developed a web server PSLpred for predicting subcellular localization of gram-negative bacterial proteins with an overall accuracy of 91.2%. PSLpred is a hybrid approach-based method that integrates PSI-BLAST and three SVM modules based on compositions of residues, dipeptides and physico-chemical properties. The prediction accuracies of 90.7, 86.8, 90.3, 95.2 and 90.6% were attained for cytoplasmic, extracellular, inner-membrane, outer-membrane and periplasmic proteins, respectively. Furthermore, PSLpred was able to predict approximately 74% of sequences with an average prediction accuracy of 98% at RI = 5.'),
(71944, 2005, 'bio', 'Time accelerated Monte Carlo simulations of biological networks using the binomial tau-leap method', 'Chatterjee, Abhijit|Mayawala, Kapil|Edwards, Jeremy S|Vlachos, Dionisios G', 'Department of Chemical Engineering, University of Delaware, Newark, 19716, USA.|Department of Chemical Engineering, University of Delaware, Newark, 19716, USA.|Department of Chemical Engineering, University of Delaware, Newark, 19716, USA.|Department of Chemical Engineering, University of Delaware, Newark, 19716, USA.', 'United States|United States|United States|United States', 43, 'Algorithms|Cell Physiological Phenomena|Computer Simulation|Gene Expression Regulation|Models, Biological|Models, Statistical|Monte Carlo Method|Signal Processing, Computer-Assisted|Signal Transduction|Time Factors', 'Journal Article', '10.1093/bioinformatics/bti308', '15699024', 'Developing a quantitative understanding of intracellular networks requires simulations and computational analyses. However, traditional differential equation modeling tools are often inadequate due to the stochasticity of intracellular reaction networks that can potentially influence the phenotypic characteristics. Unfortunately, stochastic simulations are computationally too intense for most biological systems. Herein, we have utilized the recently developed binomial tau-leap method to carry out stochastic simulations of the epidermal growth factor receptor induced mitogen activated protein kinase cascade. Results indicate that the binomial tau-leap method is computationally 100-1000 times more efficient than the exact stochastic simulation algorithm of Gillespie. Furthermore, the binomial tau-leap method avoids negative populations and accurately captures the species populations along with their fluctuations despite the large difference in their size.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71945, 2005, 'bio', 'A comparative analysis of relative occurrence of transcription factor binding sites in vertebrate genomes and gene promoter areas', 'Stepanova, Maria|Tiazhelova, Tatiana|Skoblov, Mikle|Baranova, Ancha', 'Center for Biomedical Genomics and BioInformatics, Molecular and Microbiology Department, College of Arts and Sciences, George Mason University, Fairfax, VA 22031, USA.|Center for Biomedical Genomics and BioInformatics, Molecular and Microbiology Department, College of Arts and Sciences, George Mason University, Fairfax, VA 22031, USA.|Center for Biomedical Genomics and BioInformatics, Molecular and Microbiology Department, College of Arts and Sciences, George Mason University, Fairfax, VA 22031, USA.|Center for Biomedical Genomics and BioInformatics, Molecular and Microbiology Department, College of Arts and Sciences, George Mason University, Fairfax, VA 22031, USA.', 'United States|United States|United States|United States', 18, 'Animals|Binding Sites|Chromosome Mapping|Evolution, Molecular|Promoter Regions, Genetic|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity|Transcription Factors|Transcriptional Activation|Vertebrates', 'Journal Article', '10.1093/bioinformatics/bti307', '15699025', 'The detection of transcription factor binding sites (TFBS) in genomic sequences is a basic task for elucidating the transcriptional aspects of gene regulation. Evaluation procedures applicable to the TFBS prediction outputs need improvement. Predicted TFBS located outside of the transcription associated areas are often neglected from the functional and the evolutionary points of view, therefore deserving a systematic overview.'),
(71946, 2005, 'bio', 'MPSS: an integrated database system for surveying a set of proteins', 'Hao, Pei|He, Wei-Zhong|Huang, Yin|Ma, Liang-Xiao|Xu, Ying|Xi, Hong|Wang, Chuan|Liu, Bo-Shu|Wang, Jin-Miao|Li, Yi-Xue|Zhong, Yang', 'School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.|School of Life Sciences, Fudan University, Shanghai, China.', 'China|China|China|China|China|China|China|China|China|China|China', 0, 'Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Proteins|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti306', '15699026', 'We design and implement an integrated database system called multi-protein survey system (MPSS), which provides a platform to retrieve information about many proteins at a time. This system integrates several important and widely used databases including SwissProt, TrEMBL, PDB and InterPro, plus useful references such as GO and KEGG to other databases. Users may submit a group of protein IDs, entry names, SwissProt/TrEMBL accession numbers or GenBank GIs through MPSS web interface, and obtain protein annotation information from public databases and pre-computed molecular properties speedily. MPSS can also supply comprehensive information about query proteins, including 3D structures, domains, pathway, gene ontology and visual presentation of mapping to the GO tree and KEGG pathway, to provide an up-to-date view of available knowledge with regard to the structures and molecular functions of proteins under study.'),
(71947, 2005, 'bio', 'Accurate extraction of functional associations between proteins based on common interaction partners and common domains', 'Okada, Kinya|Kanaya, Shigehiko|Asai, Kiyoshi', 'Graduate School of Information Sciences, Nara Institute of Science and Technology, Ikoma, Japan. okada-k@cb.k.u-tokyo.ac.jp|Graduate School of Information Sciences, Nara Institute of Science and Technology, Ikoma, Japan. okada-k@cb.k.u-tokyo.ac.jp|Graduate School of Information Sciences, Nara Institute of Science and Technology, Ikoma, Japan. okada-k@cb.k.u-tokyo.ac.jp', 'Japan|Japan|Japan', 16, 'Algorithms|Amino Acid Sequence|Binding Sites|Databases, Protein|Gene Expression Regulation|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Signal Transduction|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti305', '15699027', 'Genomic and proteomic approaches have accumulated a huge amount of data which provide clues to protein function. However, interpreting single omic data for predicting uncharacterized protein functions has been a challenging task, because the data contain a lot of false positives. To overcome this problem, methods for integrating data from various omic approaches are needed for more accurate function prediction.'),
(71948, 2005, 'bio', 'ExPrimer: to design primers from exon--exon junctions', 'Sandhu, Kuljeet S|Acharya, Kshitish K', 'Institute of Bioinformatics and Applied Biotechnology (IBAB) G-05, Tech Park Mall, ITPL, Bangalore, India.|Institute of Bioinformatics and Applied Biotechnology (IBAB) G-05, Tech Park Mall, ITPL, Bangalore, India.', 'India|India', 6, 'Algorithms|Computer-Aided Design|DNA Primers|Exons|In Situ Hybridization|RNA, Messenger|Reverse Transcriptase Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bti304', '15699028', 'ExPrimer is a web-based computer program to design primers mainly from a specified exon-exon junction (E-E-jn) of a gene of interest. The tool suggests the optimum primer-pair(s) of which the right (reverse) primer represents a particular E-E-jn of the mRNA. The product length decides the location of the left primer. The results also include all other primer pairs considered and their scores. ExPrimer can use the NCBI BLASTn program for sequence specificity of primers. The tool is useful in many areas of molecular biology research that involve hybridization of short sequences with mRNA or cDNA.'),
(71949, 2005, 'bio', 'Inference of missing SNPs and information quantity measurements for haplotype blocks', 'Su, Shih-Chieh|Kuo, C-C Jay|Chen, Ting', 'Department of Electrical Engineering, University of Southern California, Los Angeles, 90089, USA.|Department of Electrical Engineering, University of Southern California, Los Angeles, 90089, USA.|Department of Electrical Engineering, University of Southern California, Los Angeles, 90089, USA.', 'United States|United States|United States', 0, 'Algorithms|Artifacts|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Haplotypes|Information Storage and Retrieval|Linkage Disequilibrium|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti261', '15699029', 'Missing data in genotyping single nucleotide polymorphism (SNP) spots are common. High-throughput genotyping methods usually have a high rate of missing data. For example, the published human chromosome 21 data by Patil et al. contains about 20% missing SNPs. Inferring missing SNPs using the haplotype block structure is promising but difficult because the haplotype block boundaries are not well defined. Here we propose a global algorithm to overcome this difficulty.'),
(71950, 2005, 'bio', 'Q-SiteFinder: an energy-based method for the prediction of protein-ligand binding sites', 'Laurie, Alasdair T R|Jackson, Richard M', 'School of Biochemistry and Microbiology, University of Leeds, UK.|School of Biochemistry and Microbiology, University of Leeds, UK.', 'United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Databases, Protein|Energy Transfer|Ligands|Models, Chemical|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti315', '15701681', 'Identifying the location of ligand binding sites on a protein is of fundamental importance for a range of applications including molecular docking, de novo drug design and structural identification and comparison of functional sites. Here, we describe a new method of ligand binding site prediction called Q-SiteFinder. It uses the interaction energy between the protein and a simple van der Waals probe to locate energetically favourable binding sites. Energetically favourable probe sites are clustered according to their spatial proximity and clusters are then ranked according to the sum of interaction energies for sites within each cluster.'),
(71951, 2005, 'bio', 'Protein function prediction using the Protein Link EXplorer (PLEX)', 'Date, Shailesh V|Marcotte, Edward M', 'Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, 1 University Station, A4800, Austin, TX 78712-1064, USA.|Center for Systems and Synthetic Biology, Institute for Cellular and Molecular Biology, 1 University Station, A4800, Austin, TX 78712-1064, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computer Graphics|Evolution, Molecular|Molecular Sequence Data|Phylogeny|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti313', '15701682', 'We introduce the Protein Link EXplorer (PLEX), a web-based environment that allows the construction of a phylogenetic profile for any given amino acid sequence, and its comparison with profiles of approximately 350,000 predicted genes from 89 genomes, as a means of interactively identifying functionally linked genes and predicting protein function. PLEX can be searched iteratively and also enables searches for chromosomal gene neighbors and Rosetta Stone linkages. PLEX search results are accompanied by quantitative estimates of linkage confidence, enabling users to take advantage of coinheritance, operon and gene fusion-based methods for inferring gene function and reconstructing cellular systems and pathways.'),
(71952, 2005, 'bio', 'The Graphical Query Language: a tool for analysis of gene expression time-courses', 'Costa, Ivan G|Schönhuth, Alexander|Schliep, Alexander', 'Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.|Department of Computational Molecular Biology, Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany.', 'Germany|Germany|Germany', 19, 'Computer Graphics|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Programming Languages|Software|Time Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti311', '15701683', 'The Graphical Query Language (GQL) is a set of tools for the analysis of gene expression time-courses. They allow a user to pre-process the data, to query it for interesting patterns, to perform model-based clustering or mixture estimation, to include subsequent refinements of clusters and, finally, to use other biological resources to evaluate the results. Analyses are carried out in a graphical and interactive environment, allowing expert intervention in all stages of the data analysis.'),
(71953, 2005, 'bio', 'Bio-Object, a stochastic simulator for post-transcriptional regulation', 'Ohki, Nobukazu|Hagiwara, Masatoshi', 'Department of Functional Genomics, Medical Research Institute, 1-5-45 Yushima, Tokyo 113-0034, Japan.|Department of Functional Genomics, Medical Research Institute, 1-5-45 Yushima, Tokyo 113-0034, Japan.', 'Japan|Japan', 0, 'Algorithms|Animals|Biological Clocks|Circadian Rhythm|Computer Simulation|Drosophila melanogaster|Gene Expression Regulation|Models, Biological|Models, Statistical|Signal Transduction|Software|Stochastic Processes|Transcription Factors|Transcriptional Activation', 'Evaluation Studies', '10.1093/bioinformatics/bti316', '15705653', 'Recently, biologists learnt that the transport and degradation of transcribed mRNA and protein present critically important steps for the regulation of gene expression through extensive studies of RNA interference, none-sense mediated decay and ubiquitination. However, adequate consideration of these factors has not been done in the past in in silico analysis compared with transcriptional regulations.'),
(71954, 2005, 'bio', 'Estimating cancer survival and clinical outcome based on genetic tumor progression scores', 'Rahnenführer, Jörg|Beerenwinkel, Niko|Schulz, Wolfgang A|Hartmann, Christian|von Deimling, Andreas|Wullich, Bernd|Lengauer, Thomas', 'Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de|Max-Planck Institute for Informatics, Stuhlsatzenhausweg 85, D-66123 Saarbrücken, Germany. rahnenfj@mpi-sb.mpg.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 44, 'Biomarkers, Tumor|Chromosome Aberrations|Diagnosis, Computer-Assisted|Disease Progression|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Genetics, Population|Humans|Neoplasms|Prognosis|Proportional Hazards Models|Risk Assessment|Risk Factors|Survival Analysis|Survival Rate|Treatment Outcome', 'Evaluation Studies', '10.1093/bioinformatics/bti312', '15705654', 'In cancer research, prediction of time to death or relapse is important for a meaningful tumor classification and selecting appropriate therapies. Survival prognosis is typically based on clinical and histological parameters. There is increasing interest in identifying genetic markers that better capture the status of a tumor in order to improve on existing predictions. The accumulation of genetic alterations during tumor progression can be used for the assessment of the genetic status of the tumor. For modeling dependences between the genetic events, evolutionary tree models have been applied.'),
(71955, 2005, 'bio', 'PowerMarker: an integrated analysis environment for genetic marker analysis', 'Liu, Kejun|Muse, Spencer V', 'Bioinformatics Research Center, North Carolina State University Raleigh, 27695-7566, USA.|Bioinformatics Research Center, North Carolina State University Raleigh, 27695-7566, USA.', 'United States|United States', 0, 'Algorithms|Computer Graphics|DNA Mutational Analysis|Gene Frequency|Genetic Markers|Genetics, Population|Linkage Disequilibrium|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti282', '15705655', 'PowerMarker delivers a data-driven, integrated analysis environment (IAE) for genetic data. The IAE integrates data management, analysis and visualization in a user-friendly graphical user interface. It accelerates the analysis lifecycle and enables users to maintain data integrity throughout the process. An ever-growing list of more than 50 different statistical analyses for genetic markers has been implemented in PowerMarker.'),
(71956, 2005, 'bio', 'Divide-and-conquer approach for the exemplar breakpoint distance', 'Nguyen, C Thach|Tay, Y C|Zhang, Louxin', 'School of Computing, National University of Singapore, 117543, Singapore.|School of Computing, National University of Singapore, 117543, Singapore.|School of Computing, National University of Singapore, 117543, Singapore.', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Chromosome Mapping|DNA, Bacterial|Gene Rearrangement|Genome, Bacterial|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti327', '15713729', 'A one-to-one correspondence between the sets of genes in the two genomes being compared is necessary for the notions of breakpoint and reversal distances. To compare genomes where there are paralogous genes, Sankoff formulated the exemplar distance problem as a general version of the genome rearrangement problem. Unfortunately, the problem is NP-hard even for the breakpoint distance.'),
(71957, 2005, 'bio', 'MamMiBase: a mitochondrial genome database for mammalian phylogenetic studies', 'Vasconcelos, Ana Tereza R de|Guimarães, Ana Carolina R|Castelletti, Carlos Henrique M|Caruso, Célia S|Ribeiro, Cristina|Yokaichiya, Fabiano|Armôa, Geraldo R G|Pereira, Gislaine da Silva P|da Silva, Israel T|Schrago, Carlos G|Fernandes, Adélia L V|da Silveira, Aline R|Carneiro, André G|Carvalho, Bruno M|Viana, Carlos J M|Gramkow, Daniel|Lima, Franklin J|Corrêa, Luiz G G|Mudado, Maurício de A|Nehab-Hess, Pablo|Souza, Rangel de|Corrêa, Régis L|Russo, Claudia A M', 'Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br|Laboratório Nacional de Computação Científica LNCC/MCT, Petrópolis, RJ, Brazil. atrv@lncc.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Br', 0, 'Chromosome Mapping|DNA, Mitochondrial|Databases, Nucleic Acid|Internet|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti326', '15713730', 'MamMiBase, the mammalian mitochondrial genome database, is a relational database of complete mitochondrial genome sequences of mammalian species. The database is useful for phylogenetic analysis, since it allows a ready retrieval of nucleotide and aminoacid individual alignments, in three different formats (NEXUS for PAUP program, for MEGA program and for PHYLIP program) of the 13 protein coding mitochondrial genes. The user may download the sequences that are useful for him/her based on their parameters values, such as sequence length, p-distances, base content, transition transversion ratio, gamma, which are also given by MamMiBase. A simple phylogenetic tree (neighbor-joining tree with Jukes Cantor distance) is also available for download, useful for parameter calculations and other simple tasks.'),
(71958, 2005, 'bio', 'Tree pattern matching in phylogenetic trees: automatic search for orthologs or paralogs in homologous gene sequence databases', 'Dufayard, Jean-François|Duret, Laurent|Penel, Simon|Gouy, Manolo|Rechenmann, François|Perrière, Guy', 'INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.|INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.|INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.|INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.|INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.|INRIA Rhône-Alpes 38334 Montbonnot, Saint Ismier Cedex, France.', 'France|France|France|France|France|France', 117, 'Algorithms|Artificial Intelligence|Biological Evolution|Database Management Systems|Evolution, Molecular|Pattern Recognition, Automated|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti325', '15713731', 'Comparative sequence analysis is widely used to study genome function and evolution. This approach first requires the identification of homologous genes and then the interpretation of their homology relationships (orthology or paralogy). To provide help in this complex task, we developed three databases of homologous genes containing sequences, multiple alignments and phylogenetic trees: HOBACGEN, HOVERGEN and HOGENOM. In this paper, we present two new tools for automating the search for orthologs or paralogs in these databases.'),
(71959, 2005, 'bio', 'Boosting proportional hazards models using smoothing splines, with applications to high-dimensional microarray data', 'Li, Hongzhe|Luan, Yihui', 'Rowe Program in Human Genetics, University of California, Davis, CA 95616, USA. hli@ucdavis.edu|Rowe Program in Human Genetics, University of California, Davis, CA 95616, USA. hli@ucdavis.edu', 'United States|United States', 49, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Gene Expression Profiling|Humans|Lymphoma, B-Cell|Neoplasm Proteins|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Prognosis|Proportional Hazards Models|Reproducibility of Results|Risk Assessment|Risk Factors|Sensitivity and Specificity|Survival Analysis|Survival Rate', 'Journal Article', '10.1093/bioinformatics/bti324', '15713732', 'An important area of research in the postgenomics era is to relate high-dimensional genetic or genomic data to various clinical phenotypes of patients. Due to large variability in time to certain clinical events among patients, studying possibly censored survival phenotypes can be more informative than treating the phenotypes as categorical variables. Due to high dimensionality and censoring, building a predictive model for time to event is more difficult than the classification/linear regression problem. We propose to develop a boosting procedure using smoothing splines for estimating the general proportional hazards models. Such a procedure can potentially be used for identifying non-linear effects of genes on the risk of developing an event.'),
(71960, 2005, 'bio', 'Using sequence compression to speedup probabilistic profile matching', 'Freschi, Valerio|Bogliolo, Alessandro', 'Information Science and Technology Institute, University of Urbino, 61029 Urbino, Italy.|Information Science and Technology Institute, University of Urbino, 61029 Urbino, Italy.', 'Italy|Italy', 13, 'Algorithms|Data Compression|Gene Expression Profiling|Models, Chemical|Models, Statistical|Sequence Alignment|Sequence Analysis|Sequence Homology', 'Comparative Study', '10.1093/bioinformatics/bti323', '15713733', 'Matching a biological sequence against a probabilistic pattern (or profile) is a common task in computational biology. A probabilistic profile, represented as a scoring matrix, is more suitable than a deterministic pattern to retain the peculiarities of a given segment of a family of biological sequences. Brute-force algorithms take O(NP) to match a sequence of N characters against a profile of length P < N.'),
(71961, 2005, 'bio', 'FastContact: rapid estimate of contact and binding free energies', 'Camacho, Carlos J|Zhang, Chao', 'Department of Computational Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA. ccamacho@pitt.edu|Department of Computational Biology, University of Pittsburgh, Pittsburgh, PA 15261, USA. ccamacho@pitt.edu', 'United States|United States', 0, 'Algorithms|Amino Acids|Binding Sites|Computer Simulation|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bti322', '15713734', 'Interaction free energies are crucial for analyzing binding propensities in proteins. Although the problem of computing binding free energies remains open, approximate estimates have become very useful for filtering potential binding complexes. We report on the implementation of a fast computational estimate of the binding free energy based on a statistically determined desolvation contact potential and Coulomb electrostatics with a distance-dependent dielectric constant, and validated in the Critical Assessment of PRotein Interactions experiment. The application also reports residue contact free energies that rapidly highlight the hotspots of the interaction.'),
(71962, 2005, 'bio', 'Datamonkey: rapid detection of selective pressure on individual sites of codon alignments', 'Pond, Sergei L Kosakovsky|Frost, Simon D W', 'Antiviral Research Center, University of California, San Diego, CA 92103, USA. spond@ucsd.edu|Antiviral Research Center, University of California, San Diego, CA 92103, USA. spond@ucsd.edu', 'United States|United States', 472, 'Algorithms|Base Sequence|Chromosome Mapping|Codon|Evolution, Molecular|Internet|Molecular Sequence Data|Selection, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti320', '15713735', 'Datamonkey is a web interface to a suite of cutting edge maximum likelihood-based tools for identification of sites subject to positive or negative selection. The methods range from very fast data exploration to the some of the most complex models available in public domain software, and are implemented to run in parallel on a cluster of computers.'),
(71963, 2005, 'bio', 'Bayesian model averaging: development of an improved multi-class, gene selection and classification tool for microarray data', 'Yeung, Ka Yee|Bumgarner, Roger E|Raftery, Adrian E', 'Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu|Department of Microbiology, University of Washington, Seattle, WA 98195, USA. kayee@u.washington.edu', 'United States|United States|United States', 195, 'Algorithms|Artificial Intelligence|Bayes Theorem|Biomarkers, Tumor|Computer Simulation|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/bti319', '15713736', 'Selecting a small number of relevant genes for accurate classification of samples is essential for the development of diagnostic tests. We present the Bayesian model averaging (BMA) method for gene selection and classification of microarray data. Typical gene selection and classification procedures ignore model uncertainty and use a single set of relevant genes (model) to predict the class. BMA accounts for the uncertainty about the best set to choose by averaging over multiple models (sets of potentially overlapping relevant genes).'),
(71964, 2005, 'bio', 'Applications of beta-mixture models in bioinformatics', 'Ji, Yuan|Wu, Chunlei|Liu, Ping|Wang, Jing|Coombes, Kevin R', 'Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, 77030, USA.|Department of Biostatistics, The University of Texas M.D. Anderson Cancer Center, Houston, 77030, USA.', 'United States|United States|United States|United States|United States', 0, 'Animals|Cell Physiological Phenomena|Computational Biology|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Biological|Models, Statistical|Proteome|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bti318', '15713737', 'We propose a beta-mixture model approach to solve a variety of problems related to correlations of gene-expression levels. For example, in meta-analyses of microarray gene-expression datasets, a threshold value of correlation coefficients for gene-expression levels is used to decide whether gene-expression levels are strongly correlated across studies. Ad hoc threshold values such as 0.5 are often used. In this paper, we use a beta-mixture model approach to divide the correlation coefficients into several populations so that the large correlation coefficients can be identified. Another important application of the proposed method is in finding co-expressed genes. Two examples are provided to illustrate both applications. Through our analysis, we also discover that the popular model selection criteria BIC and AIC are not suitable for the beta-mixture model. To determine the number of components in the mixture model, we suggest an alternative criterion, ICL-BIC, which is shown to perform better in selecting the correct mixture model.'),
(71965, 2005, 'bio', 'A knowledge-driven approach to cluster validity assessment', 'Bolshakova, Nadia|Azuaje, Francisco|Cunningham, Pádraig', 'Department of Computer Science, Trinity College Dublin, Dublin 2, Ireland. nadia.bolshakova@cs.tcd.ie|Department of Computer Science, Trinity College Dublin, Dublin 2, Ireland. nadia.bolshakova@cs.tcd.ie|Department of Computer Science, Trinity College Dublin, Dublin 2, Ireland. nadia.bolshakova@cs.tcd.ie', 'Ireland|Ireland|Ireland', 46, 'Algorithms|Artificial Intelligence|Cluster Analysis|Database Management Systems|Databases, Protein|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Saccharomyces cerevisiae Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti317', '15713738', 'This paper presents an approach to assessing cluster validity based on similarity knowledge extracted from the Gene Ontology.'),
(71966, 2005, 'bio', 'Prediction methods and databases within chemoinformatics: emphasis on drugs and drug candidates', 'Jónsdóttir, Svava Osk|Jørgensen, Flemming Steen|Brunak, Søren', 'Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark. svava@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark. svava@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark. svava@cbs.dtu.dk', 'Denmark|Denmark|Denmark', 77, 'Chemistry, Pharmaceutical|Computational Biology|Databases, Factual|Drug Design|Models, Chemical|Models, Molecular|Pharmaceutical Preparations|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti314', '15713739', 'To gather information about available databases and chemoinformatics methods for prediction of properties relevant to the drug discovery and optimization process.'),
(71967, 2005, 'bio', 'ESTviewer: a web interface for visualizing mouse, rat, cattle, pig and chicken conserved ESTs in human genes and human alternatively spliced variants', 'Chen, Feng-Chi|Chuang, Trees-Juen', 'Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.|Genomics Research Center, Academia Sinica, Taipei 11529, Taiwan.', '-|-', 3, 'Animals|Cattle|Chickens|Chromosome Mapping|Computer Graphics|Conserved Sequence|Evolution, Molecular|Expressed Sequence Tags|Humans|Internet|Mice|Rats|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Species Specificity|Swine|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti332', '15722373', 'ESTviewer is a web application for interactively visualizing human gene structures, with emphasis on mammalian and avian expressed sequence tags (ESTs) that are conserved in the human genome and alternatively spliced (AS) variants. AS variants from the UCSC, Vega and PSEP annotations are presented in this application for comparison. EST data from six species, human, mouse, rat, cattle, pig and chicken, are mapped to the human genome to show cross-species EST conservation in annotated exonic and intronic regions. Cross-species EST conservation is evolutionarily and functionally important because it represents the effects of selection pressure on genic regions and transcriptome over evolutionary time. Emphatically, ESTviewer provides a convenient tool to compare highly conserved non-human ESTs and human AS variants. The application takes human gene accession Ids or coordinates of genomic sequences as inputs and presents annotated gene structures and their AS variants. In addition, the lengths and percentages of human genic regions covered by ESTs are displayed to show the level of EST coverage of different species. The percentages of the UCSC, Vega and PSEP annotated exons covered by ESTs of the six studied species are also displayed in the interface.'),
(71968, 2005, 'bio', 'Recoverable one-dimensional encoding of three-dimensional protein structures', 'Kinjo, Akira R|Nishikawa, Ken', 'Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Japan. akinjo@genes.nig.ac.jp|Center for Information Biology and DNA Data Bank of Japan, National Institute of Genetics, Mishima 411-8540, Japan. akinjo@genes.nig.ac.jp', 'Japan|Japan', 0, 'Amino Acid Sequence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti330', '15722374', 'One-dimensional (1D) structures of proteins such as secondary structure and contact number provide intuitive pictures to understand how the native three-dimensional (3D) structure of a protein is encoded in the amino acid sequence. However, it is still not clear whether a given set of 1D structures contains sufficient information for recovering the underlying 3D structure. Here we show that the 3D structure of a protein can be recovered from a set of three types of 1D structures, namely, secondary structure, contact number and residue-wise contact order which is introduced here for the first time. Using simulated annealing molecular dynamics simulations, the structures satisfying the given native 1D structural restraints were sought for 16 proteins of various structural classes and of sizes ranging from 56 to 146 residues. By selecting the structures best satisfying the restraints, all the proteins showed a coordinate RMS deviation of <4 A from the native structure, and, for most of them, the deviation was even <2 A. The present result opens a new possibility to protein structure prediction and our understanding of the sequence-structure relationship.'),
(71969, 2005, 'bio', 'Sorting points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices', 'Tsafrir, D|Tsafrir, I|Ein-Dor, L|Zuk, O|Notterman, D A|Domany, E', 'Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il|Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il|Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il|Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il|Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il|Department of Complex Systems, Weizmann Institute of Science, Rehovot 76100, Israel. fedafna@wisemail.weizmann.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel', 0, 'Algorithms|Biomarkers, Tumor|Cluster Analysis|Colonic Neoplasms|Computer Graphics|Computer Simulation|Data Interpretation, Statistical|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Information Storage and Retrieval|Models, Biological|Neoplasm Proteins|Pattern Recognition, Automated|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti329', '15722375', 'We introduce a novel unsupervised approach for the organization and visualization of multidimensional data. At the heart of the method is a presentation of the full pairwise distance matrix of the data points, viewed in pseudocolor. The ordering of points is iteratively permuted in search of a linear ordering, which can be used to study embedded shapes. Several examples indicate how the shapes of certain structures in the data (elongated, circular and compact) manifest themselves visually in our permuted distance matrix. It is important to identify the elongated objects since they are often associated with a set of hidden variables, underlying continuous variation in the data. The problem of determining an optimal linear ordering is shown to be NP-Complete, and therefore an iterative search algorithm with O(n3) step-complexity is suggested. By using sorting points into neighborhoods, i.e. SPIN to analyze colon cancer expression data we were able to address the serious problem of sample heterogeneity, which hinders identification of metastasis related genes in our data. Our methodology brings to light the continuous variation of heterogeneity--starting with homogeneous tumor samples and gradually increasing the amount of another tissue. Ordering the samples according to their degree of contamination by unrelated tissue allows the separation of genes associated with irrelevant contamination from those related to cancer progression.'),
(71970, 2005, 'bio', 'MtbRegList, a database dedicated to the analysis of transcriptional regulation in Mycobacterium tuberculosis', 'Jacques, Pierre-Etienne|Gervais, Alain L|Cantin, Mathieu|Lucier, Jean-Francois|Dallaire, Guillaume|Drouin, Geneviève|Gaudreau, Luc|Goulet, Jean|Brzezinski, Ryszard', 'Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.|Département de Biologie, Université de Sherbrooke, Sherbrooke, J1K 2R1, Quebec, Canada.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Bacterial Proteins|Chromosome Mapping|DNA, Bacterial|Databases, Genetic|Internet|Mycobacterium tuberculosis|Sequence Analysis, DNA|Transcriptional Activation|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti321', '15722376', 'MtbRegList is a database dedicated to the analysis of gene expression and regulation data in Mycobacterium tuberculosis. It is designed to contain predicted and characterized regulatory DNA motifs cross-referenced with corresponding transcription factor(s), and experimentally identified transcription start sites. MtbRegList can also handle flexible and complex genomic search requests, besides having a noteworthy browsing capability.'),
(71971, 2005, 'bio', 'GMAP: a genomic mapping and alignment program for mRNA and EST sequences', 'Wu, Thomas D|Watanabe, Colin K', 'Department of Bioinformatics Genentech, Inc., South San Francisco, CA 94080, USA. twu@gene.com|Department of Bioinformatics Genentech, Inc., South San Francisco, CA 94080, USA. twu@gene.com', 'United States|United States', 1013, 'Algorithms|Chromosome Mapping|Expressed Sequence Tags|Genome, Human|Humans|RNA Splice Sites|RNA, Messenger|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti310', '15728110', 'We introduce GMAP, a standalone program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.'),
(71972, 2005, 'bio', 'Mapping genome-genome epistasis: a high-dimensional model', 'Cui, Yuehua|Wu, Rongling', 'Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States', 0, 'Chromosome Mapping|Computer Simulation|Models, Genetic|Models, Statistical|Oryza|Phenotype|Quantitative Trait Loci|Seeds', 'Evaluation Studies', '10.1093/bioinformatics/bti342', '15728111', 'The proper development of any organ or tissue requires the coordinated expression of its underlying genes that can be located on different genomes present in an organism. For instance, each step in the development of seed for a higher plant is the consequence of gene interactions from the maternal, embryo and endosperm genomes.'),
(71973, 2005, 'bio', 'Background correction for cDNA microarray images using the TV+L1 model', 'Yin, Wotao|Chen, Terrence|Zhou, Sean Xiang|Chakraborty, Amit', 'Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. wy2002@columbia.edu|Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. wy2002@columbia.edu|Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. wy2002@columbia.edu|Department of Industrial Engineering and Operations Research, Columbia University, New York, NY 10027, USA. wy2002@columbia.edu', 'United States|United States|United States|United States', 45, 'Algorithms|Computer Simulation|Gene Expression Profiling|Image Enhancement|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti341', '15728112', 'Background correction is an important preprocess in cDNA microarray data analysis. A variety of methods have been used for this purpose. However, many kinds of backgrounds, especially inhomogeneous ones, cannot be estimated correctly using any of the existing methods. In this paper, we propose the use of the TV+L1 model, which minimizes the total variation (TV) of the image subject to an L1-fidelity term, to correct background bias. We demonstrate its advantages over the existing methods by both analytically discussing its properties and numerically comparing it with morphological opening.'),
(71974, 2005, 'bio', 'An evolution based classifier for prediction of protein interfaces without using protein structures', 'Res, I|Mihalek, I|Lichtarge, O', 'Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.|Department of Molecular and Human Genetics, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, USA.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Evolution, Molecular|Molecular Sequence Data|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti340', '15728113', 'The number of available protein structures still lags far behind the number of known protein sequences. This makes it important to predict which residues participate in protein-protein interactions using only sequence information. Few studies have tackled this problem until now.'),
(71975, 2005, 'bio', 'Selective integration of multiple biological data for supervised network inference', 'Kato, Tsuyoshi|Tsuda, Koji|Asai, Kiyoshi', 'Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan. kato-tsuyoshi@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan. kato-tsuyoshi@aist.go.jp|Computational Biology Research Center, National Institute of Advanced Industrial Science and Technology (AIST), Tokyo, Japan. kato-tsuyoshi@aist.go.jp', 'Japan|Japan|Japan', 48, 'Algorithms|Artificial Intelligence|Computer Simulation|Database Management Systems|Databases, Protein|Gene Expression Regulation|Information Storage and Retrieval|Models, Biological|Models, Statistical|Protein Interaction Mapping|Signal Transduction|Software|Systems Integration|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bti339', '15728114', 'Inferring networks of proteins from biological data is a central issue of computational biology. Most network inference methods, including Bayesian networks, take unsupervised approaches in which the network is totally unknown in the beginning, and all the edges have to be predicted. A more realistic supervised framework, proposed recently, assumes that a substantial part of the network is known. We propose a new kernel-based method for supervised graph inference based on multiple types of biological datasets such as gene expression, phylogenetic profiles and amino acid sequences. Notably, our method assigns a weight to each type of dataset and thereby selects informative ones. Data selection is useful for reducing data collection costs. For example, when a similar network inference problem must be solved for other organisms, the dataset excluded by our algorithm need not be collected.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71976, 2005, 'bio', 'MaSTerClass: a case-based reasoning system for the classification of biomedical terms', 'Spasic, Irena|Ananiadou, Sophia|Tsujii, Junichi', 'School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester M60 1QD, UK. i.spasic@manchester.ac.uk|School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester M60 1QD, UK. i.spasic@manchester.ac.uk|School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester M60 1QD, UK. i.spasic@manchester.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 2, 'Abstracting and Indexing as Topic|Artificial Intelligence|Biomedical Research|Databases, Bibliographic|Information Storage and Retrieval|Internet|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Semantics|Software|Subject Headings|Terminology as Topic|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti338', '15728115', 'The sheer volume of textually described biomedical knowledge exerts the need for natural language processing (NLP) applications in order to allow flexible and efficient access to relevant information. Specialized semantic networks (such as biomedical ontologies, terminologies or semantic lexicons) can significantly enhance these applications by supplying the necessary terminological information in a machine-readable form. With the explosive growth of bio-literature, new terms (representing newly identified concepts or variations of the existing terms) may not be explicitly described within the network and hence cannot be fully exploited by NLP applications. Linguistic and statistical clues can be used to extract many new terms from free text. The extracted terms still need to be correctly positioned relative to other terms in the network. Classification as a means of semantic typing represents the first step in updating a semantic network with new terms.'),
(71977, 2005, 'bio', 'Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons', 'Morris, Richard J|Najmanovich, Rafael J|Kahraman, Abdullah|Thornton, Janet M', 'EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acids|Binding Sites|Computer Simulation|Ligands|Models, Chemical|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti337', '15728116', 'An increasing number of protein structures are being determined for which no biochemical characterization is available. The analysis of protein structure and function assignment is becoming an unexpected challenge and a major bottleneck towards the goal of well-annotated genomes. As shape plays a crucial role in biomolecular recognition and function, the examination and development of shape description and comparison techniques is likely to be of prime importance for understanding protein structure-function relationships.'),
(71978, 2005, 'bio', 'A Gibbs sampler for identification of symmetrically structured, spaced DNA motifs with improved estimation of the signal length', 'Favorov, A V|Gelfand, M S|Gerasimova, A V|Ravcheev, D A|Mironov, A A|Makeev, V J', 'Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org|Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org|Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org|Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org|Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org|Laboratory for Bioinformatics, State Scientific Centre GosNIIGenetika, 1st Dorozhny pr. 1, Moscow, 117545, Russia. favorov@sensi.org', '-|-|-|-|-|-', 74, 'Algorithms|Bacterial Outer Membrane Proteins|Base Sequence|DNA-Binding Proteins|Escherichia coli Proteins|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Repetitive Sequences, Nucleic Acid|Repressor Proteins|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti336', '15728117', 'Transcription regulatory protein factors often bind DNA as homo-dimers or hetero-dimers. Thus they recognize structured DNA motifs that are inverted or direct repeats or spaced motif pairs. However, these motifs are often difficult to identify owing to their high divergence. The motif structure included explicitly into the motif recognition algorithm improves recognition efficiency for highly divergent motifs as well as estimation of motif geometric parameters.'),
(71979, 2005, 'bio', 'A word-oriented approach to alignment validation', 'Beiko, Robert G|Chan, Cheong Xin|Ragan, Mark A', 'ARC Centre in Bioinformatics and Institute for Molecular Bioscience, The University of Queensland Brisbane, Qld 4072, Australia.|ARC Centre in Bioinformatics and Institute for Molecular Bioscience, The University of Queensland Brisbane, Qld 4072, Australia.|ARC Centre in Bioinformatics and Institute for Molecular Bioscience, The University of Queensland Brisbane, Qld 4072, Australia.', 'Australia|Australia|Australia', 0, 'Algorithms|Artificial Intelligence|Natural Language Processing|Pattern Recognition, Automated|Proteins|Semantics|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bti335', '15728118', 'Multiple sequence alignment at the level of whole proteomes requires a high degree of automation, precluding the use of traditional validation methods such as manual curation. Since evolutionary models are too general to describe the history of each residue in a protein family, there is no single algorithm/model combination that can yield a biologically or evolutionarily optimal alignment. We propose a shotgun strategy where many different algorithms are used to align the same family, and the best of these alignments is then chosen with a reliable objective function. We present WOOF, a novel word-oriented objective function that relies on the identification and scoring of conserved amino acid patterns (words) between pairs of sequences.'),
(71980, 2005, 'bio', 'AutoMotif server: prediction of single residue post-translational modifications in proteins', 'Plewczynski, Dariusz|Tkacz, Adrian|Wyrwicz, Lucjan Stanislaw|Rychlewski, Leszek', 'BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan, Poland. darman@bioinfo.pl|BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan, Poland. darman@bioinfo.pl|BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan, Poland. darman@bioinfo.pl|BioInfoBank Institute, Limanowskiego 24A/16, 60-744 Poznan, Poland. darman@bioinfo.pl', 'Poland|Poland|Poland|Poland', 51, 'Algorithms|Amino Acid Motifs|Amino Acids|Artificial Intelligence|Internet|Protein Processing, Post-Translational|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti333', '15728119', 'The AutoMotif Server allows for identification of post-translational modification (PTM) sites in proteins based only on local sequence information. The local sequence preferences of short segments around PTM residues are described here as linear functional motifs (LFMs). Sequence models for all types of PTMs are trained by support vector machine on short-sequence fragments of proteins in the current release of Swiss-Prot database (phosphorylation by various protein kinases, sulfation, acetylation, methylation, amidation, etc.). The accuracy of the identification is estimated using the standard leave-one-out procedure. The sensitivities for all types of short LFMs are in the range of 70%.'),
(71981, 2005, 'bio', 'PatGen--a consolidated resource for searching genetic patent sequences', 'Rouse, Richard J D|Castagnetto, Jesus|Niedner, Roland H', 'PatentInformatics, PO Box 948586, La Jolla, CA 92037, USA. rjdrouse@patentinformatics.com|PatentInformatics, PO Box 948586, La Jolla, CA 92037, USA. rjdrouse@patentinformatics.com|PatentInformatics, PO Box 948586, La Jolla, CA 92037, USA. rjdrouse@patentinformatics.com', 'United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Bibliographic|Databases, Factual|Databases, Genetic|Documentation|Genetic Engineering|Information Storage and Retrieval|Natural Language Processing|Patents as Topic', 'Journal Article', '10.1093/bioinformatics/bti202', '15728120', 'Compared to the wealth of online resources covering genomic, proteomic and derived data the Bioinformatics community is rather underserved when it comes to patent information related to biological sequences. The current online resources are either incomplete or rather expensive. This paper describes, PatGen, an integrated database containing data from bioinformatic and patent resources. This effort addresses the inconsistency of publicly available genetic patent data coverage by providing access to a consolidated dataset.'),
(71982, 2005, 'bio', 'Haplotype reconstruction from SNP fragments by minimum error correction', 'Wang, Rui-Sheng|Wu, Ling-Yun|Li, Zhen-Ping|Zhang, Xiang-Sun', 'Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. wangrsh@amss.ac.cn|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. wangrsh@amss.ac.cn|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. wangrsh@amss.ac.cn|Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China. wangrsh@amss.ac.cn', 'China|China|China|China', 105, 'Algorithms|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Genome, Human|Haplotypes|Humans|Models, Genetic|Models, Statistical|Phylogeny|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti352', '15731204', 'Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individuals DNA.'),
(71983, 2005, 'bio', 'RNA tertiary structure determination: NOE pathways construction by tabu search', 'Blazewicz, Jacek|Szachniuk, Marta|Wojtowicz, Adam', 'Istitute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.|Istitute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.|Istitute of Bioorganic Chemistry, Polish Academy of Sciences, 61-704 Poznan, Poland.', 'Poland|Poland|Poland', 0, 'Algorithms|Base Sequence|Computer Simulation|Magnetic Resonance Spectroscopy|Models, Chemical|Models, Molecular|Molecular Sequence Data|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti351', '15731205', 'Liquid state nuclear magnetic resonance (NMR) spectroscopy has now been well established as a method for RNA tertiary structure determination. Most of the steps involved in the determination of RNA molecules are performed using computer programs. They however, do not apply to resonance assignment being the starting point of the whole procedure. We propose a tabu search algorithm as a tool for automating this step. Nuclear overhause effect (NOE) pathway, which determines the assignment, is constructed during an analysis of possible connections between resonances within aromatic/anomeric region of two-dimensional NOESY spectrum resulting from appropriate NMR experiment.'),
(71984, 2005, 'bio', 'PLATCOM: a Platform for Computational Comparative Genomics', 'Choi, Kwangmin|Ma, Yu|Choi, Jeong-Heyon|Kim, Sun', 'School of Informatics, Indiana University, Bloomington, IN 47404, USA.|School of Informatics, Indiana University, Bloomington, IN 47404, USA.|School of Informatics, Indiana University, Bloomington, IN 47404, USA.|School of Informatics, Indiana University, Bloomington, IN 47404, USA.', 'India|India|India|India', 18, 'Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti350', '15731206', 'As more whole genome sequences become available, comparing multiple genomes at the sequence level can provide insight into new biological discovery. However, there are significant challenges for genome comparison. The challenge includes requirement for computational resources owing to the large volume of genome data. More importantly, since the choice of genomes to be compared is entirely subjective, there are too many choices for genome comparison. For these reasons, there is pressing need for bioinformatics systems for comparing multiple genomes where users can choose genomes to be compared freely.'),
(71985, 2005, 'bio', 'Predicting a set of minimal free energy RNA secondary structures common to two sequences', 'Mathews, David H', 'Center for Human Genetics and Molecular Pediatric Disease, University of Rochester Medical Center, 601 Elmwood Avenue, Box 703, Rochester, NY 14642, USA. David_Mathews@urmc.rochester.edu', 'United States', 91, 'Algorithms|Base Pair Mismatch|Base Sequence|Models, Chemical|Models, Genetic|Molecular Sequence Data|Nucleic Acid Conformation|Programming, Linear|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bti349', '15731207', 'Function derives from structure, therefore, there is need for methods to predict functional RNA structures.'),
(71986, 2005, 'bio', 'A new measure of the robustness of biochemical networks', 'Chen, Bor-Sen|Wang, Yu-Chao|Wu, Wei-Sheng|Li, Wen-Hsiung', 'Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, ROC. bschen@ee.nthu.edu.tw|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, ROC. bschen@ee.nthu.edu.tw|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, ROC. bschen@ee.nthu.edu.tw|Lab of Control and Systems Biology, Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, ROC. bschen@ee.nthu.edu.tw', '-|-|-|-', 0, 'Animals|Cell Physiological Phenomena|Computer Simulation|Gene Expression Regulation|Humans|Models, Biological|Models, Chemical|Models, Statistical|Signal Transduction|Stochastic Processes|Systems Biology', 'Evaluation Studies', '10.1093/bioinformatics/bti348', '15731208', 'The robustness of a biochemical network is defined as the tolerance of variations in kinetic parameters with respect to the maintenance of steady state. Robustness also plays an important role in the fail-safe mechanism in the evolutionary process of biochemical networks. The purposes of this paper are to use the synergism and saturation system (S-system) representation to describe a biochemical network and to develop a robustness measure of a biochemical network subject to variations in kinetic parameters. Since most biochemical networks in nature operate close to the steady state, we consider only the robustness measurement of a biochemical network at the steady state.'),
(71987, 2005, 'bio', 'Self-organizing and self-correcting classifications of biological data', 'Garrity, George M|Lilburn, Timothy G', 'Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA. garrity@msu.edu|Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI 48824, USA. garrity@msu.edu', 'United States|United States', 11, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computer Graphics|Computer Simulation|Data Interpretation, Statistical|Databases, Genetic|Gammaproteobacteria|Gene Expression Profiling|Information Storage and Retrieval|Models, Biological|Pattern Recognition, Automated|RNA, Ribosomal|Sequence Alignment|Sequence Analysis, RNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti346', '15731209', 'Rapid, automated means of organizing biological data are required if we hope to keep abreast of the flood of data emanating from sequencing, microarray and similar high-throughput analyses. Faced with the need to validate the annotation of thousands of sequences and to generate biologically meaningful classifications based on the sequence data, we turned to statistical methods in order to automate these processes.'),
(71988, 2005, 'bio', 'Collateral missing value imputation: a new robust missing value estimation algorithm for microarray data', 'Sehgal, Muhammad Shoaib B|Gondal, Iqbal|Dooley, Laurence S', 'Gippsland School of Computing and Information Technology, Monash University, VIC 3842, Australia. Shoaib.Sehgal@infotech.monash.edu.au|Gippsland School of Computing and Information Technology, Monash University, VIC 3842, Australia. Shoaib.Sehgal@infotech.monash.edu.au|Gippsland School of Computing and Information Technology, Monash University, VIC 3842, Australia. Shoaib.Sehgal@infotech.monash.edu.au', 'Australia|Australia|Australia', 92, 'Algorithms|BRCA1 Protein|BRCA2 Protein|Data Interpretation, Statistical|Female|Gene Expression Profiling|Humans|Likelihood Functions|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Saccharomyces cerevisiae Proteins|Sample Size', 'Comparative Study', '10.1093/bioinformatics/bti345', '15731210', 'Microarray data are used in a range of application areas in biology, although often it contains considerable numbers of missing values. These missing values can significantly affect subsequent statistical analysis and machine learning algorithms so there is a strong motivation to estimate these values as accurately as possible before using these algorithms. While many imputation algorithms have been proposed, more robust techniques need to be developed so that further analysis of biological data can be accurately undertaken. In this paper, an innovative missing value imputation algorithm called collateral missing value estimation (CMVE) is presented which uses multiple covariance-based imputation matrices for the final prediction of missing values. The matrices are computed and optimized using least square regression and linear programming methods.'),
(71989, 2005, 'bio', 'Object-oriented biological system integration: a SARS coronavirus example', 'Shegogue, Daniel|Zheng, W Jim', 'Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon Street, PO Box 250835, Charleston, SC 29425, USA.|Department of Biostatistics, Bioinformatics and Epidemiology, Medical University of South Carolina, 135 Cannon Street, PO Box 250835, Charleston, SC 29425, USA.', 'United States|United States', 7, 'Animals|Computer Simulation|Humans|Models, Biological|SARS Virus|Severe Acute Respiratory Syndrome|Systems Biology|Systems Integration|Viral Proteins', 'Evaluation Studies', '10.1093/bioinformatics/bti344', '15731211', 'The importance of studying biology at the system level has been well recognized, yet there is no well-defined process or consistent methodology to integrate and represent biological information at this level. To overcome this hurdle, a blending of disciplines such as computer science and biology is necessary.'),
(71990, 2005, 'bio', 'DATF: a database of Arabidopsis transcription factors', 'Guo, Anyuan|He, Kun|Liu, Di|Bai, Shunong|Gu, Xiaocheng|Wei, Liping|Luo, Jingchu', 'Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.|Center for Bioinformatics, Beijing 100871, Peoples Republic of China.', 'China|China|China|China|China|China|China', 249, 'Amino Acid Sequence|Arabidopsis Proteins|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Internet|Molecular Sequence Data|Plant Proteins|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti334', '15731212', 'We have probably developed the most comprehensive database of Arabidopsis transcription factors (DATF). The DATF contains known and predicted Arabidopsis transcription factors (1827 genes in 56 families) with the unique information of 1177 cloned sequences and many other features including 3D structure templates, EST expression information, transcription factor binding sites and nuclear location signals.'),
(71991, 2005, 'bio', 'Using evolutionary Expectation Maximization to estimate indel rates', 'Holmes, Ian', 'Department of Statistics, 1 South Parks Road, Oxford OX1 3TG, UK. ihh@berkeley.edu', 'United Kingdom', 26, 'Algorithms|Artificial Intelligence|Base Sequence|Computer Simulation|DNA Mutational Analysis|DNA Transposable Elements|Evolution, Molecular|Likelihood Functions|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Deletion', 'Evaluation Studies', '10.1093/bioinformatics/bti177', '15731213', 'The Expectation Maximization (EM) algorithm, in the form of the Baum-Welch algorithm (for hidden Markov models) or the Inside-Outside algorithm (for stochastic context-free grammars), is a powerful way to estimate the parameters of stochastic grammars for biological sequence analysis. To use this algorithm for multiple-sequence evolutionary modelling, it would be useful to apply the EM algorithm to estimate not only the probability parameters of the stochastic grammar, but also the instantaneous mutation rates of the underlying evolutionary model (to facilitate the development of stochastic grammars based on phylogenetic trees, also known as Statistical Alignment). Recently, we showed how to do this for the point substitution component of the evolutionary process, here, we extend these results to the indel process.'),
(71992, 2005, 'bio', 'A web-based tool for principal component and significance analysis of microarray data', 'Sharov, Alexei A|Dudekula, Dawood B|Ko, Minoru S H', 'Developmental Genomics and Aging Section, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.|Developmental Genomics and Aging Section, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.|Developmental Genomics and Aging Section, Laboratory of Genetics, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer Graphics|Computer Simulation|Gene Expression Profiling|Internet|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti343', '15734774', 'We have developed a program for microarray data analysis, which features the false discovery rate for testing statistical significance and the principal component analysis using the singular value decomposition method for detecting the global trends of gene-expression patterns. Additional features include analysis of variance with multiple methods for error variance adjustment, correction of cross-channel correlation for two-color microarrays, identification of genes specific to each cluster of tissue samples, biplot of tissues and corresponding tissue-specific genes, clustering of genes that are correlated with each principal component (PC), three-dimensional graphics based on virtual reality modeling language and sharing of PC between different experiments. The software also supports parameter adjustment, gene search and graphical output of results. The software is implemented as a web tool and thus the speed of analysis does not depend on the power of a client computer.'),
(71993, 2005, 'bio', 'Protein structure topological comparison, discovery and matching service', 'Torrance, G M|Gilbert, D R|Michalopoulos, I|Westhead, D W', 'Bioinformatics Research Centre, Department of Computer Science, University of Glasgow, Glasgow G12 8QQ, UK.|Bioinformatics Research Centre, Department of Computer Science, University of Glasgow, Glasgow G12 8QQ, UK.|Bioinformatics Research Centre, Department of Computer Science, University of Glasgow, Glasgow G12 8QQ, UK.|Bioinformatics Research Centre, Department of Computer Science, University of Glasgow, Glasgow G12 8QQ, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Computer Graphics|Computer Simulation|Internet|Models, Chemical|Models, Molecular|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti331', '15741246', 'We describe a fold level fast protein comparison and motif matching facility based on the TOPS representation of structure. This provides an update to a previous service at the EBI, with a better graph matching with faster results and visualization of both the structures being compared against and the common pattern of each with the target domain.'),
(71994, 2005, 'bio', 'Disulfide connectivity prediction using secondary structure information and diresidue frequencies', 'Ferrè, F|Clote, P', 'Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.|Department of Biology, Boston College, Chestnut Hill, MA 02467, USA.', 'United States|United States', 70, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Cysteine|Disulfides|Models, Chemical|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bti328', '15741247', 'We describe a stand-alone algorithm to predict disulfide bond partners in a protein given only the amino acid sequence, using a novel neural network architecture (the diresidue neural network), and given input of symmetric flanking regions of N-terminus and C-terminus half-cystines augmented with residue secondary structure (helix, coil, sheet) as well as evolutionary information. The approach is motivated by the observation of a bias in the secondary structure preferences of free cysteines and half-cystines, and by promising preliminary results we obtained using diresidue position-specific scoring matrices.'),
(71995, 2005, 'bio', 'Computational prediction and experimental verification of novel IdeR binding sites in the upstream sequences of Mycobacterium tuberculosis open reading frames', 'Prakash, Prachee|Yellaboina, Sailu|Ranjan, Akash|Hasnain, Seyed E', 'Laboratory of Molecular and Cellular Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.|Laboratory of Molecular and Cellular Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.|Laboratory of Molecular and Cellular Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.|Laboratory of Molecular and Cellular Biology, Centre for DNA Fingerprinting and Diagnostics, Hyderabad 500 076, India.', 'India|India|India|India', 0, 'Bacterial Proteins|Binding Sites|Computer Simulation|DNA, Bacterial|Gene Expression Regulation, Bacterial|Models, Biological|Models, Chemical|Mycobacterium tuberculosis|Open Reading Frames|Protein Binding|Repressor Proteins|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti375', '15746274', 'IdeR (iron-dependent regulator) is a key regulator of virulence factors and iron acquisition systems in Mycobacterium tuberculosis. Despite the wealth of information available on IdeR-regulated genes of M.tuberculosis, there is still an underlying possibility that there are novel genes/pathways that have gone undetected, the identification of which could give new insights into understanding the pathogenesis of M.tuberculosis. We describe an in silico approach employing the positional relative entropy method to identify potential IdeR binding sites in the upstream sequences of all the 3919 ORFs of M.tuberculosis. While many of the predictions made by this approach overlapped with the ones already identified by microarray experiments and binding assays, pointing to the accuracy of our method, a few genes for which there has been no evidence for IdeR regulation were additionally identified. Our results have implications on the iron-dependent regulatory mechanism of M.tuberculosis vis-a-vis the activity of urease operon and novel transcription regulators and transporters.'),
(71996, 2005, 'bio', 'Partition-distance via the assignment problem', 'Konovalov, Dmitry A|Litow, Bruce|Bajema, Nigel', 'School of Information Technology, James Cook University, Townsville, QLD 4811, Australia. dmitry.konovalov@jcu.edu.au|School of Information Technology, James Cook University, Townsville, QLD 4811, Australia. dmitry.konovalov@jcu.edu.au|School of Information Technology, James Cook University, Townsville, QLD 4811, Australia. dmitry.konovalov@jcu.edu.au', 'Australia|Australia|Australia', 25, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Models, Genetic|Pedigree|Quantitative Trait Loci|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti373', '15746275', 'Accuracy testing of various pedigree reconstruction methods requires an efficient algorithm for the calculation of distance between a known partition and its reconstruction. The currently used algorithm of Almudevar and Field takes a prohibitively long time for certain partitions and population sizes.'),
(71997, 2005, 'bio', 'Prediction of subcellular localization using sequence-biased recurrent networks', 'Bodén, Mikael|Hawkins, John', 'School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, Australia. mikael@itee.uq.edu.au|School of Information Technology and Electrical Engineering, The University of Queensland, QLD 4072, Australia. mikael@itee.uq.edu.au', 'Australia|Australia', 107, 'Algorithms|Feedback|Gene Expression Profiling|Models, Biological|Proteins|Sequence Analysis, Protein|Signal Transduction|Subcellular Fractions', 'Evaluation Studies', '10.1093/bioinformatics/bti372', '15746276', 'Targeting peptides direct nascent proteins to their specific subcellular compartment. Knowledge of targeting signals enables informed drug design and reliable annotation of gene products. However, due to the low similarity of such sequences and the dynamical nature of the sorting process, the computational prediction of subcellular localization of proteins is challenging.'),
(71998, 2005, 'bio', 'The mutated subsequence problem and locating conserved genes', 'Chan, H L|Lam, T W|Sung, W K|Wong, Prudence W H|Yiu, S M|Fan, X', 'Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk|Department of Computer Science, University of Hong Kong, Hong Kong, China. hlchan@cs.hku.hk', 'China|China|China|China|China|China', 0, 'Algorithms|Animals|Chromosome Mapping|Conserved Sequence|DNA Mutational Analysis|Evolution, Molecular|Humans|Mice|Mutation|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/bti371', '15746277', 'For the purpose of locating conserved genes in a whole genome scale, this paper proposes a new structural optimization problem called the Mutated Subsequence Problem, which gives consideration to possible mutations between two species (in the form of reversals and transpositions) when comparing the genomes.'),
(71999, 2005, 'bio', 'A periodicity analysis of transmembrane helices', 'Leonov, Hadas|Arkin, Isaiah T', 'The Alexander Silberman Institute of Life Sciences, Department of Biological Chemistry, The Hebrew University, Givat-Ram, Jerusalem 91904, Israel.|The Alexander Silberman Institute of Life Sciences, Department of Biological Chemistry, The Hebrew University, Givat-Ram, Jerusalem 91904, Israel.', 'Israel|Israel', 8, 'Algorithms|Amino Acid Sequence|Computer Simulation|Fourier Analysis|Membrane Proteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Periodicity|Protein Conformation|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti369', '15746278', 'Transmembrane helices and the helical bundles which they form are the major building blocks of membrane proteins. Since helices are characterized by a given periodicity, it is possible to search for patterns of traits which typify one side of the helix and not the other (e.g. amphipathic helices contain a polar and apolar sides). Using Fourier transformation we have analyzed solved membrane protein structures as well as sequences of membrane proteins from the Swiss-Prot database. The traits searched included aromaticity, volume and ionization. While a number of motifs were already recognized in the literature, many were not. One particular example involved helix VII of lactose permease which contains seven aromatic residues on six helical turns. Similarly six glycine residues in four consecutive helical turns were identified as forming a motif in the chloride channel. A tabulation of all the findings is presented as well as a possible rationalization of the function of the motif.'),
(72000, 2005, 'bio', 'Classification of bacterial species from proteomic data using combinatorial approaches incorporating artificial neural networks, cluster analysis and principal components analysis', 'Lancashire, L|Schmid, O|Shah, H|Ball, G', 'The Nottingham Trent University, Nottingham, NG11 8NS, UK.|The Nottingham Trent University, Nottingham, NG11 8NS, UK.|The Nottingham Trent University, Nottingham, NG11 8NS, UK.|The Nottingham Trent University, Nottingham, NG11 8NS, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 61, 'Algorithms|Bacterial Proteins|Biomarkers|Cluster Analysis|Gene Expression Profiling|Mass Spectrometry|Models, Biological|Neisseria meningitidis|Neural Networks (Computer)|Pattern Recognition, Automated|Principal Component Analysis|Proteome|Species Specificity', 'Journal Article', '10.1093/bioinformatics/bti368', '15746279', 'Robust computer algorithms are required to interpret the vast amounts of proteomic data currently being produced and to generate generalized models which are applicable to real world scenarios. One such scenario is the classification of bacterial species. These vary immensely, some remaining remarkably stable whereas others are extremely labile showing rapid mutation and change. Such variation makes clinical diagnosis difficult and pathogens may be easily misidentified.'),
(72001, 2005, 'bio', 'Integration of GO annotations in Correspondence Analysis: facilitating the interpretation of microarray data', 'Busold, Christian H|Winter, Stefan|Hauser, Nicole|Bauer, Andrea|Dippon, Jürgen|Hoheisel, Jörg D|Fellenberg, Kurt', 'Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de|Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum (DKFZ), Im Neuenheimer Feld 580, D-69120 Heidelberg, Germany. c.busold@dkfz.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany', 11, 'Algorithms|Biomarkers, Tumor|Database Management Systems|Databases, Protein|Documentation|Gene Expression Profiling|Humans|Information Storage and Retrieval|Natural Language Processing|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Pancreatic Neoplasms|Proteins|Saccharomyces cerevisiae Proteins|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bti367', '15746280', 'The functional interpretation of microarray datasets still represents a time-consuming and challenging task. Up to now functional categories that are relevant for one or more experimental context(s) have been commonly extracted from a set of regulated genes and presented in long lists.'),
(72002, 2005, 'bio', 'Prediction of the phenotypic effects of non-synonymous single nucleotide polymorphisms using structural and evolutionary information', 'Bao, Lei|Cui, Yan', 'Department of Molecular Sciences, Center of Genomics and Bioinformatics, University of Tennessee Health Science Center, 858 Madison Avenue, Memphis, TN 38163, USA.|Department of Molecular Sciences, Center of Genomics and Bioinformatics, University of Tennessee Health Science Center, 858 Madison Avenue, Memphis, TN 38163, USA.', 'United States|United States', 52, 'Algorithms|Artificial Intelligence|Computer Simulation|DNA Mutational Analysis|Evolution, Molecular|Models, Genetic|Models, Statistical|Phenotype|Polymorphism, Single Nucleotide|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bti365', '15746281', 'There has been great expectation that the knowledge of an individuals genotype will provide a basis for assessing susceptibility to diseases and designing individualized therapy. Non-synonymous single nucleotide polymorphisms (nsSNPs) that lead to an amino acid change in the protein product are of particular interest because they account for nearly half of the known genetic variations related to human inherited diseases. To facilitate the identification of disease-associated nsSNPs from a large number of neutral nsSNPs, it is important to develop computational tools to predict the phenotypic effects of nsSNPs.'),
(72003, 2005, 'bio', 'Mega2: data-handling for facilitating genetic linkage and association analyses', 'Mukhopadhyay, Nandita|Almasy, Lee|Schroeder, Mark|Mulvihill, William P|Weeks, Daniel E', 'Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.|Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA 15261, USA.', 'United States|United States|United States|United States|United States', 119, 'Chromosome Mapping|Database Management Systems|Databases, Genetic|Information Storage and Retrieval|Linkage Disequilibrium|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti364', '15746282', 'Mega2, the manipulation environment for genetic analysis, transparently allows users to process genetic data for family-based or case/control studies accurately and efficiently. In addition to data validation checks, Mega2 provides analysis setup capabilities for a broad choice of commonly used genetic analysis programs, including SimWalk2, ASPEX, GeneHunter, SLINK, SIMULATE, S.A.G.E., SOLAR, Vitesse, Allegro, PREST, PAP, Loki, Merlin and MENDEL.'),
(72004, 2005, 'bio', 'Prediction of protein interdomain linker regions by a hidden Markov model', 'Bae, Kyounghwa|Mallick, Bani K|Elsik, Christine G', 'Department of Statistics, Texas A&M University College Station, TX 77843-3143, USA.|Department of Statistics, Texas A&M University College Station, TX 77843-3143, USA.|Department of Statistics, Texas A&M University College Station, TX 77843-3143, USA.', 'United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Binding|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti363', '15746283', 'Our aim was to predict protein interdomain linker regions using sequence alone, without requiring known homology. Identifying linker regions will delineate domain boundaries, and can be used to computationally dissect proteins into domains prior to clustering them into families. We developed a hidden Markov model of linker/non-linker sequence regions using a linker index derived from amino acid propensity. We employed an efficient Bayesian estimation of the model using Markov Chain Monte Carlo, Gibbs sampling in particular, to simulate parameters from the posteriors. Our model recognizes sequence data to be continuous rather than categorical, and generates a probabilistic output.'),
(72005, 2005, 'bio', 'Fast tandem mass spectra-based protein identification regardless of the number of spectra or potential modifications examined', 'Falkner, Jayson|Andrews, Philip', 'Department of Biological Chemistry and Program in Bioinformatics, University of Michigan, 1301 Catherine Street, Ann Arbor, MI 48109, USA. jfalkner@umich.edu|Department of Biological Chemistry and Program in Bioinformatics, University of Michigan, 1301 Catherine Street, Ann Arbor, MI 48109, USA. jfalkner@umich.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Databases, Protein|Gene Expression Profiling|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Evaluation Studies', '10.1093/bioinformatics/bti362', '15746284', 'Comparing tandem mass spectra (MSMS) against a known dataset of protein sequences is a common method for identifying unknown proteins, however, the processing of MSMS by current software often limits certain applications, including comprehensive coverage of post-translational modifications, non-specific searches and real-time searches to allow result-dependent instrument control. This problem deserves attention as new mass spectrometers provide the ability for higher throughput and as known protein datasets rapidly grow in size. New software algorithms need to be devised in order to address the performance issues of conventional MSMS protein dataset-based protein identification.'),
(72006, 2005, 'bio', 'Non-additivity in protein-DNA binding', 'OFlanagan, R A|Paillard, G|Lavery, R|Sengupta, A M', 'Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA.|Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA.|Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA.|Department of Physics and Astronomy, BioMaps Institute, Rutgers, The State University of New Jersey, 136 Frelinghuysen Road, Piscataway, NJ 08854-8019, USA.', 'Jersey|Jersey|Jersey|Jersey', 0, 'Algorithms|Amino Acid Sequence|Base Sequence|Binding Sites|DNA|DNA-Binding Proteins|Macromolecular Substances|Models, Chemical|Molecular Sequence Data|Protein Binding|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bti361', '15746285', 'Localizing protein binding sites within genomic DNA is of considerable importance, but remains difficult for protein families, such as transcription factors, which have loosely defined target sequences. It is generally assumed that protein affinity for DNA involves additive contributions from successive nucleotide pairs within the target sequence. This is not necessarily true, and non-additive effects have already been experimentally demonstrated in a small number of cases. The principal origin of non-additivity involves the so-called indirect component of protein-DNA recognition which is related to the sequence dependence of DNA deformation induced during complex formation. Non-additive effects are difficult to study because they require the identification of many more binding sequences than are normally necessary for describing additive specificity (typically via the construction of weight matrices).'),
(72007, 2005, 'bio', 'CoC: a database of universally conserved residues in protein folds', 'Donald, Jason E|Hubner, Isaac A|Rotemberg, Veronica M|Shakhnovich, Eugene I|Mirny, Leonid A', 'Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.', 'United States|United States|United States|United States|United States', 0, 'Conserved Sequence|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti360', '15746286', 'The conservatism of conservatism (CoC) database presents statistically analyzed information about the conservation of residue positions in folds across protein families.'),
(72008, 2005, 'bio', 'ADAPT: a database of affymetrix probesets and transcripts', 'Leong, Hui Sun|Yates, Tim|Wilson, Claire|Miller, Crispin J', 'Paterson Institute for Cancer Research, Wilmslow Road, Manchester M20 4BX, UK.|Paterson Institute for Cancer Research, Wilmslow Road, Manchester M20 4BX, UK.|Paterson Institute for Cancer Research, Wilmslow Road, Manchester M20 4BX, UK.|Paterson Institute for Cancer Research, Wilmslow Road, Manchester M20 4BX, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'DNA Probes|Databases, Genetic|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Internet|Oligonucleotide Array Sequence Analysis|Transcription Factors', 'Journal Article', '10.1093/bioinformatics/bti359', '15746287', 'ADAPT is an online database providing comprehensive mappings between Affymetrix probes and RefSeq and Ensembl transcripts. ADAPT was designed to help interpret microarray experiments by providing a means to explore the many-to-many relationships that exist between probes, probesets, transcripts and genes.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(72009, 2005, 'bio', 'ArrayCyGHt: a web application for analysis and visualization of array-CGH data', 'Kim, Su Young|Nam, Suk Woo|Lee, Sug Hyung|Park, Won Sang|Yoo, Nam Jin|Lee, Jung Young|Chung, Yeun-Jun', 'Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.|Microdissection Genomics Research Center, The Catholic University of Korea, Seoul, 137-701, Republic of Korea.', '-|-|-|-|-|-|-', 0, 'Algorithms|Computer Graphics|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Internet|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti357', '15746288', 'ArrayCyGHt is a web-based application tool for analysis and visualization of microarray-comparative genomic hybridization (array-CGH) data. Full process of array-CGH data analysis, from normalization of raw data to the final visualization of copy number gain or loss, can be straightforwardly achieved on this arrayCyGHt system without the use of any further software. ArrayCyGHt, therefore, provides an easy and fast tool for the analysis of copy number aberrations in any kinds of data format.'),
(72010, 2005, 'bio', 'WebAllergen: a web server for predicting allergenic proteins', 'Riaz, Tariq|Hor, Hen Ley|Krishnan, Arun|Tang, Francis|Li, Kuo-Bin', 'Bioinformatics Institute, 30 Biopolis Street, 138671, Singapore.|Bioinformatics Institute, 30 Biopolis Street, 138671, Singapore.|Bioinformatics Institute, 30 Biopolis Street, 138671, Singapore.|Bioinformatics Institute, 30 Biopolis Street, 138671, Singapore.|Bioinformatics Institute, 30 Biopolis Street, 138671, Singapore.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 20, 'Algorithms|Allergens|Amino Acid Motifs|Artificial Intelligence|Internet|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti356', '15746289', 'WebAllergen is a web server that predicts the potential allergenicity of proteins. The query protein will be compared against a set of prebuilt allergenic motifs that have been obtained from 664 known allergen proteins. The query will also be compared with known allergens that do not have detectable allergenic motifs. Moreover, users are allowed to upload their own allergens as alternative training sequences on which a new set of allergenic motifs will be built. The query sequences can also be compared with these motifs.'),
(72011, 2005, 'bio', 'Gene-Expression Omnibus integration and clustering tools in SeqExpress', 'Boyle, John', 'john@seqexpress.com', '-', 0, 'Algorithms|Cluster Analysis|Computer Graphics|Computer Simulation|Gene Expression Profiling|Internet|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Principal Component Analysis|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti355', '15746290', 'SeqExpress, a gene-expression analysis suite, has been extended to offer a number of cluster generation, refinement and visualization techniques. The cluster generation methods have been specialized to deal with aspects of the sparseness and extreme values that occur within microarray data. The results of such cluster analysis can then be refined using either: a functional enrichment based procedure, which examines each cluster to see if it possesses an unusually high or low concentration of ontology terms, or by using Expectation-Maximization to find a mixture of model based distributions within the datasets. Visualizations are provided both to explore and compare the results of the cluster generation algorithms. In addition, a tool has been developed which integrates SeqExpress with the Gene-Expression Omnibus repository. The tool provides seamless access to the large number of experimental results in the repository, so that they can be visualized and analysed locally using SeqExpress.'),
(72012, 2005, 'bio', 'SNP discovery using advanced algorithms and neural networks', 'Unneberg, Per|Strömberg, Michael|Sterky, Fredrik', 'Department of Biotechnology, Royal Institute of Technology, AlbaNova University Center, S-106 91 Stockholm, Sweden.|Department of Biotechnology, Royal Institute of Technology, AlbaNova University Center, S-106 91 Stockholm, Sweden.|Department of Biotechnology, Royal Institute of Technology, AlbaNova University Center, S-106 91 Stockholm, Sweden.', 'Sweden|Sweden|Sweden', 0, 'Algorithms|Base Sequence|Chromosome Mapping|DNA Mutational Analysis|Humans|Molecular Sequence Data|Neural Networks (Computer)|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bti354', '15746291', 'Forage is an application which uses two neural networks for detecting single nucleotide polymorphisms (SNPs). Potential SNP candidates are identified in multiple alignments. Each candidate is then represented by a vector of features, which is classified as SNP or monomorphic by the networks. A validated dataset of SNPs was constructed from experimentally verified SNP data and used for network training and method evalutation.'),
(72013, 2005, 'bio', 'Multiple flexible structure alignment using partial order graphs', 'Ye, Yuzhen|Godzik, Adam', 'Program in Bioinformatics and Systems Biology, The Burnham Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA. yye@burnham.org|Program in Bioinformatics and Systems Biology, The Burnham Institute, 10901 N. Torrey Pines Road, La Jolla, CA 92037, USA. yye@burnham.org', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Evolution, Molecular|Models, Chemical|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti353', '15746292', 'Existing comparisons of protein structures are not able to describe structural divergence and flexibility in the structures being compared because they focus on identifying a common invariant core and ignore parts of the structures outside this core. Understanding the structural divergence and flexibility is critical for studying the evolution of functions and specificities of proteins.'),
(72014, 2005, 'bio', 'PSIbase: a database of Protein Structural Interactome map (PSIMAP)', 'Gong, Sungsam|Yoon, Giseok|Jang, Insoo|Bolser, Dan|Dafas, Panos|Schroeder, Michael|Choi, Hansol|Cho, Yoobok|Han, Kyungsook|Lee, Sunghoon|Choi, Hwanho|Lappe, Michael|Holm, Liisa|Kim, Sangsoo|Oh, Donghoon|Bhak, Jonghwa', 'Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.|Biomatics Lab, Department of BioSystems, KAIST, Daejeon, Korea.', '-|-|-|-|-|-|-|-|-|-|-|-|-|-|-|-', 68, 'Binding Sites|Computer Graphics|Computer Simulation|Databases, Protein|Internet|Models, Biological|Models, Chemical|Models, Molecular|Protein Binding|Protein Conformation|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti366', '15749693', 'Protein Structural Interactome map (PSIMAP) is a global interaction map that describes domain-domain and protein-protein interaction information for known Protein Data Bank structures. It calculates the Euclidean distance to determine interactions between possible pairs of structural domains in proteins. PSIbase is a database and file server for protein structural interaction information calculated by the PSIMAP algorithm. PSIbase also provides an easy-to-use protein domain assignment module, interaction navigation and visual tools. Users can retrieve possible interaction partners of their proteins of interests if a significant homology assignment is made with their query sequences.'),
(72015, 2005, 'bio', 'REVCOM: a robust Bayesian method for evolutionary rate estimation', 'Bordner, Andrew J|Abagyan, Ruben', 'Molsoft LLC, 3366 North Torrey Pines Court, Suite 300, La Jolla, CA 92037, USA. bordner@ornl.gov|Molsoft LLC, 3366 North Torrey Pines Court, Suite 300, La Jolla, CA 92037, USA. bordner@ornl.gov', 'United States|United States', 11, 'Algorithms|Bayes Theorem|Binding Sites|Computer Simulation|Evolution, Molecular|Genetic Variation|Models, Chemical|Models, Molecular|Phylogeny|Protein Binding|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bti347', '15749694', 'Evolutionary conservation estimated from a multiple sequence alignment is a powerful indicator of the functional significance of a residue and helps to predict active sites, ligand binding sites, and protein interaction interfaces. Many algorithms that calculate conservation work well, provided an accurate and balanced alignment is used. However, such a strong dependence on the alignment makes the results highly variable. We attempted to improve the conservation prediction algorithm by making it more robust and less sensitive to (1) local alignment errors, (2) overrepresentation of sequences in some branches and (3) occasional presence of unrelated sequences.'),
(72016, 2005, 'bio', 'MIPS bacterial genomes functional annotation benchmark dataset', 'Tetko, Igor V|Brauner, Barbara|Dunger-Kaltenbach, Irmtraud|Frishman, Goar|Montrone, Corinna|Fobo, Gisela|Ruepp, Andreas|Antonov, Alexey V|Surmeli, Dimitrij|Mewes, Hans-Wernen', 'Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de|Institute for Bioinformatics (MIPS), GSF National Research Center for Environment and Health, Ingolstaedter Landstrasse 1, D-85764 Neuherberg, Germany. i.tetko@gsf.de', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 4, 'Bacterial Proteins|Benchmarking|Chromosome Mapping|Database Management Systems|Databases, Protein|Documentation|Genome, Bacterial|Information Storage and Retrieval|Internet', 'Journal Article', '10.1093/bioinformatics/bti380', '15769832', 'Any development of new methods for automatic functional annotation of proteins according to their sequences requires high-quality data (as benchmark) as well as tedious preparatory work to generate sequence parameters required as input data for the machine learning methods. Different program settings and incompatible protocols make a comparison of the analyzed methods difficult.'),
(72017, 2005, 'bio', 'Promoter modeling: the case study of mammalian histone promoters', 'Chowdhary, Rajesh|Ali, R Ayesha|Albig, Werner|Doenecke, Detlef|Bajic, Vladimir B', 'Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.|Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.|Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.|Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.|Knowledge Extraction Lab, Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613.', 'Singapore|Singapore|Singapore|Singapore|Singapore', 9, 'Algorithms|Animals|Conserved Sequence|Evolution, Molecular|Histones|Humans|Mice|Models, Genetic|Phylogeny|Promoter Regions, Genetic|Rats|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bti387', '15769833', 'Histone proteins play important roles in chromosomal functions. They are significantly evolutionarily conserved across species, which suggests similarity in their transcription regulation. The abundance of experimental data on histone promoters provides an excellent background for the evaluation of computational methods. Our study addresses the issue of how well computational analysis can contribute to unveiling the biologically relevant content of promoter regions for a large number of mammalian histone genes taken across several species, and suggests the consensus promoter models of different histone groups.'),
(72018, 2005, 'bio', 'The properties of protein family space depend on experimental design', 'Kunin, Victor|Teichmann, Sarah A|Huynen, Martijn A|Ouzounis, Christos A', 'Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. vkunin@lbl.gov|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. vkunin@lbl.gov|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. vkunin@lbl.gov|Computational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK. vkunin@lbl.gov', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 7, 'Algorithms|Computer Simulation|Databases, Protein|Models, Chemical|Models, Molecular|Models, Statistical|Proteins|Research Design|Sequence Alignment|Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/bti386', '15769834', 'Databases of protein families often exhibit drastically different properties of the protein family space.'),
(72019, 2005, 'bio', 'Fold recognition by combining profile-profile alignment and support vector machine', 'Han, Sangjo|Lee, Byung-Chul|Yu, Seung Taek|Jeong, Chan-Seok|Lee, Soyoung|Kim, Dongsup', 'Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.|Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.|Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.|Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.|Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.|Department of Biosystems, Korea Advanced Institute of Science and Technology, Daejeon, 305-701, Korea.', '-|-|-|-|-|-', 30, 'Algorithms|Artificial Intelligence|Binding Sites|Databases, Protein|Gene Expression Profiling|Pattern Recognition, Automated|Protein Binding|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bti384', '15769835', 'Currently, the most accurate fold-recognition method is to perform profile-profile alignments and estimate the statistical significances of those alignments by calculating Z-score or E-value. Although this scheme is reliable in recognizing relatively close homologs related at the family level, it has difficulty in finding the remote homologs that are related at the superfamily or fold level.'),
(72020, 2005, 'bio', 'A novel approach for clustering proteomics data using Bayesian fast Fourier transform', 'Bensmail, Halima|Golek, Jennifer|Moody, Michelle M|Semmes, John O|Haoudi, Abdelali', 'Department of Statistics, University of Tennessee, 334 Stokely Management Building, Knoxville, TN 37996-0532, USA.|Department of Statistics, University of Tennessee, 334 Stokely Management Building, Knoxville, TN 37996-0532, USA.|Department of Statistics, University of Tennessee, 334 Stokely Management Building, Knoxville, TN 37996-0532, USA.|Department of Statistics, University of Tennessee, 334 Stokely Management Building, Knoxville, TN 37996-0532, USA.|Department of Statistics, University of Tennessee, 334 Stokely Management Building, Knoxville, TN 37996-0532, USA.', 'United States|United States|United States|United States|United States', 4, 'Algorithms|Bayes Theorem|Biomarkers|Cluster Analysis|Databases, Protein|Diagnosis, Computer-Assisted|Diagnosis, Differential|Fourier Analysis|Gene Expression Profiling|Humans|Leukemia-Lymphoma, Adult T-Cell|Paraparesis, Tropical Spastic|Pattern Recognition, Automated|Proteome|Sequence Analysis, Protein|Signal Processing, Computer-Assisted|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/bti383', '15769836', 'Bioinformatics clustering tools are useful at all levels of proteomic data analysis. Proteomics studies can provide a wealth of information and rapidly generate large quantities of data from the analysis of biological specimens. The high dimensionality of data generated from these studies requires the development of improved bioinformatics tools for efficient and accurate data analyses. For proteome profiling of a particular system or organism, a number of specialized software tools are needed. Indeed, significant advances in the informatics and software tools necessary to support the analysis and management of these massive amounts of data are needed. Clustering algorithms based on probabilistic and Bayesian models provide an alternative to heuristic algorithms. The number of clusters (diseased and non-diseased groups) is reduced to the choice of the number of components of a mixture of underlying probability. The Bayesian approach is a tool for including information from the data to the analysis. It offers an estimation of the uncertainties of the data and the parameters involved.'),
(72021, 2005, 'bio', 'A non-stationary model for functional mapping of complex traits', 'Zhao, Wei|Chen, Ying Q|Casella, George|Cheverud, James M|Wu, Rongling', 'Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.|Department of Statistics, University of Florida, Gainesville, FL 32611, USA.', 'United States|United States|United States|United States|United States', 62, 'Aging|Algorithms|Animals|Body Weight|Chromosome Mapping|Computer Simulation|DNA Mutational Analysis|Female|Gene Expression Regulation, Developmental|Male|Mice|Models, Genetic|Models, Statistical|Quantitative Trait Loci|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bti382', '15769837', 'Understanding the genetic control of growth is fundamental to agricultural, evolutionary and biomedical genetic research. In this article, we present a statistical model for mapping quantitative trait loci (QTL) that are responsible for genetic differences in growth trajectories during ontogenetic development. This model is derived within the maximum likelihood context, implemented with the expectation-maximization algorithm. We incorporate mathematical aspects of growth processes to model the mean vector and structured antedependence models to approximate time-dependent covariance matrices for longitudinal traits. Our model has been employed to map QTL that affect body mass growth trajectories in both male and female mice of an F2 population derived from the Large and Small mouse strains. The results from this model are compared with those from the autoregressive-based functional mapping approach. Based on results from computer simulation studies, we suggest that these two models are alternative to one another and should be used simultaneously for the same dataset.'),
(72022, 2005, 'bio', 'Using the biological taxonomy to access biological literature with PathBinderH', 'Ding, J|Viswanathan, K|Berleant, D|Hughes, L|Wurtele, E S|Ashlock, D|Dickerson, J A|Fulmer, A|Schnable, P S', 'Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.|Department of Electrical and Computer Engineering, Iowa State University, Ames, IA 50011, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 12, 'Abstracting and Indexing as Topic|Biology|Database Management Systems|Documentation|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Plants|PubMed|Software|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti381', '15769838', 'PathBinderH allows users to make queries that retrieve sentences and the abstracts containing them from PubMed. Another aspect of PathBinderH is that users can specify biological taxa in order to limit searches by mentioning either the specified taxa, or their subordinate taxa, in the biological taxonomy. Although the current project requires this function only for plant taxa, the principle is extensible to the entire taxonomy.'),
(72023, 2005, 'bio', 'A fractional programming approach to efficient DNA melting temperature calculation', 'Leber, Markus|Kaderali, Lars|Schönhuth, Alexander|Schrader, Rainer', 'Institute for Biochemistry, University of Cologne, Zülpicher Strasse 47, Köln, D-50674, Germany.|Institute for Biochemistry, University of Cologne, Zülpicher Strasse 47, Köln, D-50674, Germany.|Institute for Biochemistry, University of Cologne, Zülpicher Strasse 47, Köln, D-50674, Germany.|Institute for Biochemistry, University of Cologne, Zülpicher Strasse 47, Köln, D-50674, Germany.', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Base Sequence|Computer Simulation|DNA|Models, Chemical|Models, Molecular|Molecular Sequence Data|Nucleic Acid Conformation|Nucleic Acid Denaturation|Sequence Alignment|Sequence Analysis, DNA|Software|Temperature|Transition Temperature', 'Comparative Study', '10.1093/bioinformatics/bti379', '15769839', 'In a wide range of experimental techniques in biology, there is a need for an efficient method to calculate the melting temperature of pairings of two single DNA strands. Avoiding cross-hybridization when choosing primers for the polymerase chain reaction or selecting probes for large-scale DNA assays are examples where the exact determination of melting temperatures is important. Beyond being exact, the method has to be efficient, as these techniques often require the simultaneous calculation of melting temperatures of up to millions of possible pairings. The problem is to simultaneously determine the most stable alignment of two sequences, including potential loops and bulges, and calculate the corresponding melting temperature.'),
(72024, 2005, 'bio', 'SNPNB: analyzing neighboring-nucleotide biases on single nucleotide polymorphisms (SNPs)', 'Zhang, Fengkai|Zhao, Zhongming', 'Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298, USA.|Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA 23298, USA.', 'United States|United States', 7, 'Algorithms|Base Pair Mismatch|Base Sequence|Chromosome Mapping|Computer Graphics|Genome, Human|Humans|Molecular Sequence Data|Nucleotides|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti377', '15769840', 'SNPNB is a user-friendly and platform-independent application for analyzing Single Nucleotide Polymorphism NeighBoring sequence context and nucleotide bias patterns, and subsequently evaluating the effective SNP size for the bias patterns observed from the whole data. It was implemented by Java and Perl. SNPNB can efficiently handle genome-wide or chromosome-wide SNP data analysis in a PC or a workstation. It provides visualizations of the bias patterns for SNPs or each type of SNPs.'),
(72025, 2005, 'bio', 'Identification and measurement of neighbor-dependent nucleotide substitution processes', 'Arndt, Peter F|Hwa, Terence', 'Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. arndt@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Ihnestrasse 73, 14195 Berlin, Germany. arndt@molgen.mpg.de', 'Germany|Germany', 63, 'Algorithms|Animals|Base Composition|Base Pair Mismatch|Base Pairing|Base Sequence|Chromosome Mapping|CpG Islands|Drosophila melanogaster|Evolution, Molecular|Genome, Human|Humans|Models, Genetic|Molecular Sequence Data|Nucleotides|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Zebrafish', 'Comparative Study', '10.1093/bioinformatics/bti376', '15769841', 'Neighbor-dependent substitution processes generated specific pattern of dinucleotide frequencies in the genomes of most organisms. The CpG-methylation-deamination process is, e.g. a prominent process in vertebrates (CpG effect). Such processes, often with unknown mechanistic origins, need to be incorporated into realistic models of nucleotide substitutions.'),
(72026, 2005, 'bio', 'Optimization of cDNA-AFLP experiments using genomic sequence data', 'Kivioja, Teemu|Arvas, Mikko|Saloheimo, Markku|Penttilä, Merja|Ukkonen, Esko', 'Department of Computer Science, University of Helsinki, Helsinki, PO Box 68, FIN-00014, Finland. Teemu.Kivioja@vtt.fi|Department of Computer Science, University of Helsinki, Helsinki, PO Box 68, FIN-00014, Finland. Teemu.Kivioja@vtt.fi|Department of Computer Science, University of Helsinki, Helsinki, PO Box 68, FIN-00014, Finland. Teemu.Kivioja@vtt.fi|Department of Computer Science, University of Helsinki, Helsinki, PO Box 68, FIN-00014, Finland. Teemu.Kivioja@vtt.fi|Department of Computer Science, University of Helsinki, Helsinki, PO Box 68, FIN-00014, Finland. Teemu.Kivioja@vtt.fi', 'Finland|Finland|Finland|Finland|Finland', 0, 'Algorithms|Chromosome Mapping|DNA Fingerprinting|DNA Probes|Oligonucleotide Array Sequence Analysis|Polymerase Chain Reaction|Polymorphism, Restriction Fragment Length|Random Amplified Polymorphic DNA Technique|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bti393', '15774551', 'cDNA amplified fragment length polymorphism (cDNA-AFLP) is one of the few genome-wide level expression profiling methods capable of finding genes that have not yet been cloned or even predicted from sequence but have interesting expression patterns under the studied conditions. In cDNA-AFLP, a complex cDNA mixture is divided into small subsets using restriction enzymes and selective PCR. A large cDNA-AFLP experiment can require a substantial amount of resources, such as hundreds of PCR amplifications and gel electrophoresis runs, followed by manual cutting of a large number of bands from the gels. Our aim was to test whether this workload can be reduced by rational design of the experiment.'),
(72027, 2005, 'bio', 'Noise-induced cooperative behavior in a multicell system', 'Chen, Luonan|Wang, Ruiqi|Zhou, Tianshou|Aihara, Kazuyuki', 'Department of Electrical Engineering and Electronics, Osaka Sangyo University, Daito, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp|Department of Electrical Engineering and Electronics, Osaka Sangyo University, Daito, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp|Department of Electrical Engineering and Electronics, Osaka Sangyo University, Daito, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp|Department of Electrical Engineering and Electronics, Osaka Sangyo University, Daito, Osaka 574-8530, Japan. chen@elec.osaka-sandai.ac.jp', 'Japan|Japan|Japan|Japan', 78, 'Adaptation, Physiological|Cell Communication|Computer Simulation|Gene Expression Regulation|Models, Biological|Models, Statistical|Signal Transduction|Stochastic Processes', 'Journal Article', '10.1093/bioinformatics/bti392', '15774552', 'All cell components exhibit intracellular noise on account of random births and deaths of individual molecules, and extracellular noise because of environment perturbations. Gene regulation in particular, is an inherently noisy process with transcriptional control, alternative splicing, translation, diffusion and chemical modification reactions, all of which involve stochastic fluctuations. Such stochastic noises may not only affect the dynamics of the entire system but may also be exploited by living organisms to actively facilitate certain functions, such as cooperative behavior and communication.'),
(72028, 2005, 'bio', 'AgentCell: a digital single-cell assay for bacterial chemotaxis', 'Emonet, Thierry|Macal, Charles M|North, Michael J|Wickersham, Charles E|Cluzel, Philippe', 'The Institute for Biophysical Dynamics and the James Franck Institute, The University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637, USA. emonet@uchicago.edu|The Institute for Biophysical Dynamics and the James Franck Institute, The University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637, USA. emonet@uchicago.edu|The Institute for Biophysical Dynamics and the James Franck Institute, The University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637, USA. emonet@uchicago.edu|The Institute for Biophysical Dynamics and the James Franck Institute, The University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637, USA. emonet@uchicago.edu|The Institute for Biophysical Dynamics and the James Franck Institute, The University of Chicago, 5640 S. Ellis Avenue, Chicago, IL 60637, USA. emonet@uchicago.edu', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Bacterial Physiological Phenomena|Chemotaxis|Computer Simulation|Flagella|Gene Expression Regulation|Models, Biological|Molecular Motor Proteins|Motion|Signal Processing, Computer-Assisted|Signal Transduction|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bti391', '15774553', 'In recent years, single-cell biology has focused on the relationship between the stochastic nature of molecular interactions and variability of cellular behavior. To describe this relationship, it is necessary to develop new computational approaches at the single-cell level.'),
(72029, 2005, 'bio', 'seq++: analyzing biological sequences with a range of Markov-related models', 'Miele, Vincent|Bourguignon, Pierre-Yves|Robelin, David|Nuel, Grégory|Richard, Hugues', 'UMR CNRS 8071 Statistique et Génome, 523 place des Terrasses, 91000 Evry, France. miele@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523 place des Terrasses, 91000 Evry, France. miele@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523 place des Terrasses, 91000 Evry, France. miele@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523 place des Terrasses, 91000 Evry, France. miele@genopole.cnrs.fr|UMR CNRS 8071 Statistique et Génome, 523 place des Terrasses, 91000 Evry, France. miele@genopole.cnrs.fr', 'France|France|France|France|France', 0, 'Algorithms|Markov Chains|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis|Sequence Homology|Software', 'Journal Article', '10.1093/bioinformatics/bti389', '15774554', 'The seq++ package offers a reference set of programs and an extensible library to biologists and developers working on sequence statistics. Its generality arises from the ability to handle sequences described with any alphabet (nucleotides, amino acids, codons and others). seq++ enables sequence modelling with various types of Markov models, including variable length Markov models and the newly developed parsimonious Markov models, all of them potentially phased. Simulation modules are supplied for Monte Carlo methods. Hence, this toolbox allows the study of any biological process which can be described by a series of states taken from a finite set.'),
(72030, 2005, 'bio', 'Characterizing dye bias in microarray experiments', 'Dobbin, K K|Kawasaki, E S|Petersen, D W|Simon, R M', 'Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov|Biometric Research Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA. dobbinke@mail.nih.gov', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Fluorescent Dyes|Gene Expression Profiling|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti378', '15774555', 'Spot intensity serves as a proxy for gene expression in dual-label microarray experiments. Dye bias is defined as an intensity difference between samples labeled with different dyes attributable to the dyes instead of the gene expression in the samples. Dye bias that is not removed by array normalization can introduce bias into comparisons between samples of interest. But if the bias is consistent across samples for the same gene, it can be corrected by proper experimental design and analysis. If the dye bias is not consistent across samples for the same gene, but is different for different samples, then removing the bias becomes more problematic, perhaps indicating a technical limitation to the ability of fluorescent signals to accurately represent gene expression. Thus, it is important to characterize dye bias to determine: (1) whether it will be removed for all genes by array normalization, (2) whether it will not be removed by normalization but can be removed by proper experimental design and analysis and (3) whether dye bias correction is more problematic than either of these and is not easily removable.'),
(72031, 2005, 'bio', 'Inferring genetic regulatory logic from expression data', 'Bulashevska, Svetlana|Eils, Roland', 'Division Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. s.bulashevska@dkfz.de|Division Theoretical Bioinformatics, German Cancer Research Center, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany. s.bulashevska@dkfz.de', 'Germany|Germany', 0, 'Bayes Theorem|Cell Cycle Proteins|Gene Expression Profiling|Gene Expression Regulation|Logistic Models|Models, Biological|Models, Statistical|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti388', '15784747', 'High-throughput molecular genetics methods allow the collection of data about the expression of genes at different time points and under different conditions. The challenge is to infer gene regulatory interactions from these data and to get an insight into the mechanisms of genetic regulation.'),
(72032, 2005, 'bio', 'Pair stochastic tree adjoining grammars for aligning and predicting pseudoknot RNA structures', 'Matsui, Hiroshi|Sato, Kengo|Sakakibara, Yasubumi', 'Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.|Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.|Keio University, Department of Biosciences and Informatics, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama 223-8522, Japan.', 'Japan|Japan|Japan', 0, 'Algorithms|Computer Simulation|Models, Chemical|Models, Genetic|Models, Statistical|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Stochastic Processes', 'Evaluation Studies', '10.1093/bioinformatics/bti385', '15784748', 'Since the whole genome sequences of many species have been determined, computational prediction of RNA secondary structures and computational identification of those non-coding RNA regions by comparative genomics become important. Therefore, more advanced alignment methods are required. Recently, an approach of structural alignment for RNA sequences has been introduced to solve these problems. Pair hidden Markov models on tree structures (PHMMTSs) proposed by Sakakibara are efficient automata-theoretic models for structural alignment of RNA secondary structures, although PHMMTSs are incapable of handling pseudoknots. On the other hand, tree adjoining grammars (TAGs), a subclass of context-sensitive grammars, are suitable for modeling pseudoknots. Our goal is to extend PHMMTSs by incorporating TAGs to be able to handle pseudoknots.'),
(72033, 2005, 'bio', 'Ovarian cancer identification based on dimensionality reduction for high-throughput mass spectrometry data', 'Yu, J S|Ongarello, S|Fiedler, R|Chen, X W|Toffolo, G|Cobelli, C|Trajanoski, Z', 'School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.|School of Electronics Engineering and Computer Science, Peking University, China.', 'China|China|China|China|China|China|China', 117, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Female|Gene Expression Profiling|Humans|Neoplasm Proteins|Ovarian Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Software|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Evaluation Studies', '10.1093/bioinformatics/bti370', '15784749', 'High-throughput and high-resolution mass spectrometry instruments are increasingly used for disease classification and therapeutic guidance. However, the analysis of immense amount of data poses considerable challenges. We have therefore developed a novel method for dimensionality reduction and tested on a published ovarian high-resolution SELDI-TOF dataset.'),
(72034, 2005, 'bio', 'Rapid motif-based prediction of circular permutations in multi-domain proteins', 'Weiner, January|Thomas, Geraint|Bornberg-Bauer, Erich', 'Division of Bioinformatics, School of Biology, Institute of Botany, The Westphalian Wilhelms University of Münster Schlossplatz 4 D48149 Münster, Germany.|Division of Bioinformatics, School of Biology, Institute of Botany, The Westphalian Wilhelms University of Münster Schlossplatz 4 D48149 Münster, Germany.|Division of Bioinformatics, School of Biology, Institute of Botany, The Westphalian Wilhelms University of Münster Schlossplatz 4 D48149 Münster, Germany.', 'Germany|Germany|Germany', 35, 'Algorithms|Amino Acid Motifs|Computer Simulation|Databases, Protein|Genetic Variation|Models, Chemical|Models, Statistical|Molecular Sequence Data|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Evaluation Studies', '10.1093/bioinformatics/bti085', '15788783', 'Rearrangements of protein domains and motifs such as swaps and circular permutations (CPs) can produce erroneous results in searching sequence databases when using traditional methods based on linear sequence alignments. Circular permutations are also of biological relevance because they can help to better understand both protein evolution and functionality.'),
(72035, 2005, 'bio', 'Mining SARS-CoV protease cleavage data using non-orthogonal decision trees: a novel method for decisive template selection', 'Yang, Zheng Rong', 'Department of Computer Science, Exeter University, United Kingdom. z.r.yang@exeter.ac.uk', 'United Kingdom', 14, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Cysteine Endopeptidases|Databases, Protein|Decision Support Techniques|Endopeptidases|Models, Chemical|Models, Molecular|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Viral Proteins', 'Comparative Study', '10.1093/bioinformatics/bti404', '15797903', 'Although the outbreak of the severe acute respiratory syndrome (SARS) is currently over, it is expected that it will return to attack human beings. A critical challenge to scientists from various disciplines worldwide is to study the specificity of cleavage activity of SARS-related coronavirus (SARS-CoV) and use the knowledge obtained from the study for effective inhibitor design to fight the disease. The most commonly used inductive programming methods for knowledge discovery from data assume that the elements of input patterns are orthogonal to each other. Suppose a sub-sequence is denoted as P2-P1-P1-P2, the conventional inductive programming method may result in a rule like if P1 = Q, then the sub-sequence is cleaved, otherwise non-cleaved. If the site P1 is not orthogonal to the others (for instance, P2, P1 and P2), the prediction power of these kind of rules may be limited. Therefore this study is aimed at developing a novel method for constructing non-orthogonal decision trees for mining protease data.'),
(72036, 2005, 'bio', 'A bioinformatic screen for novel A-I RNA editing sites reveals recoding editing in BC10', 'Clutterbuck, D R|Leroy, A|OConnell, M A|Semple, C A M', 'MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK. daniel.clutterbuck@hgu.mrc.ac.uk|MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK. daniel.clutterbuck@hgu.mrc.ac.uk|MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK. daniel.clutterbuck@hgu.mrc.ac.uk|MRC Human Genetics Unit, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK. daniel.clutterbuck@hgu.mrc.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 55, 'Adenosine|Algorithms|Animals|Base Sequence|Chromosome Mapping|Humans|Inosine|Mice|Molecular Sequence Data|Neoplasm Proteins|RNA Editing|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bti411', '15797904', 'Recent studies have demonstrated widespread adenosine-inosine RNA editing in non-coding sequence. However, the extent of editing in coding sequences has remained unknown. For many of the known sites, editing can be observed in multiple species and often occurs in well-conserved sequences. In addition, they often occur within imperfect inverted repeats and in clusters. Here we present a bioinformatic approach to identify novel sites based on these shared features. Mismatches between genomic and expressed sequences were filtered to remove the main sources of false positives, and then prioritized based on these features. This protocol is tailored to identifying specific recoding editing sites, rather than sites in non-coding repeat sequences.'),
(72037, 2005, 'bio', 'Identification of transcription factor binding sites with variable-order Bayesian networks', 'Ben-Gal, I|Shani, A|Gohr, A|Grau, J|Arviv, S|Shmilovici, A|Posch, S|Grosse, I', 'Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il|Department of Industrial Engineering, Tel-Aviv University, Tel-Aviv, 69978, Israel. bengal@eng.tau.ac.il', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 122, 'Algorithms|Artificial Intelligence|Bayes Theorem|Binding Sites|Computer Simulation|Databases, Protein|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bti410', '15797905', 'We propose a new class of variable-order Bayesian network (VOBN) models for the identification of transcription factor binding sites (TFBSs). The proposed models generalize the widely used position weight matrix (PWM) models, Markov models and Bayesian network models. In contrast to these models, where for each position a fixed subset of the remaining positions is used to model dependencies, in VOBN models, these subsets may vary based on the specific nucleotides observed, which are called the context. This flexibility turns out to be of advantage for the classification and analysis of TFBSs, as statistical dependencies between nucleotides in different TFBS positions (not necessarily adjacent) may be taken into account efficiently--in a position-specific and context-specific manner.'),
(72038, 2005, 'bio', 'Formalizing concepts of species, sex and developmental stage in anatomical ontologies', 'Aitken, Stuart', 'School of Informatics, The University of Edinburgh, Edinburgh EH8 9LE, United Kingdom. stuart@aiai.ed.ac.uk', 'United Kingdom', 10, 'Anatomy|Animals|Databases, Factual|Embryology|Humans|Information Storage and Retrieval|Models, Anatomic|Sex Characteristics|Species Specificity|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti409', '15797906', 'Anatomy ontologies have a growing role in bioinformatics-for example, in indexing gene expression data in model organisms. To relate or draw conclusions from data so indexed, anatomy ontologies must be equipped with the formal vocabulary that would allow statements about meronomy to be qualified by constraints such as part of the male or part at the embryonic stage. Lacking such a vocabulary, anatomists have built this information into the structure of the ontology or into anatomical terms. For example, in the FlyBase anatomy for drosophila, the term larval abdominal segment encodes the stage in the term, while the terms male genital disc and female genital disc encode the sex. It remains implicit that a fly has one and only one of these parts during its larval stage. Such indicators of context can and should be represented explicitly in the ontology.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(72039, 2005, 'bio', 'GOR V server for protein secondary structure prediction', 'Sen, Taner Z|Jernigan, Robert L|Garnier, Jean|Kloczkowski, Andrzej', 'L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA.|L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA.|L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA.|L.H. Baker Center for Bioinformatics and Biological Statistics, Iowa State University Ames, IA 50011, USA.', 'United States|United States|United States|United States', 126, 'Algorithms|Computer Simulation|Internet|Models, Chemical|Models, Molecular|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti408', '15797907', 'We have created the GOR V web server for protein secondary structure prediction. The GOR V algorithm combines information theory, Bayesian statistics and evolutionary information. In its fifth version, the GOR method reached (with the full jack-knife procedure) an accuracy of prediction Q3 of 73.5%. Although GOR V has been among the most successful methods, its online unavailability has been a deterrent to its popularity. Here, we remedy this situation by creating the GOR V server.'),
(72040, 2005, 'bio', 'A practical false discovery rate approach to identifying patterns of differential expression in microarray data', 'Grant, Gregory R|Liu, Junmin|Stoeckert, Christian J', 'Center for Bioinformatics, University of Pennsylvania, 1429 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. ggrant@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 1429 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. ggrant@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 1429 Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. ggrant@pcbi.upenn.edu', 'United States|United States|United States', 70, 'Algorithms|Computer Simulation|False Positive Reactions|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Comparative Study', '10.1093/bioinformatics/bti407', '15797908', 'Searching for differentially expressed genes is one of the most common applications for microarrays, yet statistically there are difficult hurdles to achieving adequate rigor and practicality. False discovery rate (FDR) approaches have become relatively standard, however, how to define and control the FDR has been hotly debated. Permutation estimation approaches such as SAM and PaGE can be effective, however, they leave much room for improvement. We pursue the permutation estimation method and describe a convenient definition for the FDR that can be estimated in a straightforward manner. We then discuss issues regarding the choice of statistic and data transformation. It is impossible to optimize the power of any statistic for thousands of genes simultaneously, and we look at the practical consequences of this. For example, the log transform can both help and hurt at the same time, depending on the gene. We examine issues surrounding the SAM fudge factor parameter, and how to handle these issues by optimizing with respect to power.'),
(72041, 2005, 'bio', 'Modularized learning of genetic interaction networks from biological annotations and mRNA expression data', 'Lee, Phil Hyoun|Lee, Doheon', 'School of Computing, Queens University, Canada.|School of Computing, Queens University, Canada.', 'Canada|Canada', 45, 'Algorithms|Artificial Intelligence|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Genetic|Oligonucleotide Array Sequence Analysis|Oxidative Stress|Protein Interaction Mapping|RNA, Messenger|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Analysis, RNA|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti406', '15797909', 'Inferring the genetic interaction mechanism using Bayesian networks has recently drawn increasing attention due to its well-established theoretical foundation and statistical robustness. However, the relative insufficiency of experiments with respect to the number of genes leads to many false positive inferences.'),
(72042, 2005, 'bio', 'Genetic algorithm-based optimization of hydrophobicity tables', 'Zviling, Moti|Leonov, Hadas|Arkin, Isaiah T', 'The Alexander Silberman Institute of Life Sciences, Department of Biological Chemistry, The Hebrew University, Givat-Ram, Jerusalem 91904, Israel.|The Alexander Silberman Institute of Life Sciences, Department of Biological Chemistry, The Hebrew University, Givat-Ram, Jerusalem 91904, Israel.|The Alexander Silberman Institute of Life Sciences, Department of Biological Chemistry, The Hebrew University, Givat-Ram, Jerusalem 91904, Israel.', 'Israel|Israel|Israel', 9, 'Algorithms|Artificial Intelligence|Computer Simulation|Databases, Protein|Hydrophobic and Hydrophilic Interactions|Membrane Proteins|Models, Chemical|Models, Molecular|Models, Statistical|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bti405', '15797910', 'The genomic abundance and pharmacological importance of membrane proteins have fueled efforts to identify them based solely on sequence information. Previous methods based on the physicochemical principle of a sliding window of hydrophobicity (hydropathy analysis) have been replaced by approaches based on hidden Markov models or neural networks which prevail due to their probabilistic orientation. In the current study, an optimization of the hydrophobicity tables used in hydropathy analysis is performed using a genetic algorithm. As such, the approach can be viewed as a synthesis between the physicochemically and statistically based methods. The resulting hydrophobicity tables lead to significant improvement in the prediction accuracy of hydropathy analysis. Furthermore, since hydropathy analysis is less dependent on the basis set of membrane proteins is used to hone the statistically based methods, as well as being faster, it may be valuable in the analysis of new genomes. Finally, the values obtained for each of the amino acids in the new hydrophobicity tables are discussed.'),
(72043, 2005, 'bio', 'An algorithm for identification of bacterial selenocysteine insertion sequence elements and selenoprotein genes', 'Zhang, Yan|Gladyshev, Vadim N', 'Department of Biochemistry, University of Nebraska, Lincoln, NE 68588-0664, USA.|Department of Biochemistry, University of Nebraska, Lincoln, NE 68588-0664, USA.', 'United States|United States', 74, 'Algorithms|Bacterial Proteins|Chromosome Mapping|DNA Transposable Elements|DNA, Bacterial|Proteins|Selenoproteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bti400', '15797911', 'Incorporation of selenocysteine (Sec) into proteins in response to UGA codons requires a cis-acting RNA structure, Sec insertion sequence (SECIS) element. Whereas SECIS elements in Escherichia coli are well characterized, a bacterial SECIS consensus structure is lacking.'),
(72044, 2005, 'bio', 'Correlation between gene expression profiles and protein-protein interactions within and across genomes', 'Bhardwaj, Nitin|Lu, Hui', 'Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.|Bioinformatics Program, Department of Bioengineering, University of Illinois at Chicago, Chicago, IL 60607, USA.', 'United States|United States', 124, 'Animals|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Humans|Mice|Oligonucleotide Array Sequence Analysis|Phylogeny|Protein Interaction Mapping|Proteome|Species Specificity|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/bti398', '15797912', 'Function annotation of an unclassified protein on the basis of its interaction partners is well documented in the literature. Reliable predictions of interactions from other data sources such as gene expression measurements would provide a useful route to function annotation. We investigate the global relationship of protein-protein interactions with gene expression. This relationship is studied in four evolutionarily diverse species, for which substantial information regarding their interactions and expression is available: human, mouse, yeast and Escherichia coli.'),
(72045, 2005, 'bio', 'A robust neural networks approach for spatial and intensity-dependent normalization of cDNA microarray data', 'Tarca, A L|Cooke, J E K|Mackay, J', 'Research Center in Forest Biology, Department of Wood and Forest Science, Laval University, Sainte-Foy (QC), Canada G1K-7P4. ltarca@rsvs.ulaval.ca|Research Center in Forest Biology, Department of Wood and Forest Science, Laval University, Sainte-Foy (QC), Canada G1K-7P4. ltarca@rsvs.ulaval.ca|Research Center in Forest Biology, Department of Wood and Forest Science, Laval University, Sainte-Foy (QC), Canada G1K-7P4. ltarca@rsvs.ulaval.ca', 'Canada|Canada|Canada', 30, 'Algorithms|Artifacts|Gene Expression Profiling|Image Interpretation, Computer-Assisted|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Neural Networks (Computer)|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated', 'Comparative Study', '10.1093/bioinformatics/bti397', '15797913', 'Microarray experiments are affected by numerous sources of non-biological variation that contribute systematic bias to the resulting data. In a dual-label (two-color) cDNA or long-oligonucleotide microarray, these systematic biases are often manifested as an imbalance of measured fluorescent intensities corresponding to Sample A versus those corresponding to Sample B. Systematic biases also affect between-slide comparisons. Making effective corrections for these systematic biases is a requisite for detecting the underlying biological variation between samples. Effective data normalization is therefore an essential step in the confident identification of biologically relevant differences in gene expression profiles. Several normalization methods for the correction of systemic bias have been described. While many of these methods have addressed intensity-dependent bias, few have addressed both intensity-dependent and spatiality-dependent bias.'),
(72046, 2005, 'bio', 'Determining functional specificity from protein sequences', 'Donald, Jason E|Shakhnovich, Eugene I', 'Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.|Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.', 'United States|United States', 18, 'Algorithms|Binding Sites|Cluster Analysis|DNA|DNA-Binding Proteins|Protein Binding|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Nucleic Acid|Structure-Activity Relationship|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bti396', '15797914', 'Given a large family of homologous protein sequences, many methods can divide the family into smaller groups that correspond to the different functions carried out by proteins within the family. One important problem, however, has been the absence of a general method for selecting an appropriate level of granularity, or size of the groups.'),
(72047, 2005, 'bio', 'MADE4: an R package for multivariate analysis of gene expression data', 'Culhane, Aedín C|Thioulouse, Jean|Perrière, Guy|Higgins, Desmond G', 'Bioinformatics, Conway Institute, University College Dublin, Dublin 4, Ireland. aedin.culhane@ucd.ie|Bioinformatics, Conway Institute, University College Dublin, Dublin 4, Ireland. aedin.culhane@ucd.ie|Bioinformatics, Conway Institute, University College Dublin, Dublin 4, Ireland. aedin.culhane@ucd.ie|Bioinformatics, Conway Institute, University College Dublin, Dublin 4, Ireland. aedin.culhane@ucd.ie', 'Ireland|Ireland|Ireland|Ireland', 216, 'Algorithms|Computer Graphics|Documentation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Multivariate Analysis|Oligonucleotide Array Sequence Analysis|Phylogeny|Signal Transduction|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti394', '15797915', 'MADE4, microarray ade4, is a software package that facilitates multivariate analysis of microarray gene-expression data. MADE4 accepts a wide variety of gene-expression data formats. MADE4 takes advantage of the extensive multivariate statistical and graphical functions in the R package ade4, extending these for application to microarray data. In addition, MADE4 provides new graphical and visualization tools that aid in interpretation of multivariate analysis of microarray data.'),
(72048, 2005, 'bio', 'Quasi-consensus-based comparison of profile hidden Markov models for protein sequences', 'Kahsay, Robel Y|Wang, Guoli|Gao, Guang|Liao, Li|Dunbrack, Roland', 'Delaware Biotechnology Institute, Newark, DE 19715, USA.|Delaware Biotechnology Institute, Newark, DE 19715, USA.|Delaware Biotechnology Institute, Newark, DE 19715, USA.|Delaware Biotechnology Institute, Newark, DE 19715, USA.|Delaware Biotechnology Institute, Newark, DE 19715, USA.', 'United States|United States|United States|United States|United States', 8, 'Algorithms|Amino Acid Sequence|Consensus Sequence|Gene Expression Profiling|Markov Chains|Models, Biological|Models, Chemical|Models, Statistical|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Evaluation Studies', '10.1093/bioinformatics/bti374', '15797916', 'A simple approach for the sensitive detection of distant relationships among protein families and for sequence-structure alignment via comparison of hidden Markov models based on their quasi-consensus sequences is presented. Using a previously published benchmark dataset, the approach is demonstrated to give better homology detection and yield alignments with improved accuracy in comparison to an existing state-of-the-art dynamic programming profile-profile comparison method. This method also runs significantly faster and is therefore suitable for a server covering the rapidly increasing structure database. A server based on this method is available at http://liao.cis.udel.edu/website/servers/modmod'),
(72049, 2005, 'bio', 'Improved method for predicting beta-turn using support vector machine', 'Zhang, Qidong|Yoon, Sukjoon|Welsh, William J', 'Department of Pharmacology, University of Medicine and Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School and Informatics Institute of UMDNJ, 675 Hoes Lane, Piscataway, NJ 08854, USA.|Department of Pharmacology, University of Medicine and Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School and Informatics Institute of UMDNJ, 675 Hoes Lane, Piscataway, NJ 08854, USA.|Department of Pharmacology, University of Medicine and Dentistry of New Jersey (UMDNJ), Robert Wood Johnson Medical School and Informatics Institute of UMDNJ, 675 Hoes Lane, Piscataway, NJ 08854, USA.', 'Jersey|Jersey|Jersey', 54, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Pattern Recognition, Automated|Protein Conformation|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti358', '15797917', 'Numerous methods for predicting beta-turns in proteins have been developed based on various computational schemes. Here, we introduce a new method of beta-turn prediction that uses the support vector machine (SVM) algorithm together with predicted secondary structure information. Various parameters from the SVM have been adjusted to achieve optimal prediction performance.'),
(72050, 2005, 'bio', 'Density guided importance sampling: application to a reduced model of protein folding', 'Thomas, Geraint L|Sessions, Richard B|Parker, Martin J', 'Astbury Centre for Structural Molecular Biology, Department of Biochemistry and Microbiology, University of Leeds, Leeds LS2 9JT, UK.|Astbury Centre for Structural Molecular Biology, Department of Biochemistry and Microbiology, University of Leeds, Leeds LS2 9JT, UK.|Astbury Centre for Structural Molecular Biology, Department of Biochemistry and Microbiology, University of Leeds, Leeds LS2 9JT, UK.', 'United Kingdom|United Kingdom|United Kingdom', 2, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Models, Statistical|Monte Carlo Method|Peptide Fragments|Protein Conformation|Protein Folding|Proteins|Sequence Analysis, Protein|Software|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti421', '15802285', 'Monte Carlo methods are the most effective means of exploring the energy landscapes of protein folding. The rugged topography of folding energy landscapes causes sampling inefficiencies however, particularly at low, physiological temperatures.'),
(72051, 2005, 'bio', 'A comprehensive and non-redundant database of protein domain movements', 'Qi, Guoying|Lee, Richard|Hayward, Steven', 'School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.|School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.|School of Computing Sciences, University of East Anglia, Norwich, NR4 7TJ, UK.', 'United Kingdom|United Kingdom|United Kingdom', 57, 'Algorithms|Amino Acid Sequence|Computer Simulation|Databases, Protein|Internet|Models, Molecular|Molecular Sequence Data|Motion|Protein Conformation|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Evaluation Studies', '10.1093/bioinformatics/bti420', '15802286', 'The current DynDom database of protein domain motions is a user-created database that suffers from selectivity and redundancy. The aim of the analysis presented here was to overcome both these limitations and to produce both a comprehensive and a non-redundant description of domain movements from structures stored in the current protein data bank.'),
(72052, 2005, 'bio', 'A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae', 'Chen, Kuang-Chi|Wang, Tse-Yi|Tseng, Huei-Hun|Huang, Chi-Ying F|Kao, Cheng-Yan', 'Division of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan Town, Miaoli County 350, Taiwan.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan Town, Miaoli County 350, Taiwan.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan Town, Miaoli County 350, Taiwan.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan Town, Miaoli County 350, Taiwan.|Division of Molecular and Genomic Medicine, National Health Research Institutes, Zhunan Town, Miaoli County 350, Taiwan.', '-|-|-|-|-', 0, 'Gene Expression Regulation|Models, Biological|Models, Statistical|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Software|Stochastic Processes|Transcription Factors|Transcriptional Activation', 'Evaluation Studies', '10.1093/bioinformatics/bti415', '15802287', 'The explosion of microarray studies has promised to shed light on the temporal expression patterns of thousands of genes simultaneously. However, available methods are far from adequate in efficiently extracting useful information to aid in a greater understanding of transcriptional regulatory network. Biological systems have been modeled as dynamic systems for a long history, such as genetic networks and cell regulatory network. This study evaluated if the stochastic differential equation (SDE), which is prominent for modeling dynamic diffusion process originating from the irregular Brownian motion, can be applied in modeling the transcriptional regulatory network in Saccharomyces cerevisiae.'),
(72053, 2005, 'bio', 'GandrKB--ontological microarray annotation and visualization', 'Schober, Daniel|Leser, Ulf|Zenke, Martin|Reich, Jens', 'Department for Bioinformatics, Max Delbrück Center for Molecular Medicine, D-13122 Berlin, Germany. schober@mdc-berlin.de|Department for Bioinformatics, Max Delbrück Center for Molecular Medicine, D-13122 Berlin, Germany. schober@mdc-berlin.de|Department for Bioinformatics, Max Delbrück Center for Molecular Medicine, D-13122 Berlin, Germany. schober@mdc-berlin.de|Department for Bioinformatics, Max Delbrück Center for Molecular Medicine, D-13122 Berlin, Germany. schober@mdc-berlin.de', 'Germany|Germany|Germany|Germany', 1, 'Algorithms|Computer Graphics|Documentation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Oligonucleotide Array Sequence Analysis|Phylogeny|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti401', '15802288', 'The Gandr (gene annotation data representation) knowledgebase is an ontological framework for laboratory-specific gene annotation. Gandr uses Protege 2000 for editing, querying and visualizing microarray data and annotations. Genes can be annotated with provided, newly created or imported ontological concepts. Annotated genes can inherit assigned concept properties and can be related to each other. The resulting knowledgebase can be visualized as interactive network of nodes and edges representing genes and their functional relationships. This allows for immediate and associative gene context exploration. Ontological query techniques allow for powerful data access.'),
(72054, 2005, 'bio', 'BEST: binding-site estimation suite of tools', 'Che, Dongsheng|Jensen, Shane|Cai, Liming|Liu, Jun S', 'Department of Computer Science, University of Georgia, Athens, GA 30602, USA. dsche@uga.edu|Department of Computer Science, University of Georgia, Athens, GA 30602, USA. dsche@uga.edu|Department of Computer Science, University of Georgia, Athens, GA 30602, USA. dsche@uga.edu|Department of Computer Science, University of Georgia, Athens, GA 30602, USA. dsche@uga.edu', 'Georgia|Georgia|Georgia|Georgia', 0, 'Algorithms|Binding Sites|Computer Graphics|DNA|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bti425', '15814553', 'The purpose of our Binding-site Estimation Suite of Tools (BEST) is two-fold: to provide a platform for using and comparing different motif-finding programs for transcription factor binding site prediction, and to improve the accuracy of these predictions by further optimization. Our software package BEST includes four commonly used motif-finding programs: AlignACE, BioProspector, CONSENSUS and MEME, as well as the optimization program BioOptimizer. BEST allows the user to run programs either separately or sequentially and manages all programs by automating the common inputs and the optimization procedure. The BEST system was implemented in Qt, a C++ application development framework, and was compiled and executed on Linux operating systems.'),
(72055, 2005, 'bio', 'EGene: a configurable pipeline generation system for automated sequence analysis', 'Durham, Alan M|Kashiwabara, André Y|Matsunaga, Fernando T G|Ahagon, Paulo H|Rainone, Flávia|Varuzza, Leonardo|Gruber, Arthur', 'Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br|Depto. de Ciências da Computação, Instituto de Matemática e Estatística São Paulo, SP, 05508-900, Brazil. alan@ime.usp.br', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 0, 'Chromosome Mapping|Computer Graphics|Database Management Systems|Databases, Nucleic Acid|Information Storage and Retrieval|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti424', '15814554', 'EGene is a generic, flexible and modular pipeline generation system that makes pipeline construction a modular job. EGene allows for third-party programs to be used and integrated according to the needs of distinct projects and without any previous programming or formal language experience being required. EGene comes with CoEd, a visual tool to facilitate pipeline construction and documentation. A series of components to build pipelines for sequence processing is provided.'),
(72056, 2005, 'bio', 'Prediction of protein solvent accessibility using fuzzy k-nearest neighbor method', 'Sim, Jaehyun|Kim, Seung-Yeon|Lee, Julian', 'Department of Bioinformatics and Life Science, Bioinformatics and Molecular Design Technology Innovation Center, Soongsil University, Seoul 156-743, South Korea.|Department of Bioinformatics and Life Science, Bioinformatics and Molecular Design Technology Innovation Center, Soongsil University, Seoul 156-743, South Korea.|Department of Bioinformatics and Life Science, Bioinformatics and Molecular Design Technology Innovation Center, Soongsil University, Seoul 156-743, South Korea.', '-|-|-', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Fuzzy Logic|Models, Chemical|Models, Molecular|Numerical Analysis, Computer-Assisted|Pattern Recognition, Automated|Protein Conformation|Proteins|Sequence Analysis, Protein|Solvents', 'Comparative Study', '10.1093/bioinformatics/bti423', '15814555', 'The solvent accessibility of amino acid residues plays an important role in tertiary structure prediction, especially in the absence of significant sequence similarity of a query protein to those with known structures. The prediction of solvent accessibility is less accurate than secondary structure prediction in spite of improvements in recent researches. The k-nearest neighbor method, a simple but powerful classification algorithm, has never been applied to the prediction of solvent accessibility, although it has been used frequently for the classification of biological and medical data.'),
(72057, 2005, 'bio', 'Penalized Cox regression analysis in the high-dimensional and low-sample size settings, with applications to microarray gene expression data', 'Gui, Jiang|Li, Hongzhe', 'Department of Statistics, University of California Davis, CA 95616, USA.|Department of Statistics, University of California Davis, CA 95616, USA.', 'United States|United States', 252, 'Biomarkers, Tumor|Computer Simulation|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Lymphoma, Large B-Cell, Diffuse|Models, Biological|Models, Statistical|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Prevalence|Proportional Hazards Models|Regression Analysis|Reproducibility of Results|Risk Assessment|Risk Factors|Sample Size|Sensitivity and Specificity|Survival Analysis|Survival Rate', 'Evaluation Studies', '10.1093/bioinformatics/bti422', '15814556', 'An important application of microarray technology is to relate gene expression profiles to various clinical phenotypes of patients. Success has been demonstrated in molecular classification of cancer in which the gene expression data serve as predictors and different types of cancer serve as a categorical outcome variable. However, there has been less research in linking gene expression profiles to the censored survival data such as patients overall survival time or time to cancer relapse. It would be desirable to have models with good prediction accuracy and parsimony property.'),
(72058, 2005, 'bio', 'Multiclass cancer classification and biomarker discovery using GA-based algorithms', 'Liu, Jane Jijun|Cutler, Gene|Li, Wuxiong|Pan, Zheng|Peng, Sihua|Hoey, Tim|Chen, Liangbiao|Ling, Xuefeng Bruce', 'Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.|Tularik Inc., South San Francisco, CA 94080, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Artificial Intelligence|Biomarkers, Tumor|Diagnosis, Computer-Assisted|Gene Expression Profiling|Humans|Neoplasm Proteins|Neoplasms|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bti419', '15814557', 'The development of microarray-based high-throughput gene profiling has led to the hope that this technology could provide an efficient and accurate means of diagnosing and classifying tumors, as well as predicting prognoses and effective treatments. However, the large amount of data generated by microarrays requires effective reduction of discriminant gene features into reliable sets of tumor biomarkers for such multiclass tumor discrimination. The availability of reliable sets of biomarkers, especially serum biomarkers, should have a major impact on our understanding and treatment of cancer.'),
(72059, 2005, 'bio', 'MEDS and PocR are novel domains with a predicted role in sensing simple hydrocarbon derivatives in prokaryotic signal transduction systems', 'Anantharaman, Vivek|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.', 'United States|United States', 17, 'Bacterial Proteins|Binding Sites|Conserved Sequence|DNA-Binding Proteins|Hydrocarbons|Protein Binding|Protein Interaction Mapping|Protein Structure, Tertiary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Signal Transduction|Trans-Activators', 'Journal Article', '10.1093/bioinformatics/bti418', '15814558', 'We identify two conserved domains in diverse bacterial and archaeal signaling proteins. One of them, the MEDS domain, is typified by the DmcR protein from Methylococcus and the other by the PocR protein of Salmonella typhi. We provide evidence that both these domains are likely to sense simple hydrocarbon derivatives and transduce downstream signals on binding these ligands. The PocR ligand-binding domain is shown to contain a novel variant of the fold found in PAS and GAF domains. The MEDS domain is present in both methylotrophs and complex methanogens, and both the MEDS and PocR domains show a lineage-specific expansion in the latter organisms, suggesting a role in sensing their principle growth substrates. The MEDS domain is also found in the negative regulators of the sigma factor SigB in actinomycetes, including pathogens like Mycobacterium tuberculosis. Hence it is possible that these sigma factors, involved in aerial mycelium development and stress response in the actinomycetes, might be under the regulation of as yet uncharacterized small molecules.'),
(72060, 2005, 'bio', 'A model-based scan statistic for identifying extreme chromosomal regions of gene expression in human tumors', 'Levin, Albert M|Ghosh, Debashis|Cho, Kathleen R|Kardia, Sharon L R', 'Department of Epidemiology, University of Michigan, Ann Arbor, MI 48104-3028, USA. fcouples@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, MI 48104-3028, USA. fcouples@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, MI 48104-3028, USA. fcouples@umich.edu|Department of Epidemiology, University of Michigan, Ann Arbor, MI 48104-3028, USA. fcouples@umich.edu', 'United States|United States|United States|United States', 24, 'Base Composition|Biomarkers, Tumor|Chromosome Mapping|Chromosomes, Human, Pair 17|Computer Simulation|Gene Expression Profiling|Genetic Predisposition to Disease|Genome, Human|Humans|Models, Genetic|Models, Statistical|Neoplasm Proteins|Neoplasms', 'Journal Article', '10.1093/bioinformatics/bti417', '15814559', 'The analysis of gene expression data in its chromosomal context has been a recent development in cancer research. However, currently available methods fail to account for variation in the distance between genes, gene density and genomic features (e.g. GC content) in identifying increased or decreased chromosomal regions of gene expression.'),
(72061, 2005, 'bio', 'Common denominator procedure: a novel approach to gene-expression data mining for identification of phenotype-specific genes', 'Korn, René|Röhrig, Sascha|Schulze-Kremer, Steffen|Brinkmann, Ulrich', 'Xantos Biomedicine AG, Max-Lebsche-Platz 31, 81377 München, Germany.|Xantos Biomedicine AG, Max-Lebsche-Platz 31, 81377 München, Germany.|Xantos Biomedicine AG, Max-Lebsche-Platz 31, 81377 München, Germany.|Xantos Biomedicine AG, Max-Lebsche-Platz 31, 81377 München, Germany.', 'Germany|Germany|Germany|Germany', 4, 'Angiogenic Proteins|Database Management Systems|Databases, Protein|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Gene Library|Humans|Information Storage and Retrieval|Neoplasm Proteins|Neoplasms|Neovascularization, Pathologic|Phenotype|Signal Transduction', 'Evaluation Studies', '10.1093/bioinformatics/bti416', '15814560', 'We have established a novel data mining procedure for the identification of genes associated with pre-defined phenotypes and/or molecular pathways. Based on the observation that these genes are frequently expressed in the same place or in close proximity at about the same time, we have devised an approach termed Common Denominator Procedure. One unusual feature of this approach is that the specificity and probability to identify genes linked to the desired phenotype/pathway increase with greater diversity of the input data.'),
(72062, 2005, 'bio', 'POSBIOTM-NER: a trainable biomedical named-entity recognition system', 'Song, Yu|Kim, Eunju|Lee, Gary Geunbae|Yi, Byoung-Kee', 'Department of CSE, POSTECH Pohang, 790-784, Korea. songyu@postech.ac.kr|Department of CSE, POSTECH Pohang, 790-784, Korea. songyu@postech.ac.kr|Department of CSE, POSTECH Pohang, 790-784, Korea. songyu@postech.ac.kr|Department of CSE, POSTECH Pohang, 790-784, Korea. songyu@postech.ac.kr', '-|-|-|-', 16, 'Algorithms|Artificial Intelligence|Biomedical Research|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Software|Terminology as Topic|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bti414', '15814561', 'POSBIOTM-NER is a trainable biomedical named-entity recognition system. POSBIOTM-NER can be automatically trained and adapted to new datasets without performance degradation, using CRF (conditional random field) machine learning techniques and automatic linguistic feature analysis. Currently, we have trained our system on three different datasets. GENIA-NER was trained based on GENIA Corpus, GENE-NER based on BioCreative data and GPCR-NER based on our own POSBIOTM/NE corpus, respectively, which would be used in GPCR-related pathway extraction.'),
(72063, 2005, 'bio', 'Probe rank approaches for gene selection in oligonucleotide arrays with a small number of replicates', 'Chen, Dung-Tsa|Chen, James J|Soong, Seng-jaw', 'Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, 153 Wallace Tumor Institute, 1824 6th Avenue South, Birmingham, AL 35294, USA. dtchen@uab.edu|Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, 153 Wallace Tumor Institute, 1824 6th Avenue South, Birmingham, AL 35294, USA. dtchen@uab.edu|Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama at Birmingham, 153 Wallace Tumor Institute, 1824 6th Avenue South, Birmingham, AL 35294, USA. dtchen@uab.edu', 'United States|United States|United States', 8, 'Algorithms|Computer Simulation|DNA Probes|DNA Replication|Gene Expression Profiling|Genes, Duplicate|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis', 'Evaluation Studies', '10.1093/bioinformatics/bti413', '15814562', 'One major area of interest in analyzing oligonucleotide gene array data is identifying differentially expressed genes. A challenge to biostatisticians is to develop an approach to summarizing probe-level information that adequately reflects the true expression level while accounting for probe variation, chip variation and interaction effects. Various statistical tools, such as MAS and RMA, have been developed to address this issue. In these approaches, the probe level expression data are summarized into gene level data, which are then used for downstream statistical analysis. Since probe variation is often larger than chip variation and there is also a potential interaction effect between probe affinity and treatment effect, strategies such as a gene level analysis, may not be optimal. In this study, we propose a procedure to analyze probe level data for selecting differentially expressed genes under two treatment conditions (groups) with a small number of replicates. The probe level discrepancy between two groups can be measured by a difference of the percentiles of probe perfect-match (PM) ranks or of probe PM weighted ranks. The difference is then compared with a pre-specified threshold to determine differentially expressed genes. The probe level approach takes into account non-homogenous treatment effects and reduces possible cross-hybridization effects across a set of probes.'),
(72064, 2005, 'bio', 'ROBIN: a tool for genome rearrangement of block-interchanges', 'Lu, Chin Lung|Wang, Tsui Ching|Lin, Ying Chih|Tang, Chuan Yi', 'Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan, ROC. cllu@mail.nctu.edu.tw|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan, ROC. cllu@mail.nctu.edu.tw|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan, ROC. cllu@mail.nctu.edu.tw|Department of Biological Science and Technology, National Chiao Tung University, Hsinchu 300, Taiwan, ROC. cllu@mail.nctu.edu.tw', '-|-|-|-', 10, 'Algorithms|Chromosome Mapping|Gene Rearrangement|Internet|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/bti412', '15814563', 'ROBIN is a web server for analyzing genome rearrangement of block-interchanges between two chromosomal genomes. It takes two or more linear/circular chromosomes as its input, and computes the number of minimum block-interchange rearrangements between any two input chromosomes for transforming one chromosome into another and also determines an optimal scenario taking this number of rearrangements. The input can be either bacterial-size sequence data or landmark-order data. If the input is sequence data, ROBIN will automatically search for the identical landmarks that are the homologous/conserved regions shared by all the input sequences.'),
(72065, 2005, 'bio', 'VariScan: Analysis of evolutionary patterns from large-scale DNA sequence polymorphism data', 'Vilella, Albert J|Blanco-Garcia, Angel|Hutter, Stephan|Rozas, Julio', 'Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.|Departament de Genètica, Facultat de Biologia, Universitat de Barcelona, Diagonal 645, 08028 Barcelona, Spain.', 'Spain|Spain|Spain|Spain', 69, 'Algorithms|Chromosome Mapping|Computer Graphics|DNA Mutational Analysis|Evolution, Molecular|Polymorphism, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti403', '15814564', 'VeriScan is a software package for the analysis of DNA sequence polymorphisms at the whole genome scale. Among other features, the software (1) can conduct many population genetic analyses, (2) incorporates a multiresolution wavelet transform-based method that allows capturing relevant information from DNA polymorphism data, (3) facilitates the visualization of the results in the most commonly used genome browsers.'),
(72066, 2005, 'bio', 'Literature mining and database annotation of protein phosphorylation using a rule-based system', 'Hu, Z Z|Narayanaswamy, M|Ravikumar, K E|Vijay-Shanker, K|Wu, C H', 'Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA. zh9@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA. zh9@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA. zh9@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA. zh9@georgetown.edu|Department of Biochemistry and Molecular Biology, Georgetown University Medical Center, Washington, DC 20057, USA. zh9@georgetown.edu', 'United States|United States|United States|United States|United States', 68, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Periodicals as Topic|Phosphorylation|Proteins|Semantics|Vocabulary, Controlled', 'Evaluation Studies', '10.1093/bioinformatics/bti390', '15814565', 'A large volume of experimental data on protein phosphorylation is buried in the fast-growing PubMed literature. While of great value, such information is limited in databases owing to the laborious process of literature-based curation. Computational literature mining holds promise to facilitate database curation.'),
(72067, 2005, 'bio', 'pFind: a novel database-searching software system for automated peptide and protein identification via tandem mass spectrometry', 'Li, Dequan|Fu, Yan|Sun, Ruixiang|Ling, Charles X|Wei, Yonggang|Zhou, Hu|Zeng, Rong|Yang, Qiang|He, Simin|Gao, Wen', 'Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences Beijing 100080, China. dqli@jdl.ac.cn', 'China|China|China|China|China|China|China|China|China|China', 106, 'Algorithms|Artificial Intelligence|Database Management Systems|Databases, Protein|Gene Expression Profiling|Mass Spectrometry|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti439', '15817687', 'Research in proteomics requires powerful database-searching software to automatically identify protein sequences in a complex protein mixture via tandem mass spectrometry. In this paper, we describe a novel database-searching software system called pFind (peptide/protein Finder), which employs an effective peptide-scoring algorithm that we reported earlier. The pFind server is implemented with the C++ STL, .Net and XML technologies. As a result, high speed and good usability of the software are achieved.'),
(72068, 2005, 'bio', 'twilight, a Bioconductor package for estimating the local false discovery rate', 'Scheid, Stefanie|Spang, Rainer', 'Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 63-73, D-14195 Berlin, Germany. stefanie.scheid@molgen.mpg.de|Max Planck Institute for Molecular Genetics, Department of Computational Molecular Biology, Ihnestrasse 63-73, D-14195 Berlin, Germany. stefanie.scheid@molgen.mpg.de', 'Germany|Germany', 37, 'Algorithms|Computer Graphics|Computer Simulation|False Positive Reactions|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti436', '15817688', 'twilight is a Bioconductor compatible package for analysing the statistical significance of differentially expressed genes. It is based on the concept of the local false discovery rate (FDR), a generalization of the frequently used global FDR. twilight implements the heuristic search algorithm for estimating the local FDR introduced in our earlier work. In addition to the raw significance measures, it produces diagnostic plots, which provide insight into the extent of differential expression across genes.'),
(72069, 2005, 'bio', 'Rapid and selective surveillance of Arabidopsis thaliana genome annotations with Centrifuge', 'Armand, Florence|Bucher, Philipp|Jongeneel, C Victor|Farmer, Edward E', 'Gene Expression Laboratory, Plant Molecular Biology, University of Lausanne, Biology Building, 1015 Lausanne, Switzerland.|Gene Expression Laboratory, Plant Molecular Biology, University of Lausanne, Biology Building, 1015 Lausanne, Switzerland.|Gene Expression Laboratory, Plant Molecular Biology, University of Lausanne, Biology Building, 1015 Lausanne, Switzerland.|Gene Expression Laboratory, Plant Molecular Biology, University of Lausanne, Biology Building, 1015 Lausanne, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland', 0, 'Arabidopsis|Arabidopsis Proteins|Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bti435', '15817689', 'Centrifuge is a user-friendly system to simultaneously access Arabidopsis gene annotations and intra- and inter-organism sequence comparison data. The tool allows rapid retrieval of user-selected data for each annotated Arabidopsis gene providing, in any combination, data on the following features: predicted protein properties such as mass, pI, cellular location and transmembrane domains, SWISS-PROT annotations, Interpro domains, Gene Ontology records, verified transcription, BLAST matches to the proteomes of A.thaliana, Oryza sativa (rice), Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. The tool lends itself particularly well to the rapid analysis of contigs or of tens or hundreds of genes identified by high-throughput gene expression experiments. In these cases, a summary table of principal predicted protein features for all genes is given followed by more detailed reports for each individual gene. Centrifuge can also be used for single gene analysis or in a word search mode.');
