INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71040, 2004, 'bio', 'Database model and specification of GermOnline Release 20, a cross-species community annotation knowledgebase on germ cell differentiation', 'Wiederkehr, C|Basavaraj, R|Sarrauste de Menthière, C|Koch, R|Schlecht, U|Hermida, L|Masdoua, B|Ishii, R|Cassen, V|Yamamoto, M|Lane, C|Cherry, M|Lamb, N|Primig, M', 'Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.|Biozentrum and Swiss Institute of Bioinformatics, Klingelbergstrasse 50-70, 4056 Basel, Switzerland.', 'Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Switzerland|Swit', 0, 'Animals|Artificial Intelligence|Cell Differentiation|Database Management Systems|Databases, Genetic|Documentation|Gene Expression Profiling|Germ Cells|Humans|Information Dissemination|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Species Specificity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth030', '14751982', 'GermOnline is a web-accessible relational database that enables life scientists to make a significant and sustained contribution to the annotation of genes relevant for the fields of mitosis, meiosis, germ line development and gametogenesis across species. This novel approach to genome annotation includes a platform for knowledge submission and curation as well as microarray data storage and visualization hosted by a global network of servers.'),
(71041, 2004, 'bio', 'Measuring the similarity of protein structures by means of the universal similarity metric', 'Krasnogor, N|Pelta, D A', 'Automated Scheduling, Optimisation and Planning Group, University of Nottingham, Nottingham NG8 1BB, UK. Natalio.Krasnogor@nottingham.ac.uk|Automated Scheduling, Optimisation and Planning Group, University of Nottingham, Nottingham NG8 1BB, UK. Natalio.Krasnogor@nottingham.ac.uk', 'United Kingdom|United Kingdom', 96, 'Algorithms|Amino Acid Sequence|Cluster Analysis|Databases, Protein|Models, Molecular|Molecular Sequence Data|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth031', '14751983', 'As an increasing number of protein structures become available, the need for algorithms that can quantify the similarity between protein structures increases as well. Thus, the comparison of proteins structures, and their clustering accordingly to a given similarity measure, is at the core of todays biomedical research. In this paper, we show how an algorithmic information theory inspired Universal Similarity Metric (USM) can be used to calculate similarities between protein pairs. The method, besides being theoretically supported, is surprisingly simple to implement and computationally efficient.'),
(71042, 2004, 'bio', 'On the significance of sequence alignments when using multiple scoring matrices', 'Frommlet, Florian|Futschik, Andreas|Bogdan, Malgorzata', 'Department of Medical Statistics, University of Vienna, Vienna, Austria. Florian.Frommlet@univie.ac.at|Department of Medical Statistics, University of Vienna, Vienna, Austria. Florian.Frommlet@univie.ac.at|Department of Medical Statistics, University of Vienna, Vienna, Austria. Florian.Frommlet@univie.ac.at', 'Austria|Austria|Austria', 0, 'Data Interpretation, Statistical|Databases, Protein|Models, Genetic|Models, Statistical|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg498', '14751984', 'Pairwise local sequence alignment is commonly used to search data bases for sequences related to some query sequence. Alignments are obtained using a scoring matrix that takes into account the different frequencies of occurrence of the various types of amino acid substitutions. Software like BLAST provides the user with a set of scoring matrices available to choose from, and in the literature it is sometimes recommended to try several scoring matrices on the sequences of interest. The significance of an alignment is usually assessed by looking at E-values and p-values. While sequence lengths and data base sizes enter the standard calculations of significance, it is much less common to take the use of several scoring matrices on the same sequences into account. Altschul proposed corrections of the p-value that account for the simultaneous use of an infinite number of PAM matrices. Here we consider the more realistic situation where the user may choose from a finite set of popular PAM and BLOSUM matrices, in particular the ones available in BLAST. It turns out that the significance of a result can be considerably overestimated, if a set of substitution matrices is used in an alignment problem and the most significant alignment is then quoted.'),
(71043, 2004, 'bio', 'Using functional and organizational information to improve genome-wide computational prediction of transcription units on pathway-genome databases', 'Romero, P R|Karp, P D', 'Bioinformatics Research Group, Artificial Intelligence Center, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 950151, USA.|Bioinformatics Research Group, Artificial Intelligence Center, SRI International, 333 Ravenswood Avenue, Menlo Park, CA 950151, USA.', 'United States|United States', 58, 'Algorithms|Bacterial Proteins|Chromosome Mapping|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Genome, Bacterial|Information Storage and Retrieval|Signal Transduction|Software|Structure-Activity Relationship|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg471', '14751985', 'The prediction of transcription units (TUs, which are similar to operons) is an important problem that has been tackled using many different approaches. The availability of complete microbial genomes has made genome-wide TU predictions possible. Pathway-genome databases (PGDBs) add metabolic and other organizational (i.e. protein complexes) information to the annotated genome, and are able to capture TU organization information. These characteristics of PGDBs make them a suitable framework for the development and implementation of TU predictors.'),
(71044, 2004, 'bio', 'The PCR suite', 'van Baren, Marijke J|Heutink, Peter', 'Department of Clinical Genetics, Erasmus Medical Center, Dr Molewaterplein 50, 3015 GE Rotterdam, The Netherlands. jeltje@cse.wustl.edu|Department of Clinical Genetics, Erasmus Medical Center, Dr Molewaterplein 50, 3015 GE Rotterdam, The Netherlands. jeltje@cse.wustl.edu', 'Netherlands|Netherlands', 28, 'Algorithms|Combinatorial Chemistry Techniques|DNA Primers|Gene Expression Profiling|Internet|Polymerase Chain Reaction|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg473', '14751986', 'The web application PCR Suite is an extension of the primer design program Primer3. It allows the design of primer sets encompassing single nucleotide polymorphisms, all exons of a single gene, all open reading frames in a list of cDNAs or the creation of overlapping PCR products.'),
(71045, 2004, 'bio', 'Genotyping of single nucleotide polymorphism using model-based clustering', 'Fujisawa, H|Eguchi, S|Ushijima, M|Miyata, S|Miki, Y|Muto, T|Matsuura, M', 'Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp|Institute of Statistical Mathematics, Tokyo 106-8569, Japan. fujisawa@ism.ac.jp', 'Japan|Japan|Japan|Japan|Japan|Japan|Japan', 0, 'Algorithms|Base Sequence|Cluster Analysis|Gene Expression Profiling|Genotype|Likelihood Functions|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg475', '14751987', 'Single nucleotide polymorphisms have been investigated as biological markers and the representative high-throughput genotyping method is a combination of the Invader assay and a statistical clustering method. A typical statistical clustering method is the k-means method, but it often fails because of the lack of flexibility. An alternative fast and reliable method is therefore desirable.'),
(71046, 2004, 'bio', 'Java-based application framework for visualization of gene regulatory region annotations', 'Sun, Hao|Davuluri, Ramana V', 'Human Cancer Genetics Program, Comprehensive Cancer Center, Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, 420 W 12th Avenue, TMRF 524, Columbus, OH 43210, USA.|Human Cancer Genetics Program, Comprehensive Cancer Center, Department of Molecular Virology, Immunology and Medical Genetics, The Ohio State University, 420 W 12th Avenue, TMRF 524, Columbus, OH 43210, USA.', 'United States|United States', 10, 'Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Hypermedia|Information Storage and Retrieval|Internet|Programming Languages|Regulatory Sequences, Nucleic Acid|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg476', '14751988', 'The genome sequences of several organisms are either complete, or being sequenced. Each genome needs to be integrated with various types of annotations, e.g. locations of genes, promoters and other functional elements such as transcriptional regulatory elements. A robust application framework will be useful for developing web-based applications to visualize various genome annotations.'),
(71047, 2004, 'bio', 'Bio-support vector machines for computational proteomics', 'Yang, Zheng Rong|Chou, Kuo-Chen', 'Department of Computer Science, Exeter University, Exeter EX4 4PT, UK. Z.R.Yang@exeter.ac.uk|Department of Computer Science, Exeter University, Exeter EX4 4PT, UK. Z.R.Yang@exeter.ac.uk', 'United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Computational Biology|Computing Methodologies|Databases, Protein|Molecular Sequence Data|Pattern Recognition, Automated|Protein Binding|Proteins|Proteome|Proteomics|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg477', '14751989', 'One of the most important issues in computational proteomics is to produce a prediction model for the classification or annotation of biological function of novel protein sequences. In order to improve the prediction accuracy, much attention has been paid to the improvement of the performance of the algorithms used, few is for solving the fundamental issue, namely, amino acid encoding as most existing pattern recognition algorithms are unable to recognize amino acids in protein sequences. Importantly, the most commonly used amino acid encoding method has the flaw that leads to large computational cost and recognition bias.'),
(71048, 2004, 'bio', 'GENIUS II: a high-throughput database system for linking ORFs in complete genomes to known protein three-dimensional structures', 'Yabuki, Yukimitsu|Mukai, Yuri|Swindells, Mark B|Suwa, Makiko', 'Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.|Computational Biology Research Center (CBRC), National Institute of Advanced Industrial Science and Technology (AIST), Aomi Frontier Building 17F, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan.', 'Japan|Japan|Japan|Japan', 2, 'Algorithms|Amino Acid Sequence|Database Management Systems|Databases, Protein|Genome|Information Storage and Retrieval|Molecular Sequence Data|Open Reading Frames|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btg478', '14751990', 'GENIUS II is an automated database system in which open reading frames (ORFs) in complete genomes are assigned to known protein three-dimensional (3D) structures. The system uses the multiple intermediate sequence search method in which query and target sequences are linked by intermediate sequences gathered by PSI-BLAST search. By applying the system to 129 complete genomes, 43.8% on average of the ORFs in the genomes were assigned to known 3D structures and the results are available for free at GENIUS II web site.'),
(71049, 2004, 'bio', 'Dominant spectral component analysis for transcriptional regulations using microarray time-series data', 'Yeung, Lap Kun|Szeto, Lap Keung|Liew, Alan Wee-Chung|Yan, Hong', 'Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong. lkyeung@msn.com|Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong. lkyeung@msn.com|Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong. lkyeung@msn.com|Department of Computer Engineering and Information Technology, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong. lkyeung@msn.com', 'Hong Kong|Hong Kong|Hong Kong|Hong Kong', 34, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Regression Analysis|Time Factors|Transcription Factors|Transcriptional Activation', 'Comparative Study', '10.1093/bioinformatics/btg479', '14751991', 'Microarray time-series data provides us a possible means for identification of transcriptional regulation relationships among genes. Currently, the most commonly used method in determining whether or not two genes have a potential regulatory relationship is to measure their expressional similarity using Pearsons correlation coefficient. Although this traditional correlation method has been successfully applied to find functionally correlated genes, it does have many limitations. In the hope of overcoming such circumstances and getting more insights into the transcriptional regulatory issue, we propose an autoregressive (AR)-based technique for detection of potential regulated gene pairs from time-series microarray measurements.'),
(71050, 2004, 'bio', 'Regression trees for regulatory element identification', 'Phuong, Tu Minh|Lee, Doheon|Lee, Kwang Hyung', 'Department of BioSystems, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea.|Department of BioSystems, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea.|Department of BioSystems, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong Yuseong-gu, Daejeon 305-701, Korea.', '-|-|-', 24, 'Algorithms|Amino Acid Motifs|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Models, Genetic|Models, Statistical|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg480', '14751992', 'The transcription of a gene is largely determined by short sequence motifs that serve as binding sites for transcription factors. Recent findings suggest direct relationships between the motifs and gene expression levels. In this work, we present a method for identifying regulatory motifs. Our method makes use of tree-based techniques for recovering the relationships between motifs and gene expression levels.'),
(71051, 2004, 'bio', 'STAM: simple transmembrane alignment method', 'Shafrir, Yinon|Guy, H Robert', 'National Cancer Institute, LECB, MSC 5677, 12 South Drive, Bethesda, MD 20892-5677, USA. yinon@nih.gov|National Cancer Institute, LECB, MSC 5677, 12 South Drive, Bethesda, MD 20892-5677, USA. yinon@nih.gov', 'United States|United States', 5, 'Algorithms|Amino Acid Motifs|Amino Acid Sequence|Membrane Proteins|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg482', '14751993', 'The database of transmembrane protein (TMP) structures is still very small. At the same time, more and more TMP sequences are being determined. Molecular modeling is an interim answer that may bridge the gap between the two databases. The first step in homology modeling is to achieve a good alignment between the target sequences and the template structure. However, since most algorithms to obtain the alignments were constructed with data derived from globular proteins, they perform poorly when applied to TMPs. In our application, we automate the alignment procedure and design it specifically for TMP. We first identify segments likely to form transmembrane alpha-helices. We then apply different sets of criteria for transmembrane and non-transmembrane segments. For example, the penalty for insertion/deletions in the transmembrane segments is much higher than that of a penalty in the loop region. Different substitution matrices are used since the frequencies of occurrence of the various amino acids differ for transmembrane segments and water-soluble domains.'),
(71052, 2004, 'bio', 'Predicting protein structure classes from function predictions', 'Sommer, I|Rahnenführer, J|Domingues, F S|de Lichtenberg, U|Lengauer, T', 'Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, Saarbrücken D-66123, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, Saarbrücken D-66123, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, Saarbrücken D-66123, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, Saarbrücken D-66123, Germany. sommer@mpi-sb.mpg.de|Department of Computational Biology and Applied Algorithmics, Max-Planck-Institute for Informatics, Stuhlsatzenhausweg 85, Saarbrücken D-66123, Germany. sommer@mpi-sb.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg483', '14751994', 'We introduce a new approach to using the information contained in sequence-to-function prediction data in order to recognize protein template classes, a critical step in predicting protein structure. The data on which our method is based comprise probabilities of functional categories, for given query sequences these probabilities are obtained by a neural net that has previously been trained on a variety of functionally important features. On a training set of sequences we assess the relevance of individual functional categories for identifying a given structural family. Using a combination of the most relevant categories, the likelihood of a query sequence to belong to a specific family can be estimated.'),
(71053, 2004, 'bio', 'Reproducibility of SELDI-TOF protein patterns in serum: comparing datasets from different experiments', 'Baggerly, Keith A|Morris, Jeffrey S|Coombes, Kevin R', 'Department of Biostatistics, U.T. M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org|Department of Biostatistics, U.T. M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org|Department of Biostatistics, U.T. M.D. Anderson Cancer Center, 1515 Holcombe Blvd, Box 447, Houston, TX 77030-4009, USA. kabagg@mdanderson.org', 'United States|United States|United States', 0, 'Algorithms|Artifacts|Blood Proteins|Databases, Protein|Diagnosis, Computer-Assisted|Female|Humans|Lasers|Mass Spectrometry|Ovarian Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg484', '14751995', 'There has been much interest in using patterns derived from surface-enhanced laser desorption and ionization (SELDI) protein mass spectra from serum to differentiate samples from patients both with and without disease. Such patterns have been used without identification of the underlying proteins responsible. However, there are questions as to the stability of this procedure over multiple experiments.'),
(71054, 2004, 'bio', 'Quality of alignment comparison by COMPASS improves with inclusion of diverse confident homologs', 'Sadreyev, Ruslan I|Grishin, Nick V', 'Howard Hughes Medical Institute, and Department of Biochemistry, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA.|Howard Hughes Medical Institute, and Department of Biochemistry, University of Texas Southwestern Medical Center, 5323, Harry Hines Blvd, Dallas, TX 75390-9050, USA.', 'United States|United States', 25, 'Algorithms|Amino Acid Sequence|Databases, Protein|Gene Expression Profiling|Genetic Variation|Molecular Sequence Data|Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg485', '14751996', 'Adding more distant homologs to a multiple alignment and thus increasing its diversity may eventually deteriorate the numerical profile constructed from this alignment. Here, we addressed the question whether such a diversity limit can be reached in the alignments of confident homologs found by PSI-BLAST, and we analyzed the dependence of the quality of the profile-profile comparison made by COMPASS on the sequence diversity within these alignments.'),
(71055, 2004, 'bio', 'ESPD: a pattern detection model underlying gene expression profiles', 'Tang, Chun|Zhang, Aidong|Ramanathan, Murali', 'Department of Computer Science and Engineering, State University of New York at Buffalo, NY 14260, USA. chuntang@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York at Buffalo, NY 14260, USA. chuntang@cse.buffalo.edu|Department of Computer Science and Engineering, State University of New York at Buffalo, NY 14260, USA. chuntang@cse.buffalo.edu', 'United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg486', '14751997', 'DNA arrays permit rapid, large-scale screening for patterns of gene expression and simultaneously yield the expression levels of thousands of genes for samples. The number of samples is usually limited, and such datasets are very sparse in high-dimensional gene space. Furthermore, most of the genes collected may not necessarily be of interest and uncertainty about which genes are relevant makes it difficult to construct an informative gene space. Unsupervised empirical sample pattern discovery and informative genes identification of such sparse high-dimensional datasets present interesting but challenging problems.'),
(71056, 2004, 'bio', 'Comparative analysis of algorithms for signal quantitation from oligonucleotide microarrays', 'Barash, Yoseph|Dehan, Elinor|Krupsky, Meir|Franklin, Wilbur|Geraci, Marc|Friedman, Nir|Kaminski, Naftali', 'School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.|School of Computer Science and Engineering, Hebrew University, Jerusalem, 91904, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel', 72, 'Algorithms|Benchmarking|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg487', '14751998', 'Recent years exponential increase in DNA microarrays experiments has motivated the development of many signal quantitation (SQ) algorithms. These algorithms perform various transformations on the actual measurements aimed to enable researchers to compare readings of different genes quantitatively within one experiment and across separate experiments. However, it is relatively unclear whether there is a best algorithm to quantitate microarray data. The ability to compare and assess such algorithms is crucial for any downstream analysis. In this work, we suggest a methodology for comparing different signal quantitation algorithms for gene expression data. Our aim is to enable researchers to compare the effect of different SQ algorithms on the specific dataset they are dealing with. We combine two kinds of tests to assess the effect of an SQ algorithm in terms of signal to noise ratio. To assess noise, we exploit redundancy within the experimental dataset to test the variability of a given SQ algorithm output. For the effect of the SQ on the signal we evaluate the overabundance of differentially expressed genes using various statistical significance tests.'),
(71057, 2004, 'bio', 'Algorithms for variable length Markov chain modeling', 'Bejerano, Gill', 'Center for Biomolecular Science and Engineering, School of Engineering, University of California, Santa Cruz, CA 95064, USA. jill@soe.ucsc.edu', 'United States', 0, 'Algorithms|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis|Sequence Homology|Software', 'Journal Article', '10.1093/bioinformatics/btg489', '14751999', 'We present a general purpose implementation of variable length Markov models. Contrary to fixed order Markov models, these models are not restricted to a predefined uniform depth. Rather, by examining the training data, a model is constructed that fits higher order Markov dependencies where such contexts exist, while using lower order Markov dependencies elsewhere. As both theoretical and experimental results show, these models are capable of capturing rich signals from a modest amount of training data, without the use of hidden states.'),
(71058, 2004, 'bio', 'CAAT-Box, Contigs-Assembly and Annotation Tool-Box for genome sequencing projects', 'Frangeul, L|Glaser, P|Rusniok, C|Buchrieser, C|Duchaud, E|Dehoux, P|Kunst, F', 'Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr|Génopole, Institut Pasteur, 28 rue du Dr Roux, 75724 Paris 15, France. lfrangeu@pasteur.fr', 'France|France|France|France|France|France|France', 46, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Documentation|Genome|Information Storage and Retrieval|Sequence Analysis, DNA|Software|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/btg490', '14752000', 'Contigs-Assembly and Annotation Tool-Box (CAAT-Box) is a software package developed for the computational part of a genome project where the sequence is obtained by a shotgun strategy. CAAT-Box contains new tools to predict links between contigs by using similarity searches with other whole genome sequences. Most importantly, it allows annotation of a genome to commence during the finishing phase using a gene-oriented strategy. For this purpose, CAAT-Box creates an Individual Protein file (IPF) for each ORF of an assembly. The nucleotide sequence reported in an IPF corresponds to the sequence of the ORF with 500 additional bases before the ORF and 200 bases after. For annotation, additional information like Blast results can be added or linked to the IPFs as well as automatic and/or manual annotations. When a new assembly is performed, CAAT-Box creates new IPFs according to the old IPF panel. CAAT-Box recognizes the modified IPFs which are the only ones used for a new automatic analysis after each assembly. Using this strategy, the user works with a group of IPFs independently of the closure phase progression. The IPFs are accessible by a web server and can therefore be modified and commented by different groups.'),
(71059, 2004, 'bio', 'In silico analysis of complete bacterial genomes: PCR, AFLP-PCR and endonuclease restriction', 'Bikandi, Joseba|San Millán, Rosario|Rementeria, Aitor|Garaizar, Javier', 'Department of Immunology, Microbiology and Parasitology, University of the Basque Country, Paseo de la Universidad, 7, 01006 Vitoria-Gasteiz, Spain. oipbibij@lg.ehu.es|Department of Immunology, Microbiology and Parasitology, University of the Basque Country, Paseo de la Universidad, 7, 01006 Vitoria-Gasteiz, Spain. oipbibij@lg.ehu.es|Department of Immunology, Microbiology and Parasitology, University of the Basque Country, Paseo de la Universidad, 7, 01006 Vitoria-Gasteiz, Spain. oipbibij@lg.ehu.es|Department of Immunology, Microbiology and Parasitology, University of the Basque Country, Paseo de la Universidad, 7, 01006 Vitoria-Gasteiz, Spain. oipbibij@lg.ehu.es', 'Spain|Spain|Spain|Spain', 0, 'Algorithms|Computer Simulation|Electrophoresis, Gel, Pulsed-Field|Gene Expression Profiling|Genome, Bacterial|Internet|Models, Biological|Polymerase Chain Reaction|Polymorphism, Restriction Fragment Length|Restriction Mapping|Software', 'Journal Article', '10.1093/bioinformatics/btg491', '14752001', 'We have developed a website, www.in-silico.com, which runs a software program that performs three basic tasks in completely sequenced bacterial genomes by in silico analysis: PCR amplification, amplified fragment length polymorphism (AFLP-PCR) and endonuclease restriction. For PCR, after selection of the genome and introduction of primers, fragment size, DNA sequence and corresponding open reading frame (ORF) identity of the resulting PCR product is computed. Plasmids of sequenced species may be included in the analysis. Theoretical AFLP-PCR analyzes similar parameters, and includes a suggestion tool providing a list of commercial restriction enzyme pairs yielding up to 50 amplicons in the selected genome. Endonuclease restriction analysis of complete genomes and plasmids calculates the number of restriction sites for endonucleases in a given genome. If the number of fragments is 50 or fewer, pulsed field gel electrophoresis image and restriction maps are illustrated. Other tools that have been included in this site are ORF search by name and DNA to protein translation as well as restriction digestion of user-defined DNA sequences.'),
(71060, 2004, 'bio', 'Gene selection for oligonucleotide array: an approach using PM probe level data', 'Chen, Dung-Tsa|Lin, Sue-Hwa|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|DNA Probes|Gene Expression Profiling|Humans|Oligonucleotide Array Sequence Analysis|Prolactin|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg493', '14752002', 'Analysis of oligonucleotide array data, especially to select genes of interest, is a highly challenging task because of the large volume of information and various experimental factors. Moreover, interaction effect (i.e. expression changes depend on probe effects) complicates the analysis because current methods often use an additive model to analyze data. We propose an approach to address these issues with the aim of producing a more reliable selection of differentially expressed genes. The approach uses the rank for normalization, employs the percentile-range to measure expression variation, and applies various filters to monitor expression changes.'),
(71061, 2004, 'bio', 'Optimizing substitution matrices by separating score distributions', 'Hourai, Yuichiro|Akutsu, Tatsuya|Akiyama, Yutaka', 'Department of Computer Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. hourai@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. hourai@is.s.u-tokyo.ac.jp|Department of Computer Science, University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. hourai@is.s.u-tokyo.ac.jp', 'Japan|Japan|Japan', 11, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Databases, Protein|Models, Molecular|Models, Statistical|Molecular Sequence Data|Proteins|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg494', '14752003', 'Homology search is one of the most fundamental tools in Bioinformatics. Typical alignment algorithms use substitution matrices and gap costs. Thus, the improvement of substitution matrices increases accuracy of homology searches. Generally, substitution matrices are derived from aligned sequences whose relationships are known, and gap costs are determined by trial and error. To discriminate relationships more clearly, we are encouraged to optimize the substitution matrices from statistical viewpoints using both positive and negative examples utilizing Bayesian decision theory.'),
(71062, 2004, 'bio', 'Approximate geodesic distances reveal biologically relevant structures in microarray data', 'Nilsson, Jens|Fioretos, Thoas|Höglund, Mattias|Fontes, Magnus', 'Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. jensn@maths.lth.se|Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. jensn@maths.lth.se|Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. jensn@maths.lth.se|Centre for Mathematical Sciences, Lund University, Box 118, SE-221 00 Lund, Sweden. jensn@maths.lth.se', 'Sweden|Sweden|Sweden|Sweden', 0, 'Algorithms|Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Humans|Linkage Disequilibrium|Lung Neoplasms|Lymphoma|Oligonucleotide Array Sequence Analysis|Sequence Analysis, DNA|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg496', '14752004', 'Genome-wide gene expression measurements, as currently determined by the microarray technology, can be represented mathematically as points in a high-dimensional gene expression space. Genes interact with each other in regulatory networks, restricting the cellular gene expression profiles to a certain manifold, or surface, in gene expression space. To obtain knowledge about this manifold, various dimensionality reduction methods and distance metrics are used. For data points distributed on curved manifolds, a sensible distance measure would be the geodesic distance along the manifold. In this work, we examine whether an approximate geodesic distance measure captures biological similarities better than the traditionally used Euclidean distance.'),
(71063, 2004, 'bio', 'Preference of simple sequence repeats in coding and non-coding regions of Arabidopsis thaliana', 'Zhang, Lida|Yuan, Dejun|Yu, Shunwu|Li, Zhugang|Cao, Youfang|Miao, Zhiqi|Qian, Hongmei|Tang, Kexuan', 'Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.|Plant Biotechnology Research Center, Fudan-SJTU-Nottingham Plant Biotechnology R&D Center, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai 200030, Peoples Republic of China.', 'China|China|China|China|China|China|China|China', 0, 'Algorithms|Arabidopsis|Base Sequence|DNA, Plant|Gene Expression Profiling|Gene Expression Regulation, Plant|Genome, Plant|Microsatellite Repeats|Molecular Sequence Data|Open Reading Frames|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth043', '14764542', 'Simple sequence repeats or microsatellites have been found abundantly in many genomes. However, the significance of distribution preference has not been completely understood. Completion of the Arabidopsis genome sequencing allows us to better understand and characterize microsatellites.'),
(71064, 2004, 'bio', 'Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment', 'Arakaki, Adrian K|Zhang, Yang|Skolnick, Jeffrey', 'Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington Street, Buffalo, NY 14203-1199, USA.|Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington Street, Buffalo, NY 14203-1199, USA.|Center of Excellence in Bioinformatics, University at Buffalo, 901 Washington Street, Buffalo, NY 14203-1199, USA.', 'United States|United States|United States', 46, 'Algorithms|Amino Acid Sequence|Binding Sites|Computer Simulation|Databases, Protein|Enzymes|Escherichia coli Proteins|Models, Molecular|Molecular Sequence Data|Protein Binding|Protein Conformation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth044', '14764543', 'Several protein function prediction methods employ structural features captured in three-dimensional (3D) descriptors of biologically relevant sites. These methods are successful when applied to high-resolution structures, but their detection ability in lower resolution predicted structures has only been tested for a few cases.'),
(71065, 2004, 'bio', 'SPI: a tool for incorporating gene expression data into a four-dimensional database of Caenorhabditis elegans embryogenesis', 'Minakuchi, Yohei|Ito, Masahiro|Kohara, Yuji', 'Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka 411-8540, Japan.|Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka 411-8540, Japan.|Genome Biology Laboratory, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka 411-8540, Japan.', 'Japan|Japan|Japan', 0, 'Animals|Caenorhabditis elegans|Caenorhabditis elegans Proteins|Database Management Systems|Databases, Factual|Embryonic and Fetal Development|Gene Expression Profiling|Image Interpretation, Computer-Assisted|Information Storage and Retrieval|Microscopy, Confocal|Models, Biological|Reproducibility of Results|Sensitivity and Specificity|Software|Subcellular Fractions|Tissue Distribution|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth045', '14764544', 'A comprehensive gene expression database is essential for computer modeling and simulation of biological phenomena, including development. Development is a four-dimensional (4D, 3D structure and time course) phenomenon. We are constructing a 4D database of gene expression for the early embryogenesis of the nematode Caenorhabditis elegans. As a framework of the 4D database, we have constructed computer graphics (CG), into which we will incorporate the expression data of a number of genes at the subcellular level. However, the assignment of 3D distribution of gene products (protein, mRNA), of embryos at various developmental stages, is both difficult and tedious. We need to automate this process. For this purpose, we developed a new system, named SPI after superimposing fluorescent confocal microscopic data onto a CG framework.'),
(71066, 2004, 'bio', 'Exploring genome architecture through GOV: a WWW-based gene order visualizer', 'Sakharkar, Kishore R|Chow, Vincent T K', 'BioInformatics Institute, Biopolis street, Singapore 138671. kishore@bii.a-star.edu.sg|BioInformatics Institute, Biopolis street, Singapore 138671. kishore@bii.a-star.edu.sg', 'Singapore|Singapore', 4, 'Algorithms|Computer Graphics|Database Management Systems|Gene Expression Profiling|Internet|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth046', '14764545', 'The past decade has seen extension in the methods of sequence analysis from single gene based to analyzing multiple genes and proteins simultaneously. Consequently, there is a need for software tools that will allow mining of these enormous datasets at genome level effectively. A key challenge is to make them user-friendly, available to a larger community and integrate with public domain software without much hassle.'),
(71067, 2004, 'bio', 'Confirmation of data mining based predictions of protein function', 'King, Ross D|Wise, Paul H|Clare, Amanda', 'Department of Computer Science, University of Wales, Aberystwyth, Wales SY23 3DB, UK. rdk@aber.ac.uk|Department of Computer Science, University of Wales, Aberystwyth, Wales SY23 3DB, UK. rdk@aber.ac.uk|Department of Computer Science, University of Wales, Aberystwyth, Wales SY23 3DB, UK. rdk@aber.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Abstracting and Indexing as Topic|Algorithms|Databases, Protein|Escherichia coli Proteins|Gene Expression Profiling|Information Storage and Retrieval|Open Reading Frames|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth047', '14764546', 'A central problem in bioinformatics is the assignment of function to sequenced open reading frames (ORFs). The most common approach is based on inferred homology using a statistically based sequence similarity (SIM) method, e.g. PSI-BLAST. Alternative non-SIM based bioinformatic methods are becoming popular. One such method is Data Mining Prediction (DMP). This is based on combining evidence from amino-acid attributes, predicted structure and phylogenic patterns, and uses a combination of Inductive Logic Programming data mining, and decision trees to produce prediction rules for functional class. DMP predictions are more general than is possible using homology. In 2000/1, DMP was used to make public predictions of the function of 1309 Escherichia coli ORFs. Since then biological knowledge has advanced allowing us to test our predictions.'),
(71068, 2004, 'bio', 'PDBSprotEC: a Web-accessible database linking PDB chains to EC numbers via SwissProt', 'Martin, Andrew C R', 'School of Animal and Microbial Science, The University of Reading, Whiteknights, PO Box 228, Reading RG6 6AJ, UK. andrew@bioinf.org.uk', 'United Kingdom', 0, 'Database Management Systems|Databases, Protein|Documentation|Enzymes|Information Storage and Retrieval|Internet|Proteins|Terminology as Topic|United Kingdom', 'Journal Article', '10.1093/bioinformatics/bth048', '14764547', 'A mapping between chains in the Protein Databank and Enzyme Classification numbers is invaluable for research into structure-function relationships. Mapping at the chain level is a non-trivial problem and we present an automatically updated Web-server, which provides this link in a queryable form and as a downloadable XML or flat file.'),
(71069, 2004, 'bio', 'Predicting rules on organization of cis-regulatory elements, taking the order of elements into account', 'Terai, Goro|Takagi, Toshihisa', 'INTEC Web and Genome Informatics Corp., 1-3-3 Shinsuna, Koto-ku, Tokyo 136-8637, Japan.|INTEC Web and Genome Informatics Corp., 1-3-3 Shinsuna, Koto-ku, Tokyo 136-8637, Japan.', 'Japan|Japan', 14, 'Algorithms|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Regulator|Reproducibility of Results|Saccharomyces cerevisiae|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth049', '14764548', 'In eukaryotes, rules regarding organization of cis-regulatory elements are complex. They sometimes govern multiple kinds of elements and positional restrictions on elements.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71070, 2004, 'bio', 'CompuCell, a multi-model framework for simulation of morphogenesis', 'Izaguirre, J A|Chaturvedi, R|Huang, C|Cickovski, T|Coffland, J|Thomas, G|Forgacs, G|Alber, M|Hentschel, G|Newman, S A|Glazier, J A', 'Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu|Department of Computer Science and Engineering, University of Notre Dame, Notre Dame, IN 46556, USA. compucell@cse.nd.edu', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Animals|Bone and Bones|Cell Communication|Cell Division|Cell Movement|Cell Physiological Phenomena|Chick Embryo|Chickens|Computer Simulation|Forelimb|Gene Expression Regulation|Models, Biological|Morphogenesis|Software|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bth050', '14764549', 'CompuCell is a multi-model software framework for simulation of the development of multicellular organisms known as morphogenesis. It models the interaction of the gene regulatory network with generic cellular mechanisms, such as cell adhesion, division, haptotaxis and chemotaxis. A combination of a state automaton with stochastic local rules and a set of differential equations, including subcellular ordinary differential equations and extracellular reaction-diffusion partial differential equations, model gene regulation. This automaton in turn controls the differentiation of the cells, and cell-cell and cell-extracellular matrix interactions that give rise to cell rearrangements and pattern formation, e.g. mesenchymal condensation. The cellular Potts model, a stochastic model that accurately reproduces cell movement and rearrangement, models cell dynamics. All these models couple in a controllable way, resulting in a powerful and flexible computational environment for morphogenesis, which allows for simultaneous incorporation of growth and spatial patterning.'),
(71071, 2004, 'bio', 'AmpliBASE MT: a Mycobacterium tuberculosis diversity knowledgebase', 'Majeed, Ahmed A|Ahmed, Niyaz|Rao, K Rajender|Ghousunnissa, S|Kauser, Farhana|Bose, Buddhaditta|Nagarajaram, H A|Katoch, V M|Cousins, Debby V|Sechi, Leonardo A|Gilman, Robert H|Hasnain, Seyed E', 'Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.|Centre for DNA Fingerprinting and Diagnostics, Nacharam, Hyderabad 500076, India.', 'India|India|India|India|India|India|India|India|India|India|India|India', 15, 'DNA Fingerprinting|Database Management Systems|Databases, Nucleic Acid|Gene Expression Profiling|Genetic Variation|Information Storage and Retrieval|Internet|Mycobacterium tuberculosis|Phenotype|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth051', '14764550', 'AmpliBASE MT is an online databank of high-resolution DNA fingerprints representing fluorescent amplified fragment length polymorphism (FAFLP) profiles or amplitypes developed for the Mycobacterium tuberculosis complex strains from 48 different countries. AmpliBASE MT is based on a relational database management system that is hyperlinked to visualize genotyping results in the form of DNA fingerprint images for individual strains. A flexible search system based on systematic comparisons of fragment sizes in base pairs allows inter-laboratory comparison of FAFLP profiles. Besides this, the database also displays previously published data on IS6110 profiles, spoligotypes, MIRU-VNTRs and large sequence polymorphisms along with the FAFLP records that will give the overall comparisons. Being the first of its kind, AmpliBASE MT is expected to be a very helpful tool in strengthening the concept of geographic genomics and will be very helpful to molecular epidemiologists and those interested in diagnostic development for tuberculosis.'),
(71072, 2004, 'bio', 'ChromoViz: multimodal visualization of gene expression data onto chromosomes using scalable vector graphics', 'Kim, Jihoon|Chung, Hee-Joon|Park, Chan Hee|Park, Woong-Yang|Kim, Ju Han', 'Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.|Seoul National University Biomedical Informatics (SNUBI), Seoul National University College of Medicine, Seoul 110-799, Republic of Korea.', '-|-|-|-|-', 0, 'Chromosome Mapping|Computer Graphics|Database Management Systems|Gene Expression Profiling|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth052', '14764551', 'ChromoViz is an R package for the visualization of microarray gene expression data, cross-species and cross-platform comparisons, as well as non-expression genomic data obtained from public databases onto chromosomes. Chromosomal visualization format is proposed for the clear decoupling of the data layer from the procedure layer and the combined visualization of genomic data from heterogeneous data sources. Visualization with Javascript-enabled scalable vector graphics enables interactive visualization and navigation of data objects on the Web.'),
(71073, 2004, 'bio', 'Large-scale co-evolution analysis of protein structural interlogues using the global protein structural interactome map (PSIMAP)', 'Kim, Wan K|Bolser, Dan M|Park, Jong H', 'MRC Rosalind Franklin Centre for Genome Research, Hinxton, Cambridge CB10 1SB, UK.|MRC Rosalind Franklin Centre for Genome Research, Hinxton, Cambridge CB10 1SB, UK.|MRC Rosalind Franklin Centre for Genome Research, Hinxton, Cambridge CB10 1SB, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Amino Acid Sequence|Binding Sites|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Molecular Sequence Data|Phylogeny|Protein Binding|Protein Conformation|Protein Interaction Mapping|Protein Structure, Tertiary|Proteins|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth053', '14764552', 'Interacting pairs of proteins should co-evolve to maintain functional and structural complementarity. Consequently, such a pair of protein families shows similarity between their phylogenetic trees. Although the tendency of co-evolution has been known for various ligand-receptor pairs, it has not been studied systematically in the widest possible scope. We investigated the degree of co-evolution for more than 900 family pairs in a global protein structural interactome map (PSIMAP--a map of all the structural domain-domain interactions in the PDB).'),
(71074, 2004, 'bio', 'Predicting subcellular localization of proteins in a hybridization space', 'Cai, Yu-Dong|Chou, Kuo-Chen', 'Biomolecular Sciences Department, UMIST, PO Box 88, Manchester M60 1QD, UK.|Biomolecular Sciences Department, UMIST, PO Box 88, Manchester M60 1QD, UK.', 'United Kingdom|United Kingdom', 81, 'Algorithms|Gene Expression Profiling|Phylogeny|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|Subcellular Fractions|Tissue Distribution', 'Comparative Study', '10.1093/bioinformatics/bth054', '14764553', 'The localization of a protein in a cell is closely correlated with its biological function. With the number of sequences entering into databanks rapidly increasing, the importance of developing a powerful high-throughput tool to determine protein subcellular location has become self-evident. In view of this, the Nearest Neighbour Algorithm was developed for predicting the protein subcellular location using the strategy of hybridizing the information derived from the recent development in gene ontology with that from the functional domain composition as well as the pseudo amino acid composition.'),
(71075, 2004, 'bio', 'Multiple sequence alignment in parallel on a workstation cluster', 'Ebedes, Justin|Datta, Amitava', 'School of Computer Science and Software Engineering, University of Western Australia, Perth, WA 6009, Australia.|School of Computer Science and Software Engineering, University of Western Australia, Perth, WA 6009, Australia.', 'Australia|Australia', 0, 'Algorithms|Computing Methodologies|Gene Expression Profiling|Local Area Networks|Microcomputers|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis', 'Comparative Study', '10.1093/bioinformatics/bth055', '14764554', 'Multiple sequence alignment is the NP-hard problem of aligning three or more DNA or amino acid sequences in an optimal way so as to match as many characters as possible from the set of sequences. The popular sequence alignment program ClustalW uses the classical method of approximating a sequence alignment, by first computing a distance matrix and then constructing a guide tree to show the evolutionary relationship of the sequences. We show that parallelizing the ClustalW algorithm can result in significant speedup. We used a cluster of workstations using C and message passing interface for our implementation. Experimental results show that speedup of over 5.5 on six processors is obtainable for most inputs.'),
(71076, 2004, 'bio', 'CLENCH: a program for calculating Cluster ENriCHment using the Gene Ontology', 'Shah, N H|Fedoroff, N V', 'The Huck Institute of Life Sciences, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu|The Huck Institute of Life Sciences, Pennsylvania State University, University Park, PA 16802, USA. nigam@psu.edu', 'United States|United States', 0, 'Abstracting and Indexing as Topic|Algorithms|Arabidopsis|Cluster Analysis|Gene Expression Profiling|Phylogeny|Sequence Alignment|Software', 'Journal Article', '10.1093/bioinformatics/bth056', '14764555', 'Analysis of microarray data most often produces lists of genes with similar expression patterns, which are then subdivided into functional categories for biological interpretation. Such functional categorization is most commonly accomplished using Gene Ontology (GO) categories. Although there are several programs that identify and analyze functional categories for human, mouse and yeast genes, none of them accept Arabidopsis thaliana data. In order to address this need for A.thaliana community, we have developed a program that retrieves GO annotations for A.thaliana genes and performs functional category analysis for lists of genes selected by the user.'),
(71077, 2004, 'bio', 'Cluster Analyzer for Transcription Sites (CATS): a C++-based program for identifying clustered transcription factor binding sites', 'Yu, Han|Yoo, Andrew S|Greenwald, Iva', 'Wave Systems Corp., 19925 Stevens Creek Blvd, Cupertino, CA 95014, USA.|Wave Systems Corp., 19925 Stevens Creek Blvd, Cupertino, CA 95014, USA.|Wave Systems Corp., 19925 Stevens Creek Blvd, Cupertino, CA 95014, USA.', 'United States|United States|United States', 0, 'Binding Sites|Cluster Analysis|Gene Expression Profiling|Programming Languages|Protein Binding|Sequence Alignment|Sequence Analysis|Software|Transcription Factors|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth057', '14764556', 'We have developed a program, Cluster Analyzer for Transcription Sites (CATS), which identifies clusters of transcription factor binding sites in any genome sequence. The program searches for clusters of the consensus sequence for DNA binding within a window (length of DNA). The window size and the cluster size (number of consensus sequences within a given window) can be varied. CATS can be used for single or multiple transcription factors for which consensus sequences have been deduced based on biochemical and mutational analysis, or by comparative genomics. The use of CATS for clusters of different transcription factor binding sites may facilitate the identification of genes that are co-regulated in a cell type-specific or developmental stage-specific manner. CATS is simple to install and use on computers running any Windows NT-platforms.'),
(71078, 2004, 'bio', 'Gene structure prediction from consensus spliced alignment of multiple ESTs matching the same genomic locus', 'Brendel, Volker|Xing, Liqun|Zhu, Wei', 'Department of Genetics, Development and Cell Biology, Iowa State University, 2112 Molecular Biology Building, Ames, IA 50011-3260, USA. vbrendel@iastate.edu|Department of Genetics, Development and Cell Biology, Iowa State University, 2112 Molecular Biology Building, Ames, IA 50011-3260, USA. vbrendel@iastate.edu|Department of Genetics, Development and Cell Biology, Iowa State University, 2112 Molecular Biology Building, Ames, IA 50011-3260, USA. vbrendel@iastate.edu', 'United States|United States|United States', 75, 'Algorithms|Chromosome Mapping|Consensus Sequence|DNA, Recombinant|Expressed Sequence Tags|Gene Expression Profiling|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth058', '14764557', 'Accurate gene structure annotation is a challenging computational problem in genomics. The best results are achieved with spliced alignment of full-length cDNAs or multiple expressed sequence tags (ESTs) with sufficient overlap to cover the entire gene. For most species, cDNA and EST collections are far from comprehensive. We sought to overcome this bottleneck by exploring the possibility of using combined EST resources from fairly diverged species that still share a common gene space. Previous spliced alignment tools were found inadequate for this task because they rely on very high sequence similarity between the ESTs and the genomic DNA.'),
(71079, 2004, 'bio', 'An evaluation of new criteria for CpG islands in the human genome as gene markers', 'Wang, Yong|Leung, Frederick C C', 'Department of Zoology, University of Hong Kong, Pokfulam, Hong Kong, HK SAR, China.|Department of Zoology, University of Hong Kong, Pokfulam, Hong Kong, HK SAR, China.', 'China|China', 0, 'Algorithms|Base Sequence|CpG Islands|Gene Expression Profiling|Genetic Markers|Genome, Human|Humans|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth059', '14764558', 'Recently, more stringent criteria for CpG islands have been introduced to exclude Alu repeats, thereby enabling a higher proportion of CpG islands associating with genes to be identified. Using these new criteria, several types of associations between CpG islands and genes were investigated to further establish the importance of CpG islands as gene markers.'),
(71080, 2004, 'bio', 'A rapid method for illustrating features in both coding and non-coding regions of a genome', 'Hall, R|Stern, L', 'Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia. rshall@cs.mu.oz.au|Department of Computer Science and Software Engineering, The University of Melbourne, Victoria 3010, Australia. rshall@cs.mu.oz.au', 'Australia|Australia', 3, 'Algorithms|Animals|Chromosome Mapping|Computer Graphics|Fourier Analysis|Gene Expression Profiling|Genome|Open Reading Frames|Plasmodium falciparum|Sequence Analysis, DNA|Signal Processing, Computer-Assisted|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth042', '14764559', 'A bitmap display of the Fourier spectra has been developed which allows convenient whole chromosome scanning for genes and other features. Use of a limited sliding window gives rapid visualization and localization of coding regions in the chromosomes, as well as non-coding features such as repetitive DNA. The method works particularly well on organisms with a skewed base composition, to provide an overview of genomic features.'),
(71081, 2004, 'bio', 'Metrics for comparing regulatory sequences on the basis of pattern counts', 'van Helden, Jacques', 'SCMBB, Université Libre de Bruxelles, Campus Plaine CP 263, Boulevard du Triomphe, B-1050 Bruxelles, Belgium. jvanheld@ucmb.ulb.ac.be', 'Belgium', 22, 'Algorithms|Base Sequence|Computer Simulation|DNA|Gene Expression Profiling|Gene Frequency|Models, Genetic|Models, Statistical|Molecular Sequence Data|Pattern Recognition, Automated|Regulatory Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg425', '14764560', 'Upstream sequences contain short motifs, which mediate transcriptional regulation by specifically binding different transcription factors. The presence of common motifs in the regulatory regions of two genes might be considered as a clue for a potential co-regulation. A pattern count-based (dis)similarity metric between sequences could thus be used to classify genes according to their putative regulatory properties.'),
(71082, 2004, 'bio', 'Rapid and sensitive dot-matrix methods for genome analysis', 'Huang, Yue|Zhang, Ling', 'Lynnon Corporation, 116 rue du Milicien, Vaudreuil-Dorion, Quebec, Canada, J7V 9M4. yhuang@lynnon.com|Lynnon Corporation, 116 rue du Milicien, Vaudreuil-Dorion, Quebec, Canada, J7V 9M4. yhuang@lynnon.com', 'Canada|Canada', 12, 'Algorithms|Animals|Base Sequence|Chromosomes, Human, Pair 11|Computer Graphics|Gene Expression Profiling|Genome|Humans|Mice|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|Thermoplasma|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg429', '14764561', 'Dot-matrix plots are widely used for similarity analysis of biological sequences. Many algorithms and computer software tools have been developed for this purpose. Though some of these tools have been reported to handle sequences of a few 100 kb, analysis of genome sequences with a length of >10 Mb on a microcomputer is still impractical due to long execution time and computer memory requirement.'),
(71083, 2004, 'bio', 'CHOISS for selection of single nucleotide polymorphism markers on interval regularity', 'Lee, Soohyun|Kang, Changwon', 'Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.|Department of Biological Sciences, Korea Advanced Institute of Science and Technology, 373-1 Guseong-dong, Yuseong-gu, Daejeon 305-701, Korea.', '-|-', 1, 'Algorithms|Gene Expression Profiling|Genetic Markers|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg458', '14764562', 'We developed algorithms that find a set of single nucleotide polymorphism (SNP) markers based on interval regularity, given either the number of SNPs to choose (m) or the desired interval (I), subject to minimum variance or minimum sum of squared deviations from I. In both cases, the number of all possible sets increases exponentially with respect to the number of input SNPs (n), but our algorithms find the minima only with O(n(2)) calculations and comparisons by elimination of redundancy.'),
(71084, 2004, 'bio', 'Comparison of various algorithms for recognizing short coding sequences of human genes', 'Gao, Feng|Zhang, Chun-Ting', 'Department of Physics, Tianjin University, Tianjin 300072, China.|Department of Physics, Tianjin University, Tianjin 300072, China.', 'China|China', 0, 'Algorithms|Base Sequence|Gene Expression Profiling|Genome, Human|Humans|Molecular Sequence Data|Open Reading Frames|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg467', '14764563', 'Since the early 1980s of the twentieth century, there has been great progress in the development of computational gene-finding algorithms. Some problems, however, have not yet been solved currently. Recognizing short genes in prokaryotes and short exons in eukaryotes is one of such problems. The paper is devoted to assessing various algorithms, including those currently available and the new ones proposed here, in order to find the best algorithm to solve the issue.'),
(71085, 2004, 'bio', 'Adplot: detection and visualization of repetitive patterns in complete genomes', 'Taneda, Akito', 'Department of Electronic and Information System Engineering, Faculty of Science and Technology, Hirosaki University, Hirosaki 036-8561, Japan. taneda@si.hirosaki-u.ac.jp', 'Japan', 15, 'Algorithms|Chromosome Mapping|Chromosomes, Fungal|Chromosomes, Human|Computer Graphics|Gene Expression Profiling|Genes, T-Cell Receptor beta|Genome|Humans|Repetitive Sequences, Nucleic Acid|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg470', '14764564', 'Repetitive DNA sequences are abundant in genomes and efficient mining of significant repeats is important as the first step of repetitive sequence research. Although many computational tools for the purpose, either automatic or visualization ones, have been developed, detection and analysis of approximate repeats are still non-trivial task.'),
(71086, 2004, 'bio', 'FORTE: a profile-profile comparison tool for protein fold recognition', 'Tomii, Kentaro|Akiyama, Yutaka', 'Computational Biology Research Center, The National Institute of Advanced Industrial Science and Technology, Aomi Frontier Building 2-43 Aomi, 17F, Koto-ku, Tokyo 135-0064, Japan. tomii@cbrc.jp|Computational Biology Research Center, The National Institute of Advanced Industrial Science and Technology, Aomi Frontier Building 2-43 Aomi, 17F, Koto-ku, Tokyo 135-0064, Japan. tomii@cbrc.jp', 'Japan|Japan', 64, 'Algorithms|Amino Acid Sequence|Databases, Protein|Information Storage and Retrieval|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg474', '14764565', 'We present FORTE, a profile-profile comparison tool for protein fold recognition. Users can submit a protein sequence to explore the possibilities of structural similarity existing in known structures. Results are reported via email in the form of pairwise alignments.'),
(71087, 2004, 'bio', 'Plotting haplotype-specific linkage disequilibrium patterns by extended haplotype homozygosity', 'Mueller, Jakob C|Andreoli, Christophe', 'Institute of Human Genetics, GSF, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany. jakob.mueller@gsf.de|Institute of Human Genetics, GSF, Ingolstaedter Landstrasse 1, 85764 Neuherberg, Germany. jakob.mueller@gsf.de', 'Germany|Germany', 17, 'Algorithms|Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Haplotypes|Homozygote|Internet|Linkage Disequilibrium|Pattern Recognition, Automated|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg481', '14764566', 'Association studies may request more details of a specific haplotype. Haplotype-specific decay of linkage disequilibrium is such a crucial and versatile characteristic. It may be used, e.g. to search for signals of natural selection in a risk haplotype. Here, we present a web-based tool to explore the relationship between population frequency and extended linkage disequilibrium measured as haplotype homozygosity of observed haplotypes within a specified candidate region.'),
(71088, 2004, 'bio', 'Fold-specific substitution matrices for protein classification', 'Vilim, R B|Cunningham, R M|Lu, B|Kheradpour, P|Stevens, F J', 'Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA. rvilim@anl.gov|Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA. rvilim@anl.gov|Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA. rvilim@anl.gov|Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA. rvilim@anl.gov|Argonne National Laboratory, 9700 S. Cass Avenue, Argonne, IL 60439, USA. rvilim@anl.gov', 'United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Immunoglobulin Light Chains|Immunoglobulin Variable Region|Molecular Sequence Data|Protein Folding|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg492', '14764567', 'Methods that focus on secondary structures, such as Position Specific Scoring Matrices and Hidden Markov Models, have proved useful for assigning proteins to families. However, for assigning proteins to an attribute class within a family these methods may introduce more free parameters than are needed. There are fewer members and there is less variability among sequences within a family. We describe a method for organizing proteins in a family that exhibits up to an order of magnitude reduction in the number of parameters. The basis is the log odds ratio commonly used to measure similarity. We adapt this to characterize the sequence dissimilarities that give rise to attribute differentiation. This leads to the definition of Class Attribute Substitution Matrices (CLASSUM), a dual of the BLOSUM.'),
(71089, 2004, 'bio', 'Sequence analysis and membrane partitioning energies of alpha-helical antimicrobial peptides', 'Han, Xing|Kang, Wenjun', 'DuPont Haskell Laboratory for Health and Environmental Sciences, PO Box 50, Newark, DE 19714, USA. xing.han@usa.dupont.com|DuPont Haskell Laboratory for Health and Environmental Sciences, PO Box 50, Newark, DE 19714, USA. xing.han@usa.dupont.com', 'United States|United States', 7, 'Algorithms|Amino Acids|Antimicrobial Cationic Peptides|Cell Membrane|Protein Conformation|Protein Structure, Secondary|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth027', '14764568', 'Sequences of 221 alpha-helical antimicrobial peptides (alphaAMPs) were compared and 63-166 of them were selected and analyzed using Perl programs. The results showed that aliphatic amino acids Gly, Leu, Ala, Ile and two positively charged amino acids Lys and Arg were composed of more than 63% of the first 20 residues of alphaAMPs. The weighed mean membrane partitioning energies at positions from 1 to 25 of alphaAMPs were calculated. Profile of the partitioning energies suggests oblique membrane insertion and an amphipathic alpha-helical structure of the N-terminus of alphaAMP (residues from 1 to 13), a bend structure at positions 13 and 14, and a less structured C-terminus that parallels the surface of the membrane. These structural features are in good agreement with the experimentally determined membrane structure of hemagglutinin fusion peptide from influenza virus. We hypothesize that this (N-terminal oblique alpha-helix)-central bend-(C-terminus) could be a common structural motif of membrane-disruptive peptides.'),
(71090, 2004, 'bio', 'SQUARE--determining reliable regions in sequence alignments', 'Tress, Michael L|Graña, Osvaldo|Valencia, Alfonso', 'CNB-CSIC, Calle Darwin, Cantoblanco, 28049 Madrid, Spain. mtress@gredos.cnb.uam.es|CNB-CSIC, Calle Darwin, Cantoblanco, 28049 Madrid, Spain. mtress@gredos.cnb.uam.es|CNB-CSIC, Calle Darwin, Cantoblanco, 28049 Madrid, Spain. mtress@gredos.cnb.uam.es', 'Spain|Spain|Spain', 17, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Internet|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bth032', '14764569', 'The Server for Quick Alignment Reliability Evaluation (SQUARE) is a Web-based version of the method we developed to predict regions of reliably aligned residues in sequence alignments. Given an alignment between a query sequence and a sequence of known structure, SQUARE is able to predict which residues are reliably aligned. The server accesses a database of profiles of sequences of known three-dimensional structures in order to calculate the scores for each residue in the alignment. SQUARE produces a graphical output of the residue profile-derived alignment scores along with an indication of the reliability of the alignment. In addition, the scores can be compared against template secondary structure, conserved residues and important sites.'),
(71091, 2004, 'bio', 'GelScape: a web-based server for interactively annotating, manipulating, comparing and archiving 1D and 2D gel images', 'Young, Nelson|Chang, Zhan|Wishart, David S', 'Department of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8 Canada.|Department of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8 Canada.|Department of Computing Science and Biological Sciences, University of Alberta, Edmonton, AB, T6G 2E8 Canada.', 'Canada|Canada|Canada', 0, 'Computer Graphics|Database Management Systems|Databases, Factual|Documentation|Electrophoresis, Gel, Two-Dimensional|Electrophoresis, Polyacrylamide Gel|Information Storage and Retrieval|Internet|Online Systems|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth033', '14764570', 'GelScape is a web-based tool that permits facile, interactive annotation, comparison, manipulation and storage of protein gel images. It uses Java applet-servlet technology to allow rapid, remote image handling and image processing in a platform-independent manner. It supports many of the features found in commercial, stand-alone gel analysis software including spot annotation, spot integration, gel warping, image resizing, HTML image mapping, image overlaying as well as the storage of gel image and gel annotation data in compliance with Federated Gel Database requirements.'),
(71092, 2004, 'bio', 'Discrepancies in dbSNP confirmation rates and allele frequency distributions from varying genotyping error rates and patterns', 'Mitchell, Adele A|Zwick, Michael E|Chakravarti, Aravinda|Cutler, David J', 'McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Jefferson Street Building, 2-120, Baltimore, MD 21287, USA.|McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Jefferson Street Building, 2-120, Baltimore, MD 21287, USA.|McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Jefferson Street Building, 2-120, Baltimore, MD 21287, USA.|McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, 600 N. Wolfe Street, Jefferson Street Building, 2-120, Baltimore, MD 21287, USA.', 'United States|United States|United States|United States', 33, 'Algorithms|Databases, Nucleic Acid|Gene Expression Profiling|Gene Frequency|Genotype|Models, Genetic|Models, Statistical|Polymorphism, Single Nucleotide|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth034', '14764571', 'Three recent publications have examined the quality and completeness of public database single nucleotide polymorphism (dbSNP) and have come to dramatically different conclusions regarding dbSNPs false positive rate and the proportion of dbSNPs that are expected to be common. These studies employed different genotyping technologies and different protocols in determining minimum acceptable genotyping quality thresholds. Because heterozygous sites typically have lower quality scores than homozygous sites, a higher minimum quality threshold reduces the number of false positive SNPs, but yields fewer heterozygotes and leads to fewer confirmed SNPs. To account for the different confirmation rates and distributions of minor allele frequencies, we propose that the three confirmation studies have different false positive and false negative rates. We developed a mathematical model to predict SNP confirmation rates and the apparent distribution of minor allele frequencies under user-specified false positive and false negative rates. We applied this model to the three published studies and to our own resequencing effort. We conclude that the dbSNP false positive rate is approximately 15-17% and that the reported confirmation studies have vastly different genotyping error rates and patterns.'),
(71093, 2004, 'bio', 'Genes@Work: an efficient algorithm for pattern discovery and multivariate feature selection in gene expression data', 'Lepre, Jorge|Rice, J Jeremy|Tu, Yuhai|Stolovitzky, Gustavo', 'IBM T.J. Watson Research Center, P.O. Box 218, Yorktown Heights, NY 10598, USA.|IBM T.J. Watson Research Center, P.O. Box 218, Yorktown Heights, NY 10598, USA.|IBM T.J. Watson Research Center, P.O. Box 218, Yorktown Heights, NY 10598, USA.|IBM T.J. Watson Research Center, P.O. Box 218, Yorktown Heights, NY 10598, USA.', 'United States|United States|United States|United States', 34, 'Algorithms|Gene Expression Profiling|Humans|Lymphoma|Multivariate Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth035', '14764572', 'Despite the growing literature devoted to finding differentially expressed genes in assays probing different tissues types, little attention has been paid to the combinatorial nature of feature selection inherent to large, high-dimensional gene expression datasets. New flexible data analysis approaches capable of searching relevant subgroups of genes and experiments are needed to understand multivariate associations of gene expression patterns with observed phenotypes.'),
(71094, 2004, 'bio', 'Good spaced seeds for homology search', 'Choi, Kwok Pui|Zeng, Fanfan|Zhang, Louxin', 'Department of Mathematics, National University of Singapore, Singapore 117543. matzlx@nus.edu.sg|Department of Mathematics, National University of Singapore, Singapore 117543. matzlx@nus.edu.sg|Department of Mathematics, National University of Singapore, Singapore 117543. matzlx@nus.edu.sg', 'Singapore|Singapore|Singapore', 0, 'Algorithms|Animals|Chromosome Mapping|Escherichia coli|Gene Expression Profiling|Mice|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth037', '14764573', 'Filtration is an important technique used to speed up local alignment as exemplified in the BLAST programs. Recently, Ma et al. discovered that better filtering can be achieved by spacing out the matching positions according to a certain pattern, instead of contiguous positions to trigger a local alignment in their PatternHunter program. Such a match pattern is called a spaced seed.'),
(71095, 2004, 'bio', 'Sensitivity and specificity of five abundance estimators for high-density oligonucleotide microarrays', 'James, Andrew C|Veitch, Jim G|Zareh, Ali R|Triche, Timothy', 'Research School of Biological Sciences, Australian National University, PO Box 475, Canberra ACT 2601, Australia. andrew.james@anu.edu.au|Research School of Biological Sciences, Australian National University, PO Box 475, Canberra ACT 2601, Australia. andrew.james@anu.edu.au|Research School of Biological Sciences, Australian National University, PO Box 475, Canberra ACT 2601, Australia. andrew.james@anu.edu.au|Research School of Biological Sciences, Australian National University, PO Box 475, Canberra ACT 2601, Australia. andrew.james@anu.edu.au', 'Australia|Australia|Australia|Australia', 11, 'Algorithms|False Positive Reactions|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth038', '14764574', 'A number of algorithms have been proposed for the processing of feature-level data from high-density oligonucleotide microarrays to give estimates of transcript abundance. Performance in the common task of detecting differential expression between samples can be quantified by the statistical concepts of sensitivity and specificity, and represented by the use of receiver operating characteristic curves. These have been previously presented for small numbers of genes known to be differentially present in spiked-in samples. We present here a study of performance over a large number (thousands) of transcripts for which there is strong evidence of differential expression, with corresponding false positive rates controlled by comparisons between replicates.'),
(71096, 2004, 'bio', 'Statistically rigorous automated protein annotation', 'Krebs, Werner G|Bourne, Philip E', 'San Diego Supercomputer Center, San Diego, California, USA.|San Diego Supercomputer Center, San Diego, California, USA.', 'United States|United States', 9, 'Abstracting and Indexing as Topic|Algorithms|Cluster Analysis|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Genetic|Models, Statistical|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth039', '14764575', 'Assignment of putative protein functional annotation by comparative analysis using pre-defined experimental annotations is performed routinely by molecular biologists. The number and statistical significance of these assignments remains a challenge in this era of high-throughput proteomics. A combined statistical method that enables robust, automated protein annotation by reliably expanding existing annotation sets is described. An existing clustering scheme, based on relevant experimental information (e.g. sequence identity, keywords or gene expression data) is required. The method assigns new proteins to these clusters with a measure of reliability. It can also provide human reviewers with a reliability score for both new and previously classified proteins.'),
(71097, 2004, 'bio', 'Ontologizing gene-expression microarray data: characterizing clusters with Gene Ontology', 'Robinson, Peter N|Wollstein, Andreas|Böhme, Ulrike|Beattie, Brad', 'Institute of Medical Genetics, Charité University Hospital, Humboldt University, Augustenburger Platz 1, 13353 Berlin, Germany. peter.robinson@charite.de|Institute of Medical Genetics, Charité University Hospital, Humboldt University, Augustenburger Platz 1, 13353 Berlin, Germany. peter.robinson@charite.de|Institute of Medical Genetics, Charité University Hospital, Humboldt University, Augustenburger Platz 1, 13353 Berlin, Germany. peter.robinson@charite.de|Institute of Medical Genetics, Charité University Hospital, Humboldt University, Augustenburger Platz 1, 13353 Berlin, Germany. peter.robinson@charite.de', 'Germany|Germany|Germany|Germany', 28, 'Cluster Analysis|DNA|Gene Expression Profiling|Hypermedia|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Phylogeny|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bth040', '14764576', 'An XML-based Java application is described that provides a function-oriented overview of the results of cluster analysis of gene-expression microarray data based on Gene Ontology terms and associations. The application generates one HTML page with listings of the frequencies of explicit and implicit Gene Ontology annotations for each cluster, and separate, linked pages with listings of explicit annotations for each gene in a cluster.'),
(71098, 2004, 'bio', 'Recognition and analysis of protein-coding genes in severe acute respiratory syndrome associated coronavirus', 'Sharma, Ramakant|Maheshwari, Jitendra Kumar|Prakash, Tulika|Dash, Debasis|Brahmachari, Samir K', 'Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.|Institute of Genomics and Integrative Biology, CSIR, Mall Road, Delhi 110 007, India.', 'India|India|India|India|India', 5, 'Algorithms|Gene Expression Profiling|Genetic Testing|Reproducibility of Results|SARS Virus|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis|Sequence Analysis, DNA|Sequence Analysis, Protein|Software|Viral Proteins', 'Comparative Study', '10.1093/bioinformatics/bth041', '14764577', 'The recent outbreak of severe acute respiratory syndrome (SARS) caused by SARS coronavirus (SARS-CoV) has necessitated an in-depth molecular understanding of the virus to identify new drug targets. The availability of complete genome sequence of several strains of SARS virus provides the possibility of identification of protein-coding genes and defining their functions. Computational approach to identify protein-coding genes and their putative functions will help in designing experimental protocols.'),
(71099, 2004, 'bio', 'CNplot: visualizing pre-clustered networks', 'Batada, Nizar N', 'Program in Biophysics, Stanford University, Stanford, CA 94305, USA. nbatada@stanford.edu', 'United States', 10, 'Cluster Analysis|Computer Graphics|Gene Expression Regulation|Models, Biological|Programming Languages|Protein Interaction Mapping|Proteins|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth080', '14871859', 'CNplot is a simple technique for the visualization of global connectivity within pre-clustered network data. CNplot is easy to implement and in most cases produces informative and satisfactory summary of the data.'),
(71100, 2004, 'bio', 'Automated ordering of fingerprinted clones', 'Flibotte, Stephane|Chiu, Readman|Fjell, Chris|Krzywinski, Martin|Schein, Jacqueline E|Shin, Heesun|Marra, Marco A', 'Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca|Genome Sciences Centre, British Columbia Cancer Research Centre, Vancouver, BC Canada, V5Z 4E6. sflibotte@bcgsc.ca', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada', 0, 'Algorithms|Cloning, Molecular|Cluster Analysis|Contig Mapping|Cryptococcus neoformans|DNA Fingerprinting|Gene Expression Profiling|Genome, Bacterial|Genome, Human|Humans|Pattern Recognition, Automated|Reproducibility of Results|Robotics|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth079', '14871860', 'A considerable amount of human intervention is currently required to produce high-quality fingerprint-based physical maps for genomic studies.'),
(71101, 2004, 'bio', 'Open source clustering software', 'de Hoon, M J L|Imoto, S|Nolan, J|Miyano, S', 'Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan. mdehoon@ims.u-tokyo.ac.jp|Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639 Japan. mdehoon@ims.u-tokyo.ac.jp', 'Japan|Japan|Japan|Japan', 2012, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Pattern Recognition, Automated|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth078', '14871861', 'We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisens well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C.'),
(71102, 2004, 'bio', 'Correction of sequence-based artifacts in serial analysis of gene expression', 'Akmaev, Viatcheslav R|Wang, Clarence J', 'Genzyme Corporation, Framingham, MA 01701-9322, USA. slava.akmaev@genzyme.com|Genzyme Corporation, Framingham, MA 01701-9322, USA. slava.akmaev@genzyme.com', 'United States|United States', 35, 'Algorithms|Artifacts|Brain Neoplasms|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Genetic Variation|Glioma|Humans|Models, Genetic|Models, Statistical|Polymerase Chain Reaction|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth077', '14871862', 'Serial Analysis of Gene Expression (SAGE) is a powerful technology for measuring global gene expression, through rapid generation of large numbers of transcript tags. Beyond their intrinsic value in differential gene expression analysis, SAGE tag collections afford abundant information on the size and shape of the sample transcriptome and can accelerate novel gene discovery. These latter SAGE applications are facilitated by the enhanced method of Long SAGE. A characteristic of sequencing-based methods, such as SAGE and Long SAGE is the unavoidable occurrence of artifact sequences resulting from sequencing errors. By virtue of their low-random incidence, such tag errors have minimal impact on differential expression analysis. However, to fully exploit the value of large SAGE tag datasets, it is desirable to account for and correct tag artifacts.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71103, 2004, 'bio', 'WebVar: A resource for the rapid estimation of relative site variability from multiple sequence alignments', 'Mignone, Flavio|Horner, David S|Pesole, Graziano', 'Dipartimento di Scienze Biomolecolari e Biotecnologie, Università di Milano, 20113 Milano, Italy.|Dipartimento di Scienze Biomolecolari e Biotecnologie, Università di Milano, 20113 Milano, Italy.|Dipartimento di Scienze Biomolecolari e Biotecnologie, Università di Milano, 20113 Milano, Italy.', 'Italy|Italy|Italy', 0, 'Algorithms|Gene Expression Profiling|Internet|Sequence Alignment|Sequence Analysis|Sequence Homology|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth076', '14871863', 'WebVar is an online resource that provides estimates of relative site variability from multiple alignments of homologous protein or nucleic acid sequences. WebVar provides a variety of graphic and textual representations of estimates, designed to assist in phylogenetic analysis.'),
(71104, 2004, 'bio', 'Poorly conserved ORFs in the genome of the archaea Halobacterium sp NRC-1 correspond to expressed proteins', 'Shmuely, H|Dinitz, E|Dahan, I|Eichler, J|Fischer, D|Shaanan, B', 'Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.|Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.|Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.|Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.|Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.|Department of Life Sciences, Ben Gurion University of the Negev, Beersheva, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel', 15, 'Bacterial Proteins|Chromosome Mapping|Conserved Sequence|Gene Expression Profiling|Genome, Archaeal|Genome, Bacterial|Halobacterium|Open Reading Frames|Sequence Alignment|Sequence Analysis, DNA', 'Evaluation Studies', '10.1093/bioinformatics/bth075', '14871864', 'A large fraction of open reading frames (ORFs) identified as hypothetical proteins correspond to either conserved hypothetical proteins, representing sequences homologous to ORFs of unknown function from other organisms, or to hypothetical proteins lacking any significant sequence similarity to other ORFs in the databases. Elucidating the functions and three-dimensional structures of such orphan ORFs, termed ORFans or poorly conserved ORFs (PCOs), is essential for understanding biodiversity. However, it has been claimed that many ORFans may not encode for expressed proteins.'),
(71105, 2004, 'bio', 'Growing genetic regulatory networks from seed genes', 'Hashimoto, Ronaldo F|Kim, Seungchan|Shmulevich, Ilya|Zhang, Wei|Bittner, Michael L|Dougherty, Edward R', 'Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.|Department of Electrical Engineering, Texas A&M University, College Station, TX, USA 77843, USA.', 'United States|United States|United States|United States|United States|United States', 74, 'Algorithms|Animals|Computer Simulation|Evolution, Molecular|Gene Expression Profiling|Gene Expression Regulation|Genetic Variation|Glioma|Humans|Melanoma|Models, Genetic|Models, Statistical|Signal Transduction|Transcription, Genetic', 'Evaluation Studies', '10.1093/bioinformatics/bth074', '14871865', 'A number of models have been proposed for genetic regulatory networks. In principle, a network may contain any number of genes, so long as data are available to make inferences about their relationships. Nevertheless, there are two important reasons why the size of a constructed network should be limited. Computationally and mathematically, it is more feasible to model and simulate a network with a small number of genes. In addition, it is more likely that a small set of genes maintains a specific core regulatory mechanism.'),
(71106, 2004, 'bio', 'eF-site and PDBjViewer: database and viewer for protein functional sites', 'Kinoshita, Kengo|Nakamura, Haruki', 'Graduate School of Integrated Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Japan.|Graduate School of Integrated Science, Yokohama City University, 1-7-29 Suehiro-cho, Tsurumi-ku, Yokohama, 230-0045, Japan.', 'Japan|Japan', 88, 'Computer Graphics|Database Management Systems|Databases, Protein|Imaging, Three-Dimensional|Information Storage and Retrieval|Models, Molecular|Protein Conformation|Proteins|Software|Static Electricity|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth073', '14871866', 'The electrostatic-surface of functional site (eF-site) is a database for the molecular surfaces of protein functional sites. To enable browsing of each molecular surface along with the atomic model, we have developed a new three-dimensional interactive viewer, PDBjViewer, that can be used both as an applet and as a stand-alone program.'),
(71107, 2004, 'bio', 'CVD: the intestinal crypt/villus in situ hybridization database', 'Olsen, Line|Hansen, Morten|Ekstrøm, Claus T|Troelsen, Jesper T|Olsen, Jørgen', 'Department of Medical Biochemistry and Genetics, Biochemistry Laboratory C, Univesrity of Copenhagen, Denmark.|Department of Medical Biochemistry and Genetics, Biochemistry Laboratory C, Univesrity of Copenhagen, Denmark.|Department of Medical Biochemistry and Genetics, Biochemistry Laboratory C, Univesrity of Copenhagen, Denmark.|Department of Medical Biochemistry and Genetics, Biochemistry Laboratory C, Univesrity of Copenhagen, Denmark.|Department of Medical Biochemistry and Genetics, Biochemistry Laboratory C, Univesrity of Copenhagen, Denmark.', 'Denmark|Denmark|Denmark|Denmark|Denmark', 11, 'Animals|Database Management Systems|Databases, Bibliographic|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Humans|In Situ Hybridization|Information Storage and Retrieval|Intestinal Mucosa|Mammals|Microvilli|Natural Language Processing|Periodicals as Topic|PubMed|Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth072', '14871867', 'The intestinal crypt/villus in situ hybridization database (CVD) query interface is a web-based tool to search for genes with similar relative expression patterns along the crypt/villus axis of the mammalian intestine. The CVD is an online database holding information for relative gene expression patterns in the mammalian intestine and is based on the scoring of in situ hybridization experiments reported in the literature. CVD contains expression data for 88 different genes collected from 156 different in situ hybridization profiles. The web-based query interface allows execution of both single gene queries and pattern searches. The query results provide links to the most relevant public gene databases.'),
(71108, 2004, 'bio', '2LD, GENECOUNTING and HAP: Computer programs for linkage disequilibrium analysis', 'Zhao, Jing Hua', 'Department of Epidemiology and Public Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK. jzhao@hgmp.mrc.ac.uk', 'United Kingdom', 151, 'Alcoholism|Algorithms|Chromosome Mapping|Chromosomes, Human, X|Gene Frequency|Genetic Markers|Genetic Predisposition to Disease|Genetic Testing|Humans|Linkage Disequilibrium|Monoamine Oxidase|Parkinson Disease|Polymorphism, Single Nucleotide|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth071', '14871868', 'Computer programs are introduced which calculate pair-wise linkage disequilibrium statistics and conduct haplotype frequency estimation, including X chromosome data, and using a heuristic algorithm to handle multiple genetic markers and missing data.'),
(71109, 2004, 'bio', 'ConSeq: the identification of functionally and structurally important residues in protein sequences', 'Berezin, Carine|Glaser, Fabian|Rosenberg, Josef|Paz, Inbal|Pupko, Tal|Fariselli, Piero|Casadio, Rita|Ben-Tal, Nir', 'Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.|Department of Biochemistry, Georbe S. Wise Faculty of Life Sciences, Tel Aviv University, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 296, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Amino Acids|Molecular Sequence Data|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth070', '14871869', 'ConSeq is a web server for the identification of biologically important residues in protein sequences. Functionally important residues that take part, e.g. in ligand binding and protein-protein interactions, are often evolutionarily conserved and are most likely to be solvent-accessible, whereas conserved residues within the protein core most probably have an important structural role in maintaining the proteins fold. Thus, estimated evolutionary rates, as well as relative solvent accessibility predictions, are assigned to each amino acid in the sequence, both are subsequently used to indicate residues that have potential structural or functional importance.'),
(71110, 2004, 'bio', 'dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data', 'Lin, Ming|Wei, Lee-Jen|Sellers, William R|Lieberfarb, Marshall|Wong, Wing Hung|Li, Cheng', 'Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.|Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA.', 'United States|United States|United States|United States|United States|United States', 301, 'Algorithms|Chromosome Mapping|Cluster Analysis|Gene Expression Profiling|Genetic Carrier Screening|Genetic Testing|Genetic Variation|Humans|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth069', '14871870', 'Oligonucleotide microarrays allow genotyping of thousands of single-nucleotide polymorphisms (SNPs) in parallel. Recently, this technology has been applied to loss-of-heterozygosity (LOH) analysis of paired normal and tumor samples. However, methods and software for analyzing such data are not fully developed.'),
(71111, 2004, 'bio', 'Bayesian mixture model based clustering of replicated microarray data', 'Medvedovic, M|Yeung, K Y|Bumgarner, R E', 'Department of Environmental Health, Center for Genome Information, University of Cincinnati Medical Center, 3223 Eden Avenue ML 56, Cincinnati, OH 45267-0056, USA. Mario.Medvedovic@uc.edu|Department of Environmental Health, Center for Genome Information, University of Cincinnati Medical Center, 3223 Eden Avenue ML 56, Cincinnati, OH 45267-0056, USA. Mario.Medvedovic@uc.edu|Department of Environmental Health, Center for Genome Information, University of Cincinnati Medical Center, 3223 Eden Avenue ML 56, Cincinnati, OH 45267-0056, USA. Mario.Medvedovic@uc.edu', 'United States|United States|United States', 143, 'Algorithms|Bayes Theorem|Cluster Analysis|Computer Simulation|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth068', '14871871', 'Identifying patterns of co-expression in microarray data by cluster analysis has been a productive approach to uncovering molecular mechanisms underlying biological processes under investigation. Using experimental replicates can generally improve the precision of the cluster analysis by reducing the experimental variability of measurements. In such situations, Bayesian mixtures allow for an efficient use of information by precisely modeling between-replicates variability.'),
(71112, 2004, 'bio', 'Cellware--a multi-algorithmic software for computational systems biology', 'Dhar, Pawan|Meng, Tan Chee|Somani, Sandeep|Ye, Li|Sairam, Anand|Chitre, Mandar|Hao, Zhu|Sakharkar, Kishore', 'Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg|Systems Biology Group, Bioinformatics Institute, 30 Biopolis Street, No. #07-01 Matrix Building, Singapore 138671. pk@bii.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 42, 'Algorithms|Cell Physiological Phenomena|Computational Biology|Computer Simulation|Models, Biological|Software|Stochastic Processes|Systems Integration|Systems Theory|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth067', '14871872', 'The intracellular environment of a cell hosts a wide variety of enzymatic reactions, diffusion events, molecular binding, polymerization and metabolic channeling. To transform these biological events into a computational framework, distinct modeling strategies are required. While currently no tool is capable of capturing all these events, progress is being made to create an integrated environment for the modeling community. To address this niche requirement, Cellware has been developed to offer a multi-algorithmic environment for modeling and simulating both deterministic and stochastic events in the cell.'),
(71113, 2004, 'bio', 'Protein isoelectric point as a predictor for increased crystallization screening efficiency', 'Kantardjieff, Katherine A|Rupp, Bernhard', 'Department of Chemistry and Biochemistry, California State University Fullerton, Fullerton, CA 92834-6866, USA. kkantardjieff@fullerton.edu|Department of Chemistry and Biochemistry, California State University Fullerton, Fullerton, CA 92834-6866, USA. kkantardjieff@fullerton.edu', 'United States|United States', 86, 'Computer Simulation|Crystallization|Crystallography|Databases, Protein|Isoelectric Point|Models, Chemical|Models, Molecular|Models, Statistical|Protein Conformation|Proteins|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth066', '14871873', 'Increased efficiency in initial crystallization screening reduces cost and material requirements in structural genomics. Because pH is one of the few consistently reported parameters in the Protein Data Bank (PDB), the isoelectric point (pI) of a protein has been explored as a useful indirect predictor for the optimal choice of range and distribution of the pH sampling in crystallization trials.'),
(71114, 2004, 'bio', 'A metric model of amino acid substitution', 'Xu, Weijia|Miranker, Daniel P', 'Department of Computer Sciences, The Center for Computational Biology and Bioinformatics, University of Texas, Austin, TX 78712, USA. xwj@cs.utexas.edu|Department of Computer Sciences, The Center for Computational Biology and Bioinformatics, University of Texas, Austin, TX 78712, USA. xwj@cs.utexas.edu', 'United States|United States', 36, 'Algorithms|Amino Acid Sequence|Amino Acid Substitution|Computer Simulation|Evolution, Molecular|Models, Molecular|Molecular Sequence Data|Mutation|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth065', '14871874', 'We address the question of whether there exists an effective evolutionary model of amino-acid substitution that forms a metric-distance function. There is always a trade-off between speed and sensitivity among competing computational methods of determining sequence homology. A metric model of evolution is a prerequisite for the development of an entire class of fast sequence analysis algorithms that are both scalable, O(log n) and sensitive.'),
(71115, 2004, 'bio', 'NvAssign: protein NMR spectral assignment with NMRView', 'Kirby, Nigel I|DeRose, Eugene F|London, Robert E|Mueller, Geoffrey A', 'Laboratory of Structural Biology, MR-01, National Institute of Environmental Health Sciences, National Institutes of Health, Box 12233, Research Triangle Park, NC 27709, USA.|Laboratory of Structural Biology, MR-01, National Institute of Environmental Health Sciences, National Institutes of Health, Box 12233, Research Triangle Park, NC 27709, USA.|Laboratory of Structural Biology, MR-01, National Institute of Environmental Health Sciences, National Institutes of Health, Box 12233, Research Triangle Park, NC 27709, USA.|Laboratory of Structural Biology, MR-01, National Institute of Environmental Health Sciences, National Institutes of Health, Box 12233, Research Triangle Park, NC 27709, USA.', 'United States|United States|United States|United States', 12, 'Algorithms|Magnetic Resonance Spectroscopy|Proteins|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth064', '14871875', 'Nuclear magnetic resonance (NMR) protein studies rely on the accurate assignment of resonances. The general procedure is to (1) pick peaks, (2) cluster data from various experiments or spectra, (3) assign peaks to the sequence and (4) verify the assignments with the spectra. Many algorithms already exist for automating the assignment process (step 3). What is lacking is a flexible interface to help a spectroscopist easily move from clustering (step 2) to assignment algorithms (step 3) and back to verification of the algorithm output with spectral analysis (step 4).'),
(71116, 2004, 'bio', 'Probabilistic inference of molecular networks from noisy data sources', 'Iossifov, Ivan|Krauthammer, Michael|Friedman, Carol|Hatzivassiloglou, Vasileios|Bader, Joel S|White, Kevin P|Rzhetsky, Andrey', 'Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu|Department of Medical Informatics, Columbia University, New York, NY 10032, USA. iossifov@dbmi.columbia.edu', 'United States|United States|United States|United States|United States|United States|United States', 22, 'Algorithms|Cell Physiological Phenomena|Database Management Systems|Databases, Bibliographic|Databases, Protein|Information Storage and Retrieval|Models, Biological|Models, Statistical|Periodicals as Topic|Protein Interaction Mapping|Sequence Analysis, Protein|Signal Transduction|Stochastic Processes|Two-Hybrid System Techniques|Yeasts', 'Comparative Study', '10.1093/bioinformatics/bth061', '14871876', 'Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predicting protein interactions from heterogeneous data sources. The model describes stochastic generation of protein-protein interaction networks with real-world properties, as well as generation of two heterogeneous sources of protein-interaction information: research results automatically extracted from the literature and yeast two-hybrid experiments. Based on the domain composition of proteins, we use the model to predict protein interactions for pairs of proteins for which no experimental data are available. We further explore the prediction limits, given experimental data that cover only part of the underlying protein networks. This approach can be extended naturally to include other types of biological data sources.'),
(71117, 2004, 'bio', 'Recognizing names in biomedical texts: a machine learning approach', 'Zhou, GuoDong|Zhang, Jie|Su, Jian|Shen, Dan|Tan, ChewLim', 'Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhougd@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhougd@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhougd@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhougd@i2r.a-star.edu.sg|Institute for Infocomm Research, 21 Heng Mui Keng Terrace, Singapore 119613. zhougd@i2r.a-star.edu.sg', 'Singapore|Singapore|Singapore|Singapore|Singapore', 150, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval|Natural Language Processing|Periodicals as Topic|Reproducibility of Results|Sensitivity and Specificity|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/bth060', '14871877', 'With an overwhelming amount of textual information in molecular biology and biomedicine, there is a need for effective and efficient literature mining and knowledge discovery that can help biologists to gather and make use of the knowledge encoded in text documents. In order to make organized and structured information available, automatically recognizing biomedical entity names becomes critical and is important for information retrieval, information extraction and automated knowledge acquisition.'),
(71118, 2004, 'bio', 'Pseudo-periodic partitions of biological sequences', 'Li, Lugang|Jin, Renchao|Kok, Poh-Lin|Wan, Honghui', 'Department of Protective Medicine, Nanjing Army Medical College, The Second Army Medical University, Nanjing, Jiangsu 210099, China.|Department of Protective Medicine, Nanjing Army Medical College, The Second Army Medical University, Nanjing, Jiangsu 210099, China.|Department of Protective Medicine, Nanjing Army Medical College, The Second Army Medical University, Nanjing, Jiangsu 210099, China.|Department of Protective Medicine, Nanjing Army Medical College, The Second Army Medical University, Nanjing, Jiangsu 210099, China.', 'China|China|China|China', 10, 'Algorithms|Base Sequence|Conserved Sequence|Molecular Sequence Data|Pattern Recognition, Automated|Periodicity|Proteins|Repetitive Sequences, Amino Acid|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg404', '14960455', 'Algorithm development for finding typical patterns in sequences, especially multiple pseudo-repeats (pseudo-periodic regions), is at the core of many problems arising in biological sequence and structure analysis. In fact, one of the most significant features of biological sequences is their high quasi-repetitiveness. Variation in the quasi-repetitiveness of genomic and proteomic texts demonstrates the presence and density of different biologically important information. It is very important to develop sensitive automatic computational methods for the identification of pseudo-periodic regions of sequences through which we can infer, describe and understand biological properties, and seek precise molecular details of biological structures, dynamics, interactions and evolution.'),
(71119, 2004, 'bio', 'affy--analysis of Affymetrix GeneChip data at the probe level', 'Gautier, Laurent|Cope, Leslie|Bolstad, Benjamin M|Irizarry, Rafael A', 'Center for Biological Sequence Analysis (CBS), Technical University of Denmark, Building 208, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis (CBS), Technical University of Denmark, Building 208, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis (CBS), Technical University of Denmark, Building 208, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk|Center for Biological Sequence Analysis (CBS), Technical University of Denmark, Building 208, 2800 Lyngby, Denmark. laurent@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark', 3063, 'Algorithms|DNA Probes|Databases, Bibliographic|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg405', '14960456', 'The processing of the Affymetrix GeneChip data has been a recent focus for data analysts. Alternatives to the original procedure have been proposed and some of these new methods are widely used.'),
(71120, 2004, 'bio', 'Hybrid simulation of cellular behavior', 'Kiehl, Thomas R|Mattheyses, Robert M|Simmons, Melvin K', 'Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady, NY 12309, USA.|Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady, NY 12309, USA.|Bioinformatics Laboratory, GE Global Research, 1 Research Circle, Schenectady, NY 12309, USA.', 'United States|United States|United States', 90, 'Algorithms|Bacteriophage lambda|Cell Physiological Phenomena|Computer Simulation|Metabolism|Models, Biological|Numerical Analysis, Computer-Assisted|Signal Processing, Computer-Assisted|Systems Theory|Viral Proteins', 'Comparative Study', '10.1093/bioinformatics/btg409', '14960457', 'To be valuable to biological or biomedical research, in silico methods must be scaled to complex pathways and large numbers of interacting molecular species. The correct method for performing such simulations, discrete event simulation by Monte Carlo generation, is computationally costly for large complex systems. Approximation of molecular behavior by continuous models fails to capture stochastic behavior that is essential to many biological phenomena.'),
(71121, 2004, 'bio', 'A benchmark for Affymetrix GeneChip expression measures', 'Cope, Leslie M|Irizarry, Rafael A|Jaffee, Harris A|Wu, Zhijin|Speed, Terence P', 'Department of Mathematical Sciences, Johns Hopkins University, 104 Whitehead Hall, 3400 North Charles Street, Baltimore, MD 21218, USA.|Department of Mathematical Sciences, Johns Hopkins University, 104 Whitehead Hall, 3400 North Charles Street, Baltimore, MD 21218, USA.|Department of Mathematical Sciences, Johns Hopkins University, 104 Whitehead Hall, 3400 North Charles Street, Baltimore, MD 21218, USA.|Department of Mathematical Sciences, Johns Hopkins University, 104 Whitehead Hall, 3400 North Charles Street, Baltimore, MD 21218, USA.|Department of Mathematical Sciences, Johns Hopkins University, 104 Whitehead Hall, 3400 North Charles Street, Baltimore, MD 21218, USA.', 'United States|United States|United States|United States|United States', 225, 'Algorithms|Benchmarking|Computer Graphics|Gene Expression Profiling|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Reference Standards|Reproducibility of Results|Sensitivity and Specificity|Sequence Analysis, DNA|Software|United States|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg410', '14960458', 'The defining feature of oligonucleotide expression arrays is the use of several probes to assay each targeted transcript. This is a bonanza for the statistical geneticist, who can create probeset summaries with specific characteristics. There are now several methods available for summarizing probe level data from the popular Affymetrix GeneChips, but it is difficult to identify the best method for a given inquiry.'),
(71122, 2004, 'bio', 'Model-based methods for identifying periodically expressed genes based on time course microarray gene expression data', 'Luan, Y|Li, H', 'Rowe Program in Human Genetics, School of Medicine, University of California, Davis, CA 95616, USA.|Rowe Program in Human Genetics, School of Medicine, University of California, Davis, CA 95616, USA.', 'United States|United States', 88, 'Algorithms|Animals|Biological Clocks|Cell Cycle|Circadian Rhythm|Computer Simulation|Fungal Proteins|Gene Expression Profiling|Gene Expression Regulation|Gene Expression Regulation, Fungal|Heart|Liver|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Periodicity|Yeasts', 'Comparative Study', '10.1093/bioinformatics/btg413', '14960459', 'The expressions of many genes associated with certain periodic biological and cell cycle processes such as circadian rhythm regulation are known to be rhythmic. Identification of the genes whose time course expressions are synchronized to certain periodic biological process may help to elucidate the molecular basis of many diseases, and these gene products may in turn represent drug targets relevant to those diseases.'),
(71123, 2004, 'bio', 'Functional topology in a network of protein interactions', 'Przulj, N|Wigle, D A|Jurisica, I', 'Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.|Department of Computer Science, University of Toronto, Toronto, M5S 3G4, Canada.', 'Canada|Canada|Canada', 0, 'Algorithms|Cluster Analysis|Computer Simulation|Models, Biological|Multienzyme Complexes|Protein Interaction Mapping|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/btg415', '14960460', 'The building blocks of biological networks are individual protein-protein interactions (PPIs). The cumulative PPI data set in Saccharomyces cerevisiae now exceeds 78 000. Studying the network of these interactions will provide valuable insight into the inner workings of cells.'),
(71124, 2004, 'bio', 'An ontology for collaborative construction and analysis of cellular pathways', 'Demir, E|Babur, O|Dogrusoz, U|Gursoy, A|Ayaz, A|Gulesir, G|Nisanci, G|Cetin-Atalay, R', 'Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.|Center for Bioinformatics, Bilkent University, Ankara, Turkey.', 'Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey|Turkey', 0, 'Biopolymers|Cell Physiological Phenomena|Database Management Systems|Databases, Factual|Information Storage and Retrieval|Models, Biological|Signal Transduction|Software|Systems Integration|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/btg416', '14960461', 'As the scientific curiosity in genome studies shifts toward identification of functions of the genomes in large scale, data produced about cellular processes at molecular level has been accumulating with an accelerating rate. In this regard, it is essential to be able to store, integrate, access and analyze this data effectively with the help of software tools. Clearly this requires a strong ontology that is intuitive, comprehensive and uncomplicated.'),
(71125, 2004, 'bio', 'Advanced significance analysis of microarray data based on weighted resampling: a comparative study and application to gene deletions in Mycobacterium bovis', 'Kutalik, Zoltan|Inwald, Jacqueline|Gordon, Steve V|Hewinson, R Glyn|Butcher, Philip|Hinds, Jason|Cho, Kwang-Hyun|Wolkenhauer, Olaf', 'Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.|Control Systems Centre, Department of Electrical Engineering and Electronics, P.O. Box 88, UMIST, Manchester M60 1QD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Data Interpretation, Statistical|Gene Deletion|Gene Expression Profiling|Genetic Variation|Genome, Bacterial|Models, Genetic|Models, Statistical|Mycobacterium bovis|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg417', '14960462', 'When analyzing microarray data, non-biological variation introduces uncertainty in the analysis and interpretation. In this paper we focus on the validation of significant differences in gene expression levels, or normalized channel intensity levels with respect to different experimental conditions and with replicated measurements. A myriad of methods have been proposed to study differences in gene expression levels and to assign significance values as a measure of confidence. In this paper we compare several methods, including SAM, regularized t-test, mixture modeling, Wilks lambda score and variance stabilization. From this comparison we developed a weighted resampling approach and applied it to gene deletions in Mycobacterium bovis.'),
(71126, 2004, 'bio', 'Non-parametric, hypothesis-based analysis of microarrays for comparison of several phenotypes', 'Kowalski, Jeanne|Drake, Charles|Schwartz, Ronald H|Powell, Jonathan', 'Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA. jkowals1@jhmi.edu|Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA. jkowals1@jhmi.edu|Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA. jkowals1@jhmi.edu|Department of Oncology, Johns Hopkins University, Baltimore, MD 21205, USA. jkowals1@jhmi.edu', 'United States|United States|United States|United States', 21, 'Algorithms|Animals|Clonal Anergy|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Phenotype|Receptors, Antigen, T-Cell|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg418', '14960463', 'We present a statistical framework for the analysis of high-dimensional microarray data, where the goal is to compare intensities among several groups based on as few as a single sample from each group. In this setting, it is of interest to compare gene expression among several phenotypes to define candidate genes that simultaneously characterize several criteria, simultaneously, among the comparison groups. We motivate the approach by a comparative microarray experiment in which clones of a cell were singly exposed to several distinct but related conditions. The experiment was conducted to elucidate genes involved in pathways leading to T cell clonal anergy.'),
(71127, 2004, 'bio', 'Is cross-validation valid for small-sample microarray classification?', 'Braga-Neto, Ulisses M|Dougherty, Edward R', 'Section of Clinical Cancer Genetics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.|Section of Clinical Cancer Genetics, University of Texas MD Anderson Cancer Center, Houston, TX, USA.', 'United States|United States', 0, 'Algorithms|Benchmarking|Breast Neoplasms|Computer Simulation|Gene Expression Profiling|Genetic Predisposition to Disease|Genetic Testing|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Reproducibility of Results|Sample Size|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg419', '14960464', 'Microarray classification typically possesses two striking attributes: (1) classifier design and error estimation are based on remarkably small samples and (2) cross-validation error estimation is employed in the majority of the papers. Thus, it is necessary to have a quantifiable understanding of the behavior of cross-validation in the context of very small samples.'),
(71128, 2004, 'bio', 'A graph-theoretic modeling on GO space for biological interpretation of gene clusters', 'Lee, Sung Geun|Hur, Jung Uk|Kim, Yang Seok', 'Bioinformatics Unit, ISTECH Inc., No 704, Hyundai Town Vill 848-1, Janghang-dong, Ilsan-gu, Goyang city, Gyunggido, 411-380, Republic of Korea. sglee@istech21.com|Bioinformatics Unit, ISTECH Inc., No 704, Hyundai Town Vill 848-1, Janghang-dong, Ilsan-gu, Goyang city, Gyunggido, 411-380, Republic of Korea. sglee@istech21.com|Bioinformatics Unit, ISTECH Inc., No 704, Hyundai Town Vill 848-1, Janghang-dong, Ilsan-gu, Goyang city, Gyunggido, 411-380, Republic of Korea. sglee@istech21.com', '-|-|-', 0, 'Algorithms|Cluster Analysis|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Proteins|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg420', '14960465', 'With the advent of DNA microarray technologies, the parallel quantification of genome-wide transcriptions has been a great opportunity to systematically understand the complicated biological phenomena. Amidst the enthusiastic investigations into the intricate gene expression data, clustering methods have been the useful tools to uncover the meaningful patterns hidden in those data. The mathematical techniques, however, entirely based on the numerical expression data, do not show biologically relevant information on the clustering results.'),
(71129, 2004, 'bio', 'Knowledge discovery by automated identification and ranking of implicit relationships', 'Wren, Jonathan D|Bekeredjian, Raffi|Stewart, Jelena A|Shohet, Ralph V|Garner, Harold R', 'Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@ou.edu|Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@ou.edu|Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@ou.edu|Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@ou.edu|Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@ou.edu', 'United States|United States|United States|United States|United States', 150, 'Abstracting and Indexing as Topic|Algorithms|Artificial Intelligence|Computing Methodologies|Database Management Systems|Databases, Bibliographic|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Semantics|Terminology as Topic', 'Evaluation Studies', '10.1093/bioinformatics/btg421', '14960466', 'New relationships are often implicit from existing information, but the amount and growth of published literature limits the scope of analysis an individual can accomplish. Our goal was to develop and test a computational method to identify relationships within scientific reports, such that large sets of relationships between unrelated items could be sought out and statistically ranked for their potential relevance as a set.'),
(71130, 2004, 'bio', 'Parallel Metropolis coupled Markov chain Monte Carlo for Bayesian phylogenetic inference', 'Altekar, Gautam|Dwarkadas, Sandhya|Huelsenbeck, John P|Ronquist, Fredrik', 'Department of Computer Science, University of Rochester, USA. galtekar@cs.rochester.edu|Department of Computer Science, University of Rochester, USA. galtekar@cs.rochester.edu|Department of Computer Science, University of Rochester, USA. galtekar@cs.rochester.edu|Department of Computer Science, University of Rochester, USA. galtekar@cs.rochester.edu', 'United States|United States|United States|United States', 741, 'Algorithms|Bayes Theorem|Computer Communication Networks|Computing Methodologies|Gene Expression Profiling|Markov Chains|Monte Carlo Method|Numerical Analysis, Computer-Assisted|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg427', '14960467', 'Bayesian estimation of phylogeny is based on the posterior probability distribution of trees. Currently, the only numerical method that can effectively approximate posterior probabilities of trees is Markov chain Monte Carlo (MCMC). Standard implementations of MCMC can be prone to entrapment in local optima. Metropolis coupled MCMC [(MC)(3)], a variant of MCMC, allows multiple peaks in the landscape of trees to be more readily explored, but at the cost of increased execution time.'),
(71131, 2004, 'bio', 'LDDist: a Perl module for calculating LogDet pair-wise distances for protein and nucleotide sequences', 'Thollesson, Mikael', 'Department of Molecular Evolution, Evolutionary Biology Centre and Linnaeus Centre for Bioinformatics, Uppsala University, Norbyvägen 18C, SE-752 36 Uppsala, Sweden. lddist@artedi.ebc.uu.se', 'Sweden', 32, 'Algorithms|Amino Acid Sequence|Base Sequence|DNA|Evolution, Molecular|Gene Expression Profiling|Gene Frequency|Hypermedia|Molecular Sequence Data|Phylogeny|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg422', '14960468', 'LDDist is a Perl module implemented in C++ that allows the user to calculate LogDet pair-wise genetic distances for amino acid as well as nucleotide sequence data. It can handle site-to-site rate variation by treating a proportion of the sites as invariant and/or by assigning sites to different, presumably homogenous, rate categories. The rate-class assignments and invariant proportion can be set explicitly, or estimated by the program, the latter using either of two different capture-recapture methods. The assignment to rate categories in lieu of a phylogeny can be done using Shannon-Wiener index as a crude token for relative rate.'),
(71132, 2004, 'bio', 'Predicting protein secondary structure by cascade-correlation neural networks', 'Wood, Matthew J|Hirst, Jonathan D', 'School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, UK.|School of Chemistry, University of Nottingham, University Park, Nottingham NG7 2RD, UK.', 'United Kingdom|United Kingdom', 11, 'Algorithms|Amino Acid Sequence|Databases, Protein|Internet|Models, Chemical|Models, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|Statistics as Topic', 'Journal Article', '10.1093/bioinformatics/btg423', '14960469', 'The back-propagation neural network algorithm is a commonly used method for predicting the secondary structure of proteins. Whilst popular, this method can be slow to learn and here we compare it with an alternative: the cascade-correlation architecture. Using a constructive algorithm, cascade-correlation achieves predictive accuracies comparable to those obtained by back-propagation, in shorter time.'),
(71133, 2004, 'bio', 'SVM based method for predicting HLA-DRB1*0401 binding peptides in an antigen sequence', 'Bhasin, Manoj|Raghava, G P S', 'Institute of Microbial Technology, Sector 39A, Chandigarh, India.|Institute of Microbial Technology, Sector 39A, Chandigarh, India.', 'India|India', 0, 'Algorithms|Amino Acid Sequence|Antigens|Artificial Intelligence|Binding Sites|Binding Sites, Antibody|Cluster Analysis|Computing Methodologies|Drug Design|Epitopes, T-Lymphocyte|HLA-DR Antigens|HLA-DRB1 Chains|Molecular Sequence Data|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Binding|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/btg424', '14960470', 'Prediction of peptides binding with MHC class II allele HLA-DRB1(*)0401 can effectively reduce the number of experiments required for identifying helper T cell epitopes. This paper describes support vector machine (SVM) based method developed for identifying HLA-DRB1(*)0401 binding peptides in an antigenic sequence. SVM was trained and tested on large and clean data set consisting of 567 binders and equal number of non-binders. The accuracy of the method was 86% when evaluated through 5-fold cross-validation technique.'),
(71134, 2004, 'bio', 'PIVOT: protein interacions visualizatiOn tool', 'Orlev, Nir|Shamir, Ron|Shiloh, Yosef', 'Department of Human Genetics, Faculty of Medicine, Tel Aviv University, Israel. niro@post.tau.ac.il|Department of Human Genetics, Faculty of Medicine, Tel Aviv University, Israel. niro@post.tau.ac.il|Department of Human Genetics, Faculty of Medicine, Tel Aviv University, Israel. niro@post.tau.ac.il', 'Israel|Israel|Israel', 0, 'Database Management Systems|Databases, Protein|Information Storage and Retrieval|Protein Binding|Protein Interaction Mapping|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg426', '14960471', 'Protein Interaction VisualizatiOn Tool (PIVOT) is a visualization tool for protein-protein interactions. It allows the user to create personal data sets of interactions by combining information from private and public data sources. The user can gradually access the interactions data using a clear interactive map that is focused on the researchers protein of interest, and is reshaped and expanded in response to his/her queries. It also offers several visual enhancements and intelligent queries that help the user efficiently study it. PIVOT allows the user to search the interactions data set for paths connecting proteins that are expected to co-operate. The user can also employ PIVOT to predict unknown interactions among proteins, based on interactions among their homologous proteins in other species.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71135, 2004, 'bio', 'The Jalview Java alignment editor', 'Clamp, Michele|Cuff, James|Searle, Stephen M|Barton, Geoffrey J', 'The Wellcome Trust Sanger Institute, Hinxton, UK. michele@sanger.ac.uk|The Wellcome Trust Sanger Institute, Hinxton, UK. michele@sanger.ac.uk|The Wellcome Trust Sanger Institute, Hinxton, UK. michele@sanger.ac.uk|The Wellcome Trust Sanger Institute, Hinxton, UK. michele@sanger.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom', 1134, 'Algorithms|Database Management Systems|Documentation|Hypermedia|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface|Word Processing', 'Journal Article', '10.1093/bioinformatics/btg430', '14960472', 'Multiple sequence alignment remains a crucial method for understanding the function of groups of related nucleic acid and protein sequences. However, it is known that automatic multiple sequence alignments can often be improved by manual editing. Therefore, tools are needed to view and edit multiple sequence alignments. Due to growth in the sequence databases, multiple sequence alignments can often be large and difficult to view efficiently. The Jalview Java alignment editor is presented here, which enables fast viewing and editing of large multiple sequence alignments.'),
(71136, 2004, 'bio', 'SEPON, a Selection and Evaluation Pipeline for OligoNucleotides based on ESTs with a non-target Tm algorithm for reducing cross-hybridization in microarray gene expression experiments', 'Hornshøj, Henrik|Stengaard, Henrik|Panitz, Frank|Bendixen, Christian', 'Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, Research Center Foulum, DK-8830 Tjele, Denmark. henrikh.jensen@agrsci.dk|Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, Research Center Foulum, DK-8830 Tjele, Denmark. henrikh.jensen@agrsci.dk|Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, Research Center Foulum, DK-8830 Tjele, Denmark. henrikh.jensen@agrsci.dk|Department of Animal Breeding and Genetics, Danish Institute of Agricultural Sciences, Research Center Foulum, DK-8830 Tjele, Denmark. henrikh.jensen@agrsci.dk', 'Denmark|Denmark|Denmark|Denmark', 10, 'Algorithms|Artifacts|DNA Probes|Exons|Expressed Sequence Tags|Oligonucleotide Array Sequence Analysis|Oligonucleotides|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/btg434', '14960473', 'SEPON, Selection and Evaluation Pipeline for OligoNucleotide generates n-mer oligonucleotide sequences from expressed sequence tags of non-annotated genomes for microarray gene-expression profiling. A non-target melting temperature (T(m)) algorithm will reduce cross-hybridization by estimating T(m) of oligonucleotide hybridization to non-specific targets (non-target T(m)) and discard oligonucleotides with non-target T(m) estimate above user-defined threshold. SEPON allows user-defined filtering, predicts exon location, assigns penalty based on 3 distance, GC content, secondary structure T(m) and non-target T(m) and ranks oligonucleotides for optimal selection.'),
(71137, 2004, 'bio', 'Gene specific siRNA selector', 'Levenkova, Natasha|Gu, Qingjuan|Rux, John J', 'The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104, USA.|The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104, USA.|The Wistar Institute, 3601 Spruce Street, Philadelphia, PA 19104, USA.', 'United States|United States|United States', 0, 'Algorithms|Computer-Aided Design|Drug Design|RNA, Small Interfering|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/btg437', '14960474', 'Small interfering RNA (siRNA) is used in functional genomics applications to decrease the expression of a target gene, which may yield a biological effect that suggests a function for the target gene. The siRNA design tool scans a target gene for candidate siRNA sequences that satisfy user-adjustable rules. Selected candidates are then screened to identify those siRNA sequences that are specific to the gene of interest.'),
(71138, 2004, 'bio', 'VisCoSe: visualization and comparison of consensus sequences', 'Spitzer, Michael|Fuellen, Georg|Cullen, Paul|Lorkowski, Stefan', 'Integrated Functional Genomics, IZKF, University Hospital Münster, Von-Esmarch-Str. 56, 48149 Münster, Germany. michael.spitzer@uni-muenster.de|Integrated Functional Genomics, IZKF, University Hospital Münster, Von-Esmarch-Str. 56, 48149 Münster, Germany. michael.spitzer@uni-muenster.de|Integrated Functional Genomics, IZKF, University Hospital Münster, Von-Esmarch-Str. 56, 48149 Münster, Germany. michael.spitzer@uni-muenster.de|Integrated Functional Genomics, IZKF, University Hospital Münster, Von-Esmarch-Str. 56, 48149 Münster, Germany. michael.spitzer@uni-muenster.de', 'Germany|Germany|Germany|Germany', 12, 'Algorithms|Amino Acid Sequence|Base Sequence|Consensus Sequence|Database Management Systems|Hypermedia|Information Storage and Retrieval|Molecular Sequence Data|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg444', '14960475', 'We introduce visualization and comparison of consensus sequences (VisCoSe) as a WWW service and a stand-alone command line Perl script for visualizing and comparing consensus sequences of protein and nucleotide sequences. VisCoSe is the only interface available that simultaneously calculates consensus sequences of multiple data sets and automatically compares these consensus sequences. Furthermore, VisCoSe allows visualization of chemical properties of amino acids.'),
(71139, 2004, 'bio', 'HIVbase: a PC/Windows-based software offering storage and querying power for locally held HIV-1 genetic, experimental and clinical data', 'Lamers, Susanna|Beason, Scott|Dunlap, Luke|Compton, Robert|Salemi, Marco', 'Gene Johnson Inc., St Augustine, FL, USA.|Gene Johnson Inc., St Augustine, FL, USA.|Gene Johnson Inc., St Augustine, FL, USA.|Gene Johnson Inc., St Augustine, FL, USA.|Gene Johnson Inc., St Augustine, FL, USA.', 'United States|United States|United States|United States|United States', 11, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|HIV|Humans|Information Storage and Retrieval|Microcomputers|Programming Languages|Sequence Alignment|Sequence Analysis|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg445', '14960476', 'Human immunodeficiency virus (HIV) research involves ongoing, repetitious sequencing of the HIV genome and the massive accumulation of associated investigational data. As a result, the storage of annotated DNA and/or protein sequences, as well as information retrieval, have become increasingly difficult tasks, with scientists extracting less information from their collected data than they should.'),
(71140, 2004, 'bio', 'Frequency Finder: a multi-source web application for collection of public allele frequencies of SNP markers', 'Nguyen, Tu H|Liu, Chunyu|Gershon, Elliot S|McMahon, Francis J', 'Department of Psychiatry, University of Chicago, IL 60616, USA. tnguyen@yoda.bsd.uchicago.edu|Department of Psychiatry, University of Chicago, IL 60616, USA. tnguyen@yoda.bsd.uchicago.edu|Department of Psychiatry, University of Chicago, IL 60616, USA. tnguyen@yoda.bsd.uchicago.edu|Department of Psychiatry, University of Chicago, IL 60616, USA. tnguyen@yoda.bsd.uchicago.edu', 'United States|United States|United States|United States', 7, 'Algorithms|Databases, Genetic|Gene Frequency|Genetic Markers|Hypermedia|Internet|Polymorphism, Single Nucleotide|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg446', '14960477', 'Publicly available single nucleotide polymorphism (SNP) allele frequencies are an important resource for the selection of genetic markers that may be most useful for gene mapping and association studies. Data mining these allele frequencies through disparate public databases and Websites is time consuming and can result in inconsistent findings. We have developed a web-based software tool, Frequency Finder, to acquire SNP allele frequencies from multiple public data sources and return a summarized result to the user. Our software optimizes and automates the search of candidate markers, decreasing the amount of time it would take to extract pertinent data manually. We have included several methods to output the data, including on-screen and as a compressed text file. We show that Frequency Finder accurately retrieves available frequency data from the available sources. Using this tool, we detect significant differences between Asian, African and Caucasian populations in the allele frequency spectra of 246 097 SNPs. While limited to public databases that provide web-based access to allele frequencies, Frequency Finder provides a single, user-friendly interface for retrieving allele frequencies for large batches of SNPs from multiple data sources.'),
(71141, 2004, 'bio', 'Improved prediction of MHC class I and class II epitopes using a novel Gibbs sampling approach', 'Nielsen, Morten|Lundegaard, Claus|Worning, Peder|Hvid, Christina Sylvester|Lamberth, Kasper|Buus, Søren|Brunak, Søren|Lund, Ole', 'Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk|Center for Biological Sequence Analysis, BioCentrum-DTU, Building 208, Technical University of Denmark, DK-2800 Lyngby, Denmark. mneil@cbs.dtu.dk', 'Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark|Denmark', 213, 'Algorithms|Binding Sites|Epitopes, T-Lymphocyte|Histocompatibility Antigens Class I|Histocompatibility Antigens Class II|Major Histocompatibility Complex|Protein Binding|Protein Interaction Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth100', '14962912', 'Prediction of which peptides will bind a specific major histocompatibility complex (MHC) constitutes an important step in identifying potential T-cell epitopes suitable as vaccine candidates. MHC class II binding peptides have a broad length distribution complicating such predictions. Thus, identifying the correct alignment is a crucial part of identifying the core of an MHC class II binding motif. In this context, we wish to describe a novel Gibbs motif sampler method ideally suited for recognizing such weak sequence motifs. The method is based on the Gibbs sampling method, and it incorporates novel features optimized for the task of recognizing the binding motif of MHC classes I and II. The method locates the binding motif in a set of sequences and characterizes the motif in terms of a weight-matrix. Subsequently, the weight-matrix can be applied to identifying effectively potential MHC binding peptides and to guiding the process of rational vaccine design.'),
(71142, 2004, 'bio', 'Simple sequence repeat marker loci discovery using SSR primer', 'Robinson, Andrew J|Love, Christopher G|Batley, Jacqueline|Barker, Gary|Edwards, David', 'Plant Biotechnology Centre, Primary Industries Research Victoria, La Trobe University, Bundoora 3086, Victoria, Australia.|Plant Biotechnology Centre, Primary Industries Research Victoria, La Trobe University, Bundoora 3086, Victoria, Australia.|Plant Biotechnology Centre, Primary Industries Research Victoria, La Trobe University, Bundoora 3086, Victoria, Australia.|Plant Biotechnology Centre, Primary Industries Research Victoria, La Trobe University, Bundoora 3086, Victoria, Australia.|Plant Biotechnology Centre, Primary Industries Research Victoria, La Trobe University, Bundoora 3086, Victoria, Australia.', 'Australia|Australia|Australia|Australia|Australia', 85, 'Algorithms|Chromosome Mapping|DNA Primers|Genetic Markers|Internet|Microsatellite Repeats|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration', 'Evaluation Studies', '10.1093/bioinformatics/bth104', '14962913', 'Simple sequence repeats (SSRs) have become important molecular markers for a broad range of applications, such as genome mapping and characterization, phenotype mapping, marker assisted selection of crop plants and a range of molecular ecology and diversity studies. With the increase in the availability of DNA sequence information, an automated process to identify and design PCR primers for amplification of SSR loci would be a useful tool in plant breeding programs. We report an application that integrates SPUTNIK, an SSR repeat finder, with Primer3, a PCR primer design program, into one pipeline tool, SSR Primer. On submission of multiple FASTA formatted sequences, the script screens each sequence for SSRs using SPUTNIK. The results are parsed to Primer3 for locus-specific primer design. The script makes use of a Web-based interface, enabling remote use.'),
(71143, 2004, 'bio', 'Align-m--a new algorithm for multiple alignment of highly divergent sequences', 'Van Walle, Ivo|Lasters, Ignace|Wyns, Lode', 'Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be|Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be|Department of Ultrastructure, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussel, Belgium. ivwalle@vub.ac.be', 'Belgium|Belgium|Belgium', 77, 'Algorithms|Amino Acid Sequence|Genetic Variation|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth116', '14962914', 'Multiple alignment of highly divergent sequences is a challenging problem for which available programs tend to show poor performance. Generally, this is due to a scoring function that does not describe biological reality accurately enough or a heuristic that cannot explore solution space efficiently enough. In this respect, we present a new program, Align-m, that uses a non-progressive local approach to guide a global alignment.'),
(71144, 2004, 'bio', 'VARAN: a web server for variability analysis of DNA microarray experiments', 'Golfier, G|Dang, M Tran|Dauphinot, L|Graison, E|Rossier, J|Potier, M-C', 'Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr|Neurobiologie et Diversité Cellulaire, CNRS UMR7637, Ecole Supérieure de Physique et de Chimie Industrielles, 10 rue Vauquelin, 75005 Paris, France. geoffroy.golfier@espci.fr', 'France|France|France|France|France|France', 13, 'Algorithms|Computing Methodologies|Data Interpretation, Statistical|Genetic Variation|Internet|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|Statistical Distributions|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth117', '14962915', 'Here, we describe a tool for VARiability Analysis of DNA microarrays experiments (VARAN), a freely available Web server that performs a signal intensity based analysis of the log2 expression ratio variability deduced from DNA microarray data (one or two channels). Two modules are proposed: VARAN generator to compute a sliding windows analysis of the experimental variability (mean and SD) and VARAN analyzer to compare experimental data with an asymptotic variability model previously built with the generator module from control experiments. Both modules provide normalized intensity signals with five possible methods, log ratio values and a list of genes showing significant variations between conditions.'),
(71145, 2004, 'bio', 'Analysis of variance components in gene expression data', 'Chen, James J|Delongchamp, Robert R|Tsai, Chen-An|Hsueh, Huey-miin|Sistare, Frank|Thompson, Karol L|Desai, Varsha G|Fuscoe, James C', 'Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov|Division of Biometry and Risk Assessment, National Center for Toxicology Research, Food and Drug Administration, Jefferson, AR 72079, USA. jchen@nctr.fda.gov', 'United States|United States|United States|United States|United States|United States|United States|United States', 72, 'Algorithms|Analysis of Variance|Base Sequence|Gene Expression Profiling|Genetic Variation|Models, Genetic|Models, Statistical|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth118', '14962916', 'A microarray experiment is a multi-step process, and each step is a potential source of variation. There are two major sources of variation: biological variation and technical variation. This study presents a variance-components approach to investigating animal-to-animal, between-array, within-array and day-to-day variations for two data sets. The first data set involved estimation of technical variances for pooled control and pooled treated RNA samples. The variance components included between-array, and two nested within-array variances: between-section (the upper- and lower-sections of the array are replicates) and within-section (two adjacent spots of the same gene are printed within each section). The second experiment was conducted on four different weeks. Each week there were reference and test samples with a dye-flip replicate in two hybridization days. The variance components included week-to-week, animal-to-animal and between-array and within-array variances.'),
(71146, 2004, 'bio', 'Gap statistics for whole genome shotgun DNA sequencing projects', 'Wendl, Michael C|Yang, Shiaw-Pyng', 'Genome Sequencing Center, Washington University School of Medicine, Box 8501, 4444 Forest Park Blvd., Saint Louis, MO 63108 USA. mwendl@wustl.edu|Genome Sequencing Center, Washington University School of Medicine, Box 8501, 4444 Forest Park Blvd., Saint Louis, MO 63108 USA. mwendl@wustl.edu', 'United States|United States', 10, 'Animals|Artifacts|Computer Simulation|Data Interpretation, Statistical|Genetic Variation|Humans|Models, Genetic|Models, Statistical|Sample Size|Sequence Alignment|Sequence Analysis, DNA|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bth120', '14962917', 'Investigators utilize gap estimates for DNA sequencing projects. Standard theories assume sequences are independently and identically distributed, leading to appreciable under-prediction of gaps.'),
(71147, 2004, 'bio', 'Amplicon: software for designing PCR primers on aligned DNA sequences', 'Jarman, Simon N', 'Australian Antarctic Division, Channel Highway, Kingston, TAS, 7050, Australia. simon.jarman@aad.gov.au', 'Australia', 63, 'Algorithms|DNA Primers|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth121', '14962918', 'Amplicon is a program for designing PCR primers on aligned groups of DNA sequences. The most important application for Amplicon is the design of group-specific PCR primer sets that amplify a DNA region from a given taxonomic group but do not amplify orthologous regions from other taxonomic groups.'),
(71148, 2004, 'bio', 'OBIYagns: a grid-based biochemical simulator with a parameter estimator', 'Kimura, Shuhei|Kawasaki, Takuji|Hatakeyama, Mariko|Naka, Takashi|Konishi, Fumikazu|Konagaya, Akihiko', 'Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.|Bioinformatics Group, RIKEN Genomic Sciences Center, 1-7-22 Suehirocho, Tsurumi-ku, Yokohama, Kanagawa 230-0045, Japan.', 'Japan|Japan|Japan|Japan|Japan|Japan', 8, 'Algorithms|Biochemistry|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Gene Expression Regulation|Models, Biological|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth122', '14962919', 'OBIYagns (yet another gene network simulator) is a biochemical system simulator that comprises a multiple-user Web-based graphical interface, an ordinary differential equation solver and a parameter estimators distributed over an open bioinformatics grid (OBIGrid). This grid-based biochemical simulation system can achieve high performance and provide a secure simulation environment for estimating kinetic parameters in an acceptable time period. OBIYagns can be applied to larger system biology-oriented simulation projects.'),
(71149, 2004, 'bio', 'Evaluation and optimization of clustering in gene expression data analysis', 'Famili, A Fazel|Liu, Ganming|Liu, Ziying', 'Institute for Information Technology, National Research Council of Canada, Ottawa, ON, Canada. fazel.famili@nrc-cnrc.gc.ca|Institute for Information Technology, National Research Council of Canada, Ottawa, ON, Canada. fazel.famili@nrc-cnrc.gc.ca|Institute for Information Technology, National Research Council of Canada, Ottawa, ON, Canada. fazel.famili@nrc-cnrc.gc.ca', 'Canada|Canada|Canada', 33, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Genetic Variation|Genome|Genomic Instability|Hepacivirus|Leukemia|Models, Genetic|Models, Statistical|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Yeasts', 'Comparative Study', '10.1093/bioinformatics/bth124', '14962920', 'A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expression. This is strongly desirable when a large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functions or gene response analysis.'),
(71150, 2004, 'bio', 'A general computational model of mitochondrial metabolism in a whole organelle scale', 'Yugi, Katsuyuki|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Endo 5322, Fujisawa, Kanagawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Endo 5322, Fujisawa, Kanagawa, 252-8520, Japan.', 'Japan|Japan', 29, 'Animals|Computational Biology|Computer Graphics|Computer Simulation|Gene Expression Regulation|Humans|Mitochondria|Mitochondrial Proteins|Models, Biological|Multienzyme Complexes|Organelles|Proteome|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth125', '14962921', 'A computational tool for mitochondrial systems biology has been developed as a simulation model of E-Cell2, a publicly available simulation system. The general model consists of 58 enzymatic reactions and 117 metabolites, representing the respiratory chain, the TCA cycle, the fatty acid beta-oxidation and the inner-membrane transport system. It is based on previously published enzyme kinetics studies in the literature, we have successfully integrated and packaged them into a single large model. The model can be easily extended and modified so that mitochondrial biologists/physiologists can integrate their own models and evaluate them in the context of the whole organelle metabolism.'),
(71151, 2004, 'bio', 'Combining partial order alignment and progressive multiple sequence alignment increases alignment speed and scalability to very large alignment problems', 'Grasso, Catherine|Lee, Christopher', 'Department of Chemistry and Biochemistry, Molecular Biology Institute, Center for Genomics and Proteomics, University of California, Los Angeles, CA 90095-1570, USA.|Department of Chemistry and Biochemistry, Molecular Biology Institute, Center for Genomics and Proteomics, University of California, Los Angeles, CA 90095-1570, USA.', 'United States|United States', 91, 'Algorithms|Computing Methodologies|Databases, Protein|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/bth126', '14962922', 'Partial order alignment (POA) has been proposed as a new approach to multiple sequence alignment (MSA), which can be combined with existing methods such as progressive alignment. This is important for addressing problems both in the original version of POA (such as order sensitivity) and in standard progressive alignment programs (such as information loss in complex alignments, especially surrounding gap regions).'),
(71152, 2004, 'bio', 'BioOptimizer: a Bayesian scoring function approach to motif discovery', 'Jensen, Shane T|Liu, Jun S', 'Department of Statistics, Harvard University, Cambridge, MA 02138-2901, USA. jensen@stat.harvard.edu|Department of Statistics, Harvard University, Cambridge, MA 02138-2901, USA. jensen@stat.harvard.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Motifs|Bayes Theorem|Binding Sites|DNA|Protein Binding|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth127', '14962923', 'Transcription factors (TFs) bind directly to short segments on the genome, often within hundreds to thousands of base pairs upstream of gene transcription start sites, to regulate gene expression. The experimental determination of TFs binding sites is expensive and time-consuming. Many motif-finding programs have been developed, but no program is clearly superior in all situations. Practitioners often find it difficult to judge which of the motifs predicted by these algorithms are more likely to be biologically relevant.'),
(71153, 2004, 'bio', 'A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence alignments', 'Dekker, John P|Fodor, Anthony|Aldrich, Richard W|Yellen, Gary', 'Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.|Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.|Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.|Department of Neurobiology, Harvard Medical School, 220 Longwood Avenue, Boston, MA 02115, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Computer Simulation|Evolution, Molecular|Genetic Variation|Likelihood Functions|Models, Genetic|Models, Statistical|Regression Analysis|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth128', '14962924', 'The constituent amino acids of a protein work together to define its structure and to facilitate its function. Their interdependence should be apparent in the evolutionary record of each protein family: positions in the sequence of a protein family that are intimately associated in space or in function should co-vary in evolution. A recent approach by Ranganathan and colleagues proposes to look at subsets of a protein family, selected for their sequence at one position, to see how this affects variation at other positions.'),
(71154, 2004, 'bio', 'Evaluating the predictability of conformational switching in RNA', 'Voss, Björn|Meyer, Carsten|Giegerich, Robert', 'International NRW Graduate School in Bioinformatics and Genome Research, Bielefeld, Germany. bvoss@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Bielefeld, Germany. bvoss@techfak.uni-bielefeld.de|International NRW Graduate School in Bioinformatics and Genome Research, Bielefeld, Germany. bvoss@techfak.uni-bielefeld.de', 'Germany|Germany|Germany', 45, 'Algorithms|Computer Simulation|Humans|Models, Chemical|Models, Molecular|Models, Statistical|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth129', '14962925', 'There are various cases where the biological function of an RNA molecule involves a reversible change of conformation. paRNAss is a software approach to the prediction of such structural switching in RNA. It is based on three hypotheses about the secondary structure space of a switching RNA molecule that can be evaluated by RNA folding and structure comparison. In the positive case, the predicted structural switching must be verified experimentally.'),
(71155, 2004, 'bio', 'A graph theoretical approach for predicting common RNA secondary structure motifs including pseudoknots in unaligned sequences', 'Ji, Yongmei|Xu, Xing|Stormo, Gary D', 'Department of Genetics, Washington University, School of Medicine, St. Louis, MO 63110, USA.|Department of Genetics, Washington University, School of Medicine, St. Louis, MO 63110, USA.|Department of Genetics, Washington University, School of Medicine, St. Louis, MO 63110, USA.', 'United States|United States|United States', 0, 'Algorithms|Base Sequence|Molecular Sequence Data|Nucleic Acid Conformation|RNA|Regulatory Sequences, Ribonucleic Acid|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Evaluation Studies', '10.1093/bioinformatics/bth131', '14962926', 'RNA structure motifs contained in mRNAs have been found to play important roles in regulating gene expression. However, identification of novel RNA regulatory motifs using computational methods has not been widely explored. Effective tools for predicting novel RNA regulatory motifs based on genomic sequences are needed.'),
(71156, 2004, 'bio', 'Analysis of disturbed images', 'Kauer, Gerhard|Blöcker, Helmut', 'Department of Genome Analysis, GBF-German Research Centre for Biotechnology, Mascheroder Weg 1, D-38124 Braunschweig, Germany. kauer@nwt.fho-emden.de|Department of Genome Analysis, GBF-German Research Centre for Biotechnology, Mascheroder Weg 1, D-38124 Braunschweig, Germany. kauer@nwt.fho-emden.de', 'Germany|Germany', 3, 'Algorithms|Artifacts|Color|Colorimetry|Image Enhancement|Image Interpretation, Computer-Assisted|Models, Statistical|Signal Processing, Computer-Assisted|Stochastic Processes', 'Comparative Study', '10.1093/bioinformatics/bth099', '14962927', 'Images in cellular and molecular biology (from microscopy, blots, biochips, etc.) are often disturbed, so that the detection and analysis of the respective relevant geometrical objects may be difficult or error-prone. The disturbances are either caused by the detector, usually a CCD camera, or by the experimental setup. Furthermore, microtechnology experiments often require simultaneous multiple-colour stainings. Therefore, the image analysis of such experiments should be colour-sensitive, and colour shadings should not only be detectable but also quantifiable.'),
(71157, 2004, 'bio', 'Rapid 3D protein structure database searching using information retrieval techniques', 'Aung, Zeyar|Tan, Kian-Lee', 'Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543. zeyaraun@comp.nus.edu.sg|Department of Computer Science, National University of Singapore, 3 Science Drive 2, Singapore 117543. zeyaraun@comp.nus.edu.sg', 'Singapore|Singapore', 0, 'Algorithms|Amino Acid Sequence|Computer Simulation|Database Management Systems|Information Storage and Retrieval|Models, Molecular|Molecular Sequence Data|Protein Conformation|Protein Structure, Secondary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/bth036', '14962928', 'As the sizes of three-dimensional (3D) protein structure databases are growing rapidly nowadays, exhaustive database searching, in which a 3D query structure is compared to each and every structure in the database, becomes inefficient. We propose a rapid 3D protein structure retrieval system named ProtDex2, in which we adopt the techniques used in information retrieval systems in order to perform rapid database searching without having access to every 3D structure in the database. The retrieval process is based on the inverted-file index constructed on the feature vectors of the relationships between the secondary structure elements (SSEs) of all the 3D protein structures in the database. ProtDex2 is a significant improvement, both in terms of speed and accuracy, upon its predecessor system, ProtDex.'),
(71158, 2004, 'bio', 'GeneAnnot: comprehensive two-way linking between oligonucleotide array probesets and GeneCards genes', 'Chalifa-Caspi, Vered|Yanai, Itai|Ophir, Ron|Rosen, Naomi|Shmoish, Michael|Benjamin-Rodrig, Hila|Shklar, Maxim|Stein, Tsippi Iny|Shmueli, Orit|Safran, Marilyn|Lancet, Doron', 'Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.|Department of Biological Services, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel|Israel', 42, 'Algorithms|Chromosome Mapping|Documentation|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth081', '14962929', 'High density oligonucleotide arrays are usually annotated in a one-to-one fashion, with each probeset assigned to one gene. However, in reality, subsets of oligonucleotides in a probeset may match sequences within more than one gene, potentially leading to misinterpretations. Moreover, a gene is often represented by more than one probeset, and analyzing probe matches at the mRNA level can help one deduce whether these probesets are derived from the same or different splice variants.'),
(71159, 2004, 'bio', 'ParSeq: searching motifs with structural and biochemical properties', 'Schmollinger, M|Fischer, I|Nerz, C|Pinkenburg, S|Götz, F|Kaufmann, M|Lange, K-J|Reuter, R|Rosenstiel, W|Zell, A', 'Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.|Center for Bioinformatics, University of Tubingen, Sand 14, 72076 Tubingen, Germany.', 'Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany|Germany', 0, 'Algorithms|Amino Acid Motifs|Biochemistry|Programming Languages|Proteins|Sequence Alignment|Sequence Analysis|Software|Structure-Activity Relationship', 'Journal Article', '10.1093/bioinformatics/bth083', '14962930', 'Searches for variable motifs such as protein-binding sites or promoter regions are more complex than the search for casual motifs. For example, in amino acid sequences comparing motifs alone mostly proves to be insufficient to detect regions that represent proteins with a special function, because the function depends on biochemical properties of individual amino acids (such as polarity or hydrophobicity). Pure string matching programs are not able to find these motifs, hence, we developed ParSeq, a program that combines the search for motifs with certain structural properties, the verification of biochemical properties, an approximate search mechanism and a stepwise creation of the motif description by allowing to search on previously obtained results.'),
(71160, 2004, 'bio', 'RAG: RNA-As-Graphs database--concepts, analysis, and features', 'Gan, Hin Hark|Fera, Daniela|Zorn, Julie|Shiffeldrim, Nahum|Tang, Michael|Laserson, Uri|Kim, Namhee|Schlick, Tamar', 'Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.|Department of Chemistry, New York University, New York, NY 10003, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Conserved Sequence|Database Management Systems|Databases, Nucleic Acid|Information Storage and Retrieval|Sequence Alignment|Sequence Analysis, RNA', 'Evaluation Studies', '10.1093/bioinformatics/bth084', '14962931', 'Understanding RNAs structural diversity is vital for identifying novel RNA structures and pursuing RNA genomics initiatives. By classifying RNA secondary motifs based on correlations between conserved RNA secondary structures and functional properties, we offer an avenue for predicting novel motifs. Although several RNA databases exist, no comprehensive schemes are available for cataloguing the range and diversity of RNAs structural repertoire.'),
(71161, 2004, 'bio', 'Automatic prediction of protein domains from sequence information using a hybrid learning system', 'Nagarajan, Niranjan|Yona, Golan', 'Department of Computer Science, Cornell University, Upson Hall, Ithaca, NY 14853, USA. niranjan@cs.cornell.edu|Department of Computer Science, Cornell University, Upson Hall, Ithaca, NY 14853, USA. niranjan@cs.cornell.edu', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Cluster Analysis|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Pattern Recognition, Automated|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth086', '14962932', 'We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence and are combined into a single predictor using a neural network. The output is further smoothed and post-processed using a probabilistic model to predict the most likely transition positions between domains.'),
(71162, 2004, 'bio', 'NetAffx Gene Ontology Mining Tool: a visual approach for microarray data analysis', 'Cheng, Jill|Sun, Shaw|Tracy, Adam|Hubbell, Earl|Morris, Joseph|Valmeekam, Venu|Kimbrough, Andrew|Cline, Melissa S|Liu, Guoying|Shigeta, Ron|Kulp, David|Siani-Rose, Michael A', 'Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@affymetrix.com|Affymetrix Corporation, Bioinformatics, 6550 Vallejo Street, Suite 100, Emeryville, CA 94608, USA. jill_cheng@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', 26, 'Abstracting and Indexing as Topic|Algorithms|Computer Graphics|Database Management Systems|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth087', '14962933', 'The NetAffx Gene Ontology (GO) Mining Tool is a web-based, interactive tool that permits traversal of the GO graph in the context of microarray data. It accepts a list of Affymetrix probe sets and renders a GO graph as a heat map colored according to significance measurements. The rendered graph is interactive, with nodes linked to public web sites and to lists of the relevant probe sets. The GO Mining Tool provides visualization combining biological annotation with expression data, encompassing thousands of genes in one interactive view.'),
(71163, 2004, 'bio', 'GOstat: find statistically overrepresented Gene Ontologies within a group of genes', 'Beissbarth, Tim|Speed, Terence P', 'Walter and Eliza Hall Institute of medical Research, 1G Royal Parade, Parkville, Vic 3050, Australia. beissbarth@wehi.edu.au|Walter and Eliza Hall Institute of medical Research, 1G Royal Parade, Parkville, Vic 3050, Australia. beissbarth@wehi.edu.au', 'Australia|Australia', 943, 'Abstracting and Indexing as Topic|Algorithms|DNA|Databases, Genetic|Documentation|Gene Expression Profiling|Internet|Models, Genetic|Models, Statistical|Natural Language Processing|Software', 'Journal Article', '10.1093/bioinformatics/bth088', '14962934', 'Modern experimental techniques, as for example DNA microarrays, as a result usually produce a long list of genes, which are potentially interesting in the analyzed process. In order to gain biological understanding from this type of data, it is necessary to analyze the functional annotations of all genes in this list. The Gene-Ontology (GO) database provides a useful tool to annotate and analyze the functions of a large number of genes. Here, we introduce a tool that utilizes this information to obtain an understanding of which annotations are typical for the analyzed list of genes. This program automatically obtains the GO annotations from a database and generates statistics of which annotations are overrepresented in the analyzed list of genes. This results in a list of GO terms sorted by their specificity.'),
(71164, 2004, 'bio', 'ACID: a database for microarray clone information', 'Ringnér, Markus|Veerla, Srinivas|Andersson, Samuel|Staaf, Johan|Häkkinen, Jari', 'Complex Systems Division, Lund University, Sweden.|Complex Systems Division, Lund University, Sweden.|Complex Systems Division, Lund University, Sweden.|Complex Systems Division, Lund University, Sweden.|Complex Systems Division, Lund University, Sweden.', 'Sweden|Sweden|Sweden|Sweden|Sweden', 0, 'Animals|Chromosome Mapping|Cloning, Molecular|Database Management Systems|Databases, Genetic|Genome, Human|Humans|Information Storage and Retrieval|Internet|Mice|Oligonucleotide Array Sequence Analysis|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth089', '14962935', 'Array Close Information Database is an online database for information about microarray cDNA clones. For each clone, the database contents include assigned UniGene cluster(s), location in the full-length transcript, assigned gene ontology terms and position in the genome assembly.'),
(71165, 2004, 'bio', 'A comparison of scoring functions for protein sequence profile alignment', 'Edgar, Robert C|Sjölander, Kimmen', 'bob@drive5.com|bob@drive5.com', '-|-', 92, 'Algorithms|Amino Acid Sequence|Gene Expression Profiling|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth090', '14962936', 'In recent years, several methods have been proposed for aligning two protein sequence profiles, with reported improvements in alignment accuracy and homolog discrimination versus sequence-sequence methods (e.g. BLAST) and profile-sequence methods (e.g. PSI-BLAST). Profile-profile alignment is also the iterated step in progressive multiple sequence alignment algorithms such as CLUSTALW. However, little is known about the relative performance of different profile-profile scoring functions. In this work, we evaluate the alignment accuracy of 23 different profile-profile scoring functions by comparing alignments of 488 pairs of sequences with identity < or =30% against structural alignments. We optimize parameters for all scoring functions on the same training set and use profiles of alignments from both PSI-BLAST and SAM-T99. Structural alignments are constructed from a consensus between the FSSP database and CE structural aligner. We compare the results with sequence-sequence and sequence-profile methods, including BLAST and PSI-BLAST.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71166, 2004, 'bio', 'COACH: profile-profile alignment of protein families using hidden Markov models', 'Edgar, Robert C|Sjölander, Kimmen', 'bob@drive5.com|bob@drive5.com', '-|-', 0, 'Algorithms|Amino Acid Sequence|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Molecular Sequence Data|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth091', '14962937', 'Alignments of two multiple-sequence alignments, or statistical models of such alignments (profiles), have important applications in computational biology. The increased amount of information in a profile versus a single sequence can lead to more accurate alignments and more sensitive homolog detection in database searches. Several profile-profile alignment methods have been proposed and have been shown to improve sensitivity and alignment quality compared with sequence-sequence methods (such as BLAST) and profile-sequence methods (e.g. PSI-BLAST). Here we present a new approach to profile-profile alignment we call Comparison of Alignments by Constructing Hidden Markov Models (HMMs) (COACH). COACH aligns two multiple sequence alignments by constructing a profile HMM from one alignment and aligning the other to that HMM.'),
(71167, 2004, 'bio', 'Modeling T-cell activation using gene expression profiling and state-space models', 'Rangel, Claudia|Angus, John|Ghahramani, Zoubin|Lioumi, Maria|Sotheran, Elizabeth|Gaiba, Alessia|Wild, David L|Falciani, Francesco', 'School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.|School of Mathematical Sciences, Claremont Graduate University, 121 E. Tenth St., Claremont, CA 91711, USA.', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Humans|Jurkat Cells|Lymphocyte Activation|Models, Immunological|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Systems Theory|T-Lymphocytes', 'Comparative Study', '10.1093/bioinformatics/bth093', '14962938', 'We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc.'),
(71168, 2004, 'bio', 'Site2genome: locating short DNA sequences in whole genomes', 'Frith, Martin C|Halees, Anason S|Hansen, Ulla|Weng, Zhiping', 'Bioinformatics Program, Boston University, MA 02215, USA.|Bioinformatics Program, Boston University, MA 02215, USA.|Bioinformatics Program, Boston University, MA 02215, USA.|Bioinformatics Program, Boston University, MA 02215, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|DNA|Genome|Internet|Oligonucleotides|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bth094', '14962939', 'Many biological papers describe short, functional DNA sites without specifying their exact positions in the genome. We have developed a Web server that automates the tedious task of locating such sites in eukaryotic genomes, thus giving access to the context of rich annotations that are increasingly available for genome sequences.'),
(71169, 2004, 'bio', 'A hint to search for metalloproteins in gene banks', 'Andreini, Claudia|Bertini, Ivano|Rosato, Antonio', 'Magnetic Resonance Center (CERM), University of Florence, Italy.|Magnetic Resonance Center (CERM), University of Florence, Italy.|Magnetic Resonance Center (CERM), University of Florence, Italy.', 'Italy|Italy|Italy', 0, 'Algorithms|Binding Sites|Copper|Databases, Protein|Drosophila Proteins|Genomics|Humans|Information Storage and Retrieval|Metalloproteins|Protein Binding|Protein Interaction Mapping|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Species Specificity', 'Comparative Study', '10.1093/bioinformatics/bth095', '14962940', 'With the advent of genome sequencing, a huge database of protein primary sequences has been accumulating. In parallel, a number of tools to investigate and expand upon this information, e.g. reconstructing and building relationships between protein families and superfamilies, have been developed. Metalloproteins are proteins capable of binding one or more metal ions, which are required for their biological function or for regulation of their activities or for structural purposes. Sometimes, metal binding can be observed in vitro but not be physiologically relevant. At present, there is a lack of specific tools to address the matter of the identification of metalloproteins in databases of gene sequences.'),
(71170, 2004, 'bio', 'ToPNet--an application for interactive analysis of expression data and biological networks', 'Hanisch, Daniel|Sohler, Florian|Zimmer, Ralf', 'Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, 53754 Sankt Augustin, Germany.|Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, 53754 Sankt Augustin, Germany.|Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, 53754 Sankt Augustin, Germany.', 'Germany|Germany|Germany', 9, 'Computer Graphics|Gene Expression Profiling|Internet|Models, Biological|Oligonucleotide Array Sequence Analysis|Protein Interaction Mapping|Signal Transduction|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth096', '14962941', 'ToPNet is a new tool for the combined visualization and exploration of gene networks and expression data. ToPNet provides various ways of restricting, manipulating and combining biological networks according to annotation data (e.g. Gene Ontology terms) and presents results to the user via different visualization procedures and hyperlinks to the underlying data sources. To easily identify relevant parts of the network, ToPNet provides a method of detecting significant subnetworks with respect to expression measurements. As ToPNet is a pure JAVA application with additional scripting capabilities, it is well-suited as a test-bed for algorithm development and exploratory biological data analysis alike.'),
(71171, 2004, 'bio', 'QDist--quartet distance between evolutionary trees', 'Mailund, Thomas|Pedersen, Christian N S', 'Bioinformatics Research Center (BiRC), University of Aarhus, Ny Munkegade, Building 540, DK-8000 Arhus C, Denmark. mailund@birc.dk|Bioinformatics Research Center (BiRC), University of Aarhus, Ny Munkegade, Building 540, DK-8000 Arhus C, Denmark. mailund@birc.dk', 'Denmark|Denmark', 0, 'Algorithms|Biological Evolution|Evolution, Molecular|Genetics, Population|Models, Genetic|Phylogeny|Sequence Analysis|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth097', '14962942', 'QDist is a program for computing the quartet distance between two unrooted trees, i.e. the number of quartet topology differences between the trees, where a quartet topology is the topological subtree induced by four species. The program is based on an algorithm with running time O(n log2 n), which makes it practical to compare large trees. Available under GNU license.'),
(71172, 2004, 'bio', 'Application of the GA/KNN method to SELDI proteomics data', 'Li, Leping|Umbach, David M|Terry, Paul|Taylor, Jack A', 'Biostatistics Branch, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709, USA. li3@niehs.nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709, USA. li3@niehs.nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709, USA. li3@niehs.nih.gov|Biostatistics Branch, National Institute of Environmental Health Sciences, National Institute of Health, Research Triangle Park, NC 27709, USA. li3@niehs.nih.gov', 'United States|United States|United States|United States', 0, 'Algorithms|Biomarkers|Female|Gene Expression Profiling|Humans|Neoplasm Proteins|Ovarian Neoplasms|Proteome|Proteomics|Reference Values|Reproducibility of Results|Sensitivity and Specificity|Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization', 'Comparative Study', '10.1093/bioinformatics/bth098', '14962943', 'Proteomics technology has shown promise in identifying biomarkers for disease, toxicant exposure and stress. We show by example that the genetic algorithm/k-nearest neighbors method, developed for mining high-dimensional microarray gene expression data, is also capable of mining surface enhanced laser desorption/ionization-time-of-flight proteomics data.'),
(71173, 2004, 'bio', 'Analysing microarray data using modular regulation analysis', 'Curtis, R Keira|Brand, Martin D', 'MRC Dunn Human Nutrition Unit, Hills Road, Cambridge, CB2 2XY, UK. rkc24@cam.ac.uk|MRC Dunn Human Nutrition Unit, Hills Road, Cambridge, CB2 2XY, UK. rkc24@cam.ac.uk', 'United Kingdom|United Kingdom', 5, 'Algorithms|Base Sequence|Cluster Analysis|Deoxyglucose|Galactose|Gene Expression Profiling|Gene Expression Regulation|Molecular Sequence Data|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|RNA, Messenger|Reproducibility of Results|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, RNA', 'Comparative Study', '10.1093/bioinformatics/bth082', '14976028', 'Microarray experiments measure complex changes in the abundance of many mRNAs under different conditions. Current analysis methods cannot distinguish between direct and indirect effects on expression, or calculate the relative importance of mRNAs in effecting responses.'),
(71174, 2004, 'bio', 'Prediction of Saccharomyces cerevisiae protein functional class from functional domain composition', 'Cai, Yu-Dong|Doig, Andrew J', 'Department of Biomolecular Sciences, UMIST, P.O. Box 88, Manchester M60 1QD, UK. y.cai@umist.ac.uk|Department of Biomolecular Sciences, UMIST, P.O. Box 88, Manchester M60 1QD, UK. y.cai@umist.ac.uk', 'United Kingdom|United Kingdom', 43, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computing Methodologies|Databases, Protein|Gene Expression Profiling|Pattern Recognition, Automated|Protein Structure, Tertiary|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/bth085', '14976029', 'A key goal of genomics is to assign function to genes, especially for orphan sequences.'),
(71175, 2004, 'bio', 'TANDEM: matching proteins with tandem mass spectra', 'Craig, Robertson|Beavis, Ronald C', 'Manitoba Centre for Proteomics, University of Manitoba, Winnipeg, MB, Canada R3T 2N2.|Manitoba Centre for Proteomics, University of Manitoba, Winnipeg, MB, Canada R3T 2N2.', 'Canada|Canada', 1782, 'Algorithms|Databases, Protein|Information Storage and Retrieval|Mass Spectrometry|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth092', '14976030', 'Tandem mass spectra obtained from fragmenting peptide ions contain some peptide sequence specific information, but often there is not enough information to sequence the original peptide completely. Several proprietary software applications have been developed to attempt to match the spectra with a list of protein sequences that may contain the sequence of the peptide. The application TANDEM was written to provide the proteomics research community with a set of components that can be used to test new methods and algorithms for performing this type of sequence-to-data matching.'),
(71176, 2004, 'bio', 'GeneSyn: a tool for detecting conserved gene order across genomes', 'Pavesi, G|Mauri, G|Iannelli, F|Gissi, C|Pesole, G', 'Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy.|Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy.|Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy.|Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy.|Dipartimento di Informatica, Sistemistica e Comunicazione, Università di Milano-Bicocca, via Bicocca degli Arcimboldi 8, 20126 Milano, Italy.', 'Italy|Italy|Italy|Italy|Italy', 0, 'Algorithms|Base Sequence|Chromosome Mapping|Conserved Sequence|Evolution, Molecular|Genome|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth102', '14976031', 'GeneSyn is a software tool that allows automatic detection of conserved gene order from annotated genomes.'),
(71177, 2004, 'bio', 'Spectral Repeat Finder (SRF): identification of repetitive sequences using Fourier transformation', 'Sharma, Deepak|Issac, Biju|Raghava, G P S|Ramaswamy, R', 'Department of Biotechnology, All India Institute of Medical Sciences, New Delhi 110029, India.|Department of Biotechnology, All India Institute of Medical Sciences, New Delhi 110029, India.|Department of Biotechnology, All India Institute of Medical Sciences, New Delhi 110029, India.|Department of Biotechnology, All India Institute of Medical Sciences, New Delhi 110029, India.', 'India|India|India|India', 127, 'Algorithms|DNA|Fourier Analysis|Pattern Recognition, Automated|Periodicity|Repetitive Sequences, Nucleic Acid|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth103', '14976032', 'Repetitive DNA sequences, besides having a variety of regulatory functions, are one of the principal causes of genomic instability. Understanding their origin and evolution is of fundamental importance for genome studies. The identification of repeats and their units helps in deducing the intra-genomic dynamics as an important feature of comparative genomics. A major difficulty in identification of repeats arises from the fact that the repeat units can be either exact or imperfect, in tandem or dispersed, and of unspecified length.'),
(71178, 2004, 'bio', 'Enhanced homology searching through genome reading frame predetermination', 'Yuan, Jeffrey|Bush, Bruce|Elbrecht, Alex|Liu, Yuan|Zhang, Theresa|Zhao, Wenqing|Blevins, Richard', 'Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com|Department of Bioinformatics, Merck & Co., Inc., P.O. Box 2000, RY80-A1, Rahway, NJ 07065, USA. jeffrey_yuan@merck.com', 'United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Amino Acid Sequence|Chromosome Mapping|Molecular Sequence Data|Open Reading Frames|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth115', '14976033', 'Many bioinformatic approaches exist for finding novel genes within genomic sequence data. Traditionally, homology search-based methods are often the first approach employed in determining whether a novel gene exists that is similar to a known gene. Unfortunately, distantly related genes or motifs often are difficult to find using single query-based homology search algorithms against large sequence datasets such as the human genome. Therefore, the motivation behind this work was to develop an approach to enhance the sensitivity of traditional single query-based homology algorithms against genomic data without losing search selectivity.'),
(71179, 2004, 'bio', 'galaxie--CGI scripts for sequence identification through automated phylogenetic analysis', 'Nilsson, R Henrik|Larsson, Karl-Henrik|Ursing, Björn M', 'Botanical Institute, Goteborg University, Box 461, 405 30 Goteborg, Sweden. henrik.nilsson@botany.gu.se|Botanical Institute, Goteborg University, Box 461, 405 30 Goteborg, Sweden. henrik.nilsson@botany.gu.se|Botanical Institute, Goteborg University, Box 461, 405 30 Goteborg, Sweden. henrik.nilsson@botany.gu.se', 'Sweden|Sweden|Sweden', 20, 'Algorithms|Computer Communication Networks|Database Management Systems|Databases, Genetic|Internet|Phylogeny|Programming Languages|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth119', '14976034', 'The prevalent use of similarity searches like BLAST to identify sequences and species implicitly assumes the reference database to be of extensive sequence sampling. This is often not the case, restraining the correctness of the outcome as a basis for sequence identification. Phylogenetic inference outperforms similarity searches in retrieving correct phylogenies and consequently sequence identities, and a project was initiated to design a freely available script package for sequence identification through automated Web-based phylogenetic analysis.'),
(71180, 2004, 'bio', 'Primer design using genetic algorithm', 'Wu, Jain-Shing|Lee, Chungnan|Wu, Chien-Chang|Shiue, Yow-Ling', 'Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. wujs@mail.cse.nsysu.edu|Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. wujs@mail.cse.nsysu.edu|Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. wujs@mail.cse.nsysu.edu|Department of Computer Science and Engineering, National Sun Yat-Sen University, Kaohsiung, Taiwan. wujs@mail.cse.nsysu.edu', '-|-|-|-', 6, 'Algorithms|Base Sequence|Computer Simulation|DNA Primers|Models, Genetic|Molecular Sequence Data|Polymerase Chain Reaction|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth147', '14988099', 'Before performing a polymerase chain reaction experiment, a pair of primers to clip the target DNA subsequence is required. However, this is a tedious task as too many constraints need to be satisfied. Various kinds of approaches for designing a primer have been proposed in the last few decades, but most of them do not have restriction sites on the designed primers and do not satisfy the specificity constraint.'),
(71181, 2004, 'bio', 'Haplotypes histories as pathways of recombinations', 'El-Mabrouk, Nadia|Labuda, Damian', 'Département dinformatique et de recherche opérationnelle, Université de Montréal, CP 6128 Succursale Centre-ville, Montréal, QC, Canada H3C 3J7. mabrouk@iro.montreal.ca|Département dinformatique et de recherche opérationnelle, Université de Montréal, CP 6128 Succursale Centre-ville, Montréal, QC, Canada H3C 3J7. mabrouk@iro.montreal.ca', 'Canada|Canada', 5, 'Algorithms|Chromosome Mapping|Genetic Variation|Genetics, Population|Haplotypes|Models, Genetic|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth148', '14988100', 'The diversity of a haplotype, represented as a string of polymorphic sites along a DNA sequence, increases exponentially with the number of sites if recombinations are taking place. Reconstructing the history of recombinations compared with that of the polymorphic sites is thus extremely difficult. However, in the human genome, because of the relatively simple pattern of haplotype diversity dominated by a few ancestral haplotypes, the complexity of the recombinational network can be reduced, thus making its reconstruction feasible. We focus on the problem of inferring the recombination pathways starting with putative ancestral haplotypes and leading to new rare recombinant haplotypes.'),
(71182, 2004, 'bio', 'Haplotype reconstruction from genotype data using Imperfect Phylogeny', 'Halperin, Eran|Eskin, Eleazar', 'CS Division, University of California Berkeley, Berkeley, CA 92093-0114, USA. eran@eecs.berkeley.edu|CS Division, University of California Berkeley, Berkeley, CA 92093-0114, USA. eran@eecs.berkeley.edu', 'United States|United States', 170, 'Algorithms|Chromosome Mapping|Genetic Variation|Genetics, Population|Genotype|Haplotypes|Models, Genetic|Phenotype|Phylogeny|Polymorphism, Single Nucleotide|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth149', '14988101', 'Critical to the understanding of the genetic basis for complex diseases is the modeling of human variation. Most of this variation can be characterized by single nucleotide polymorphisms (SNPs) which are mutations at a single nucleotide position. To characterize the genetic variation between different people, we must determine an individuals haplotype or which nucleotide base occurs at each position of these common SNPs for each chromosome. In this paper, we present results for a highly accurate method for haplotype resolution from genotype data. Our method leverages a new insight into the underlying structure of haplotypes that shows that SNPs are organized in highly correlated blocks. In a few recent studies, considerable parts of the human genome were partitioned into blocks, such that the majority of the sequenced genotypes have one of about four common haplotypes in each block. Our method partitions the SNPs into blocks, and for each block, we predict the common haplotypes and each individuals haplotype. We evaluate our method over biological data. Our method predicts the common haplotypes perfectly and has a very low error rate (<2% over the data) when taking into account the predictions for the uncommon haplotypes. Our method is extremely efficient compared with previous methods such as PHASE and HAPLOTYPER. Its efficiency allows us to find the block partition of the haplotypes, to cope with missing data and to work with large datasets.'),
(71183, 2004, 'bio', 'Structural exon database, SEDB, mapping exon boundaries on multiple protein structures', 'Leslin, Chesley M|Abyzov, Alex|Ilyin, Valentin A', 'Department of Biology, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA.|Department of Biology, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA.|Department of Biology, Northeastern University, 360 Huntington Avenue, Boston, MA 02115, USA.', 'United States|United States|United States', 7, 'Databases, Genetic|Exons|Internet|Models, Chemical|Online Systems|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth150', '14988102', 'Comparative analysis of exon/intron organization of genes and their resulting protein structures is important for understanding evolutionary relationships between species, rules of protein organization and protein functionality. We present Structural Exon Database (SEDB), with a Web interface, an application that allows users to retrieve the exon/intron organization of genes and map the location of the exon boundaries and the intron phase onto a multiple structural alignment. SEDB is linked with Friend, an integrated analytical multiple sequence/structure viewer, which allows simultaneous visualization of exon boundaries on structure and sequence alignments. With SEDB researchers can study the correlations of gene structure with the properties of the encoded three-dimensional protein structures across eukaryotic organisms.'),
(71184, 2004, 'bio', 'Sight: automating genomic data-mining without programming skills', 'Meskauskas, Audrius|Lehmann-Horn, Frank|Jurkat-Rott, Karin', 'Department of Applied Physiology, Ulm University, Albert-Einstein-Allee 11, D-89069 Ulm, Germany.|Department of Applied Physiology, Ulm University, Albert-Einstein-Allee 11, D-89069 Ulm, Germany.|Department of Applied Physiology, Ulm University, Albert-Einstein-Allee 11, D-89069 Ulm, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Computer Graphics|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Hypermedia|Information Storage and Retrieval|Internet|Online Systems|Programming Languages|Sequence Analysis|Software|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth151', '14988103', 'We created and tested Sight, a Java-based package that provides a user-friendly interface to generate and connect agents for automatic genomic data-mining for individual requirements without requiring programming skills from the user.'),
(71185, 2004, 'bio', 'An a posteriori strategy for enhancing gene discovery in anonymous cDNA microarray experiments', 'Anderssen, R S|Wu, Y|Dolferus, R|Saunders, I', 'CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT 2601, Australia. Bob.Anderssen@csiro.au|CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT 2601, Australia. Bob.Anderssen@csiro.au|CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT 2601, Australia. Bob.Anderssen@csiro.au|CSIRO Mathematical and Information Sciences, GPO Box 664, Canberra ACT 2601, Australia. Bob.Anderssen@csiro.au', 'Australia|Australia|Australia|Australia', 3, 'Algorithms|Gene Expression Profiling|Genetic Variation|In Situ Hybridization, Fluorescence|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sample Size|Sensitivity and Specificity|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth152', '14988104', 'Because of the high cost of sequencing, the bulk of gene discovery is performed using anonymous cDNA microarrays. Though the clones on such arrays are easier and cheaper to construct and utilize than unigene and oligonucleotide arrays, they are there in proportion to their corresponding gene expression activity in the tissue being examined. The associated redundancy will be there in any pool of possibly interesting differentially expressed clones identified in a microarray experiment for subsequent sequencing and investigation. An a posteriori sampling strategy is proposed to enhance gene discovery by reducing the impact of the redundancy in the identified pool.'),
(71186, 2004, 'bio', 'Multiple-sequence functional annotation and the generalized hidden Markov phylogeny', 'McAuliffe, Jon D|Pachter, Lior|Jordan, Michael I', 'Department of Statistics, University of California, 367 Evans Hall, Berkeley, CA 94720, USA.|Department of Statistics, University of California, 367 Evans Hall, Berkeley, CA 94720, USA.|Department of Statistics, University of California, 367 Evans Hall, Berkeley, CA 94720, USA.', 'United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Evolution, Molecular|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth153', '14988105', 'Phylogenetic shadowing is a comparative genomics principle that allows for the discovery of conserved regions in sequences from multiple closely related organisms. We develop a formal probabilistic framework for combining phylogenetic shadowing with feature-based functional annotation methods. The resulting model, a generalized hidden Markov phylogeny (GHMP), applies to a variety of situations where functional regions are to be inferred from evolutionary constraints.'),
(71187, 2004, 'bio', 'Genomic data visualization on the Web', 'Wu, Wei|Noble, William S', 'Department of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195, USA. weiw@u.washington.edu|Department of Genome Sciences, University of Washington, 1705 NE Pacific Street, Seattle, WA 98195, USA. weiw@u.washington.edu', 'United States|United States', 7, 'Computer Graphics|Database Management Systems|Documentation|Gene Expression Profiling|Genome|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|Online Systems|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth154', '14988106', 'Many types of genomic data can be represented in matrix format, with rows corresponding to genes and columns corresponding to gene features. The heat map is a popular technique for visualizing such data, plotting the data on a two-dimensional grid and using a color scale to represent the magnitude of each matrix entry. Prism is a Web-based software tool for generating annotated heat map visualizations of genome-wide data quickly. The tool provides a selection of genome-specific annotation catalogs as well as a catalog upload capability. The heat maps generated are clickable, allowing the user to drill down to examine specific matrix entries, and gene annotations are linked to relevant genomic databases.'),
(71188, 2004, 'bio', 'TOPALi: software for automatic identification of recombinant sequences within DNA multiple alignments', 'Milne, Iain|Wright, Frank|Rowe, Glenn|Marshall, David F|Husmeier, Dirk|McGuire, Gràinne', 'Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk|Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk|Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk|Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk|Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk|Biomathematics & Statistics Scotland, SCRI, Dundee, DD2 5DA, UK. topali@bioss.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 332, 'Computer Graphics|Gene Expression Profiling|Information Storage and Retrieval|Online Systems|Pattern Recognition, Automated|Phylogeny|Programming Languages|Recombination, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth155', '14988107', 'TOPALi is a new Java graphical analysis application that allows the user to identify recombinant sequences within a DNA multiple alignment (either automatically or via manual investigation). TOPALi allows a choice of three statistical methods to predict the positions of breakpoints due to past recombination. The breakpoint predictions are then used to identify putative recombinant sequences and their relationships to other sequences. In addition to its sophisticated interface, TOPALi can import many sequence formats, estimate and display phylogenetic trees and allow interactive analysis and/or automatic HTML report generation.'),
(71189, 2004, 'bio', 'FunMap: functional mapping of complex traits', 'Ma, Chang-Xing|Wu, Rongling|Casella, George', 'Department of Statistics, 533 McCarty Hall C, University of Florida, Gainesville, FL 32611, USA. cma@biostat.ufl.edu|Department of Statistics, 533 McCarty Hall C, University of Florida, Gainesville, FL 32611, USA. cma@biostat.ufl.edu|Department of Statistics, 533 McCarty Hall C, University of Florida, Gainesville, FL 32611, USA. cma@biostat.ufl.edu', 'United States|United States|United States', 0, 'Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Internet|Models, Genetic|Online Systems|Quantitative Trait Loci|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth156', '14988108', 'FunMap is a Web-based user interface designed to map quantitative trait loci (QTL) affecting function-valued traits or infinite-dimensional traits in well-structured pedigrees or natural populations. User input includes three files: longitudinal trait data, marker genotypes and/or a linkage map. This software allows for a systematic genome-wide scan and significance test of QTL throughout the map. The dynamic change of QTL effects during the time course of growth is automatically drawn, from which specific biological hypotheses regarding the genetic control mechanisms of growth and development can be tested.'),
(71190, 2004, 'bio', 'Second eigenvalue of the Laplacian matrix for predicting RNA conformational switch by mutation', 'Barash, Danny', 'Genome Diversity Center, Institute of Evolution, University of Haifa, Mount Carmel, Haifa 31905, Israel. dbarash@research.haifa.ac.il', 'Israel', 19, 'Algorithms|Computer Simulation|Models, Chemical|Models, Molecular|Mutation|Nucleic Acid Conformation|RNA|Sequence Alignment|Sequence Analysis, RNA|Software', 'Evaluation Studies', '10.1093/bioinformatics/bth157', '14988109', 'Conformational switching in RNAs is thought to be of fundamental importance in several biological processes, including translational regulation, regulation of self-cleavage in viruses, protein biosynthesis and mRNA splicing. Current methods for detecting bi-stable RNAs that can lead to structural switching when triggered by an outside event rely on kinetics, energetics and properties of the combinatorial structure space of RNAs. Based on these properties, tools have been developed to predict whether a given sequence folds to a structure characterized by a bi-stable conformation, or to design multi-stable RNAs by an iterative algorithm. A useful addition is in developing a local procedure to prescribe, given an initial sequence, the least amount of mutations needed to drive the system into an optimal bi-stable conformation.'),
(71191, 2004, 'bio', 'Robust PCA and classification in biosciences', 'Hubert, Mia|Engelen, Sanne', 'Department of Mathematics, Katholieke Universiteit Leuven, W. De Croylaan 54, B-3001 Leuven, Belgium. Mia.Hubert@wis.kuleuven.ac.be|Department of Mathematics, Katholieke Universiteit Leuven, W. De Croylaan 54, B-3001 Leuven, Belgium. Mia.Hubert@wis.kuleuven.ac.be', 'Belgium|Belgium', 0, 'Algorithms|Animals|Biological Science Disciplines|Computer Simulation|Gene Expression Profiling|Mice|Models, Genetic|Models, Statistical|Neoplasms|Oligonucleotide Array Sequence Analysis|Principal Component Analysis|Rats|Reproducibility of Results|Sensitivity and Specificity|Software', 'Comparative Study', '10.1093/bioinformatics/bth158', '14988110', 'Principal components analysis (PCA) is a very popular dimension reduction technique that is widely used as a first step in the analysis of high-dimensional microarray data. However, the classical approach that is based on the mean and the sample covariance matrix of the data is very sensitive to outliers. Also, classification methods based on this covariance matrix do not give good results in the presence of outlying measurements.'),
(71192, 2004, 'bio', 'Visualization for genomics: the Microbial Genome Viewer', 'Kerkhoven, Robert|van Enckevort, Frank H J|Boekhorst, Jos|Molenaar, Douwe|Siezen, Roland J', 'Centre for Molecular and Biomolecular Informatics, University of Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. R.Kerkhoven@cmbi.kun.nl|Centre for Molecular and Biomolecular Informatics, University of Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. R.Kerkhoven@cmbi.kun.nl|Centre for Molecular and Biomolecular Informatics, University of Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. R.Kerkhoven@cmbi.kun.nl|Centre for Molecular and Biomolecular Informatics, University of Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. R.Kerkhoven@cmbi.kun.nl|Centre for Molecular and Biomolecular Informatics, University of Nijmegen, P.O. Box 9010, 6500 GL Nijmegen, The Netherlands. R.Kerkhoven@cmbi.kun.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 64, 'Chromosome Mapping|Computer Graphics|Gene Expression Profiling|Genome, Bacterial|Genome, Fungal|Genomics|Information Storage and Retrieval|Internet|Online Systems|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth159', '14988111', 'A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a MySQL database. The generated images are in scalable vector graphics (SVG) format, which is suitable for creating high-quality scalable images and dynamic Web representations. Gene-related data such as transcriptome and time-course microarray experiments can be superimposed on the maps for visual inspection.'),
(71193, 2004, 'bio', 'Improving false discovery rate estimation', 'Pounds, Stan|Cheng, Cheng', 'Department of Biostatistics, MS 262 St Jude Childrens Research Hospital, 332 N. Lauderdale Street, Memphis, TN 38105-2794, USA. stanley.pounds@stjude.org|Department of Biostatistics, MS 262 St Jude Childrens Research Hospital, 332 N. Lauderdale Street, Memphis, TN 38105-2794, USA. stanley.pounds@stjude.org', 'United States|United States', 108, 'Algorithms|Benchmarking|Computer Simulation|False Positive Reactions|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Quality Control|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth160', '14988112', 'Recent attempts to account for multiple testing in the analysis of microarray data have focused on controlling the false discovery rate (FDR). However, rigorous control of the FDR at a preselected level is often impractical. Consequently, it has been suggested to use the q-value as an estimate of the proportion of false discoveries among a set of significant findings. However, such an interpretation of the q-value may be unwarranted considering that the q-value is based on an unstable estimator of the positive FDR (pFDR). Another method proposes estimating the FDR by modeling p-values as arising from a beta-uniform mixture (BUM) distribution. Unfortunately, the BUM approach is reliable only in settings where the assumed model accurately represents the actual distribution of p-values.'),
(71194, 2004, 'bio', 'GenAlyzer: interactive visualization of sequence similarities between entire genomes', 'Choudhuri, Jomuna V|Schleiermacher, Chris|Kurtz, Stefan|Giegerich, Robert', 'Faculty of Technology, University of Bielefeld, P.O. Box 100131, 33501 Bielefeld, Germany.|Faculty of Technology, University of Bielefeld, P.O. Box 100131, 33501 Bielefeld, Germany.|Faculty of Technology, University of Bielefeld, P.O. Box 100131, 33501 Bielefeld, Germany.|Faculty of Technology, University of Bielefeld, P.O. Box 100131, 33501 Bielefeld, Germany.', 'Germany|Germany|Germany|Germany', 18, 'Algorithms|Chromosome Mapping|Computer Graphics|Conserved Sequence|Internet|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth161', '14988113', 'Genalyzer is a software tool designed for the interactive visualization of sequence matches between DNA or protein sequences. It provides visualizations on different levels of granularity, from complete overviews via zoomed regions to alignments of particular matching substrings. Genalyzer can efficiently handle very large datasets, allowing to display tens of thousands of matches between sequences of tens of millions of bases.'),
(71195, 2004, 'bio', 'Harvester: a fast meta search engine of human protein resources', 'Liebel, Urban|Kindler, Bjoern|Pepperkok, Rainer', 'Cell Biology and Cell Biophysics Programme, European Molecular Biology Laboratory, Heidelberg, Germany.|Cell Biology and Cell Biophysics Programme, European Molecular Biology Laboratory, Heidelberg, Germany.|Cell Biology and Cell Biophysics Programme, European Molecular Biology Laboratory, Heidelberg, Germany.', 'Germany|Germany|Germany', 29, 'Database Management Systems|Databases, Protein|Documentation|Humans|Information Storage and Retrieval|Internet|Natural Language Processing|Proteins|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth146', '14988114', 'We have developed a Web-based tool named Harvester that bulk-collects bioinformatic data on human proteins from various databases and prediction servers. The information on every single protein is assembled on a single HTML page as a combination of database screen-shots and plain text. A full text meta search engine, similar to Google trade mark, allows screening of the whole genome proteome for current protein functions and predictions in a few seconds. With Harvester it is now possible to compare and check the quality of different database entries and prediction algorithms on a single page. A feedback forum allows users to comment on Harvester and to report database inconsistencies.'),
(71196, 2004, 'bio', 'PartiGene--constructing partial genomes', 'Parkinson, John|Anthony, Alasdair|Wasmuth, James|Schmid, Ralf|Hedley, Ann|Blaxter, Mark', 'School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca|School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca|School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca|School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca|School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca|School of Biological Sciences, Ashworth Laboratories, Kings Buildings, West Mains Rd, University of Edinburgh, Edinburgh EH9 3JT, UK. jparkin@sickkids.ca', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 124, 'Chromatography|Chromosome Mapping|Databases, Nucleic Acid|Expressed Sequence Tags|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth101', '14988115', 'Expressed sequence tags (ESTs) offer a low-cost approach to gene discovery and are being used by an increasing number of laboratories to obtain sequence information for a wide variety of organisms. The challenge lies in processing and organizing this data within a genomic context to facilitate large scale analyses. Here we present PartiGene, an integrated sequence analysis suite that uses freely available public domain software to (1) process raw trace chromatograms into sequence objects suitable for submission to dbEST, (2) place these sequences within a genomic context, (3) perform customizable first-pass annotation of the data, and (4) present the data as HTML tables and an SQL database resource. PartiGene has been used to create a number of non-model organism database resources including NEMBASE (http://www.nematodes.org) and LumbriBase (http://www.earthworms.org/). The packages are readily portable, freely available and can be run on simple Linux-based workstations.'),
(71197, 2004, 'bio', 'SeqExpress: desktop analysis and visualization tool for gene expression experiments', 'Boyle, John', 'Holbeck, George Street, Cambridge CB4 1AJ, UK. john@seqexpress.com', 'United Kingdom', 5, 'Algorithms|Gene Expression Profiling|Information Storage and Retrieval|Microcomputers|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth123', '14988116', 'SeqExpress is a stand-alone desktop application for the identification of relevant genes within collections of microarray or SAGE experiments. A number of analysis, filtering and visualization tools are provided to aid in the selection of groups of genes. If R is installed then the application can use this to provide further analysis.'),
(71198, 2004, 'bio', 'Protein secondary structure: entropy, correlations and prediction', 'Crooks, Gavin E|Brenner, Steven E', 'Department of Plant and Microbial Biology, University of California, 111 Koshland Hall No. 3102, Berkeley, CA 94720-3102, USA. gec@compbio.berkeley.edu|Department of Plant and Microbial Biology, University of California, 111 Koshland Hall No. 3102, Berkeley, CA 94720-3102, USA. gec@compbio.berkeley.edu', 'United States|United States', 57, 'Algorithms|Amino Acid Sequence|Computer Simulation|Entropy|Markov Chains|Models, Chemical|Models, Molecular|Models, Statistical|Molecular Sequence Data|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Statistics as Topic', 'Evaluation Studies', '10.1093/bioinformatics/bth132', '14988117', 'Is protein secondary structure primarily determined by local interactions between residues closely spaced along the amino acid backbone or by non-local tertiary interactions? To answer this question, we measure the entropy densities of primary and secondary structure sequences, and the local inter-sequence mutual information density.'),
(71199, 2004, 'bio', 'matchprobes: a Bioconductor package for the sequence-matching of microarray probe elements', 'Huber, Wolfgang|Gentleman, Robert', 'Department of Molecular Genome Analysis, German Cancer Research Center, INF 580, Heidelberg, 69120, Germany. w.huber@dkfz.de|Department of Molecular Genome Analysis, German Cancer Research Center, INF 580, Heidelberg, 69120, Germany. w.huber@dkfz.de', 'Germany|Germany', 33, 'Algorithms|DNA Probes|Information Storage and Retrieval|Oligonucleotide Array Sequence Analysis|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Journal Article', '10.1093/bioinformatics/bth133', '14988118', 'The nucleotide sequences of the probes on a microarray can be used for a variety of purposes in the analysis of microarray experiments. We describe software and a paradigm for the creation of data packages for curating, distributing and working with probe sequence data in a uniform, across-types-of-microarrays manner. While the implementation is specific to the Bioconductor project, the ideas and general strategies are more general and could be easily adopted by other projects.'),
(71200, 2004, 'bio', 'Common structural patterns in human genes', 'Hill, Aubrey|Sorscher, Eric', 'Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294-0005, USA. ahill@uab.edu|Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294-0005, USA. ahill@uab.edu', 'United States|United States', 4, 'Algorithms|Chromosome Mapping|Conserved Sequence|Exons|Gene Expression Profiling|Genome, Human|Humans|Introns|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth134', '14988119', 'A graphical representation of the exon-intron structure of various genes, such as that presented by the National Center for Biotechnology Information Map Viewer, suggests a digital waveform or pattern that varies either in amplitude or frequency. This observation suggests that different genes may have portions of their total exon-intron structure in common. The existence of common structural patterns across unrelated genes suggests the repeated insertion of transposable elements throughout the human genome and/or a common structural function.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71201, 2004, 'bio', 'Mathematical characterization of three-dimensional gene expression patterns', 'Costa, L da F|Barbosa, M S|Manoel, E T M|Streicher, J|Müller, G B', 'Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br|Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br|Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br|Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br|Cybernetic Vision Research Group, GII-IFSC, Universidade de São Paulo, São Carlos, SP, Caixa Postal 369, 13560-970, Brazil. luciano@if.sc.usp.br', 'Brazil|Brazil|Brazil|Brazil|Brazil', 9, 'Animals|Culture Techniques|DNA-Binding Proteins|Embryo, Mammalian|Fractals|Gene Expression Profiling|Gene Expression Regulation|Image Interpretation, Computer-Assisted|Imaging, Three-Dimensional|In Situ Hybridization, Fluorescence|Mice|Microscopy, Fluorescence|Muscle Proteins|Myogenic Regulatory Factor 5|Numerical Analysis, Computer-Assisted|Pattern Recognition, Automated|Tissue Distribution|Trans-Activators|Transcriptional Activation', 'Comparative Study', '10.1093/bioinformatics/bth135', '14988120', 'The importance of a systematic methodology for the mathematical characterization of three-dimensional gene expression patterns in embryonic development.'),
(71202, 2004, 'bio', 'Protein backbone angle prediction with machine learning approaches', 'Kuang, Rui|Leslie, Christina S|Yang, An-Suei', 'Department of Computer Science, Columbia University, New York, NY 10032, USA.|Department of Computer Science, Columbia University, New York, NY 10032, USA.|Department of Computer Science, Columbia University, New York, NY 10032, USA.', 'United States|United States|United States', 57, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computer Simulation|Models, Chemical|Models, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Protein Conformation|Protein Structure, Secondary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bth136', '14988121', 'Protein backbone torsion angle prediction provides useful local structural information that goes beyond conventional three-state (alpha, beta and coil) secondary structure predictions. Accurate prediction of protein backbone torsion angles will substantially improve modeling procedures for local structures of protein sequence segments, especially in modeling loop conformations that do not form regular structures as in alpha-helices or beta-strands.'),
(71203, 2004, 'bio', 'Development of joint application strategies for two microbial gene finders', 'McHardy, Alice C|Goesmann, Alexander|Pühler, Alfred|Meyer, Folker', 'Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.|Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.|Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.|Center for Biotechnology (CeBiTec), Bielefeld University, Bielefeld, Germany.', 'Germany|Germany|Germany|Germany', 63, 'Algorithms|DNA, Bacterial|Gene Expression Profiling|Genome, Bacterial|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth137', '14988122', 'As a starting point in annotation of bacterial genomes, gene finding programs are used for the prediction of functional elements in the DNA sequence. Due to the faster pace and increasing number of genome projects currently underway, it is becoming especially important to have performant methods for this task.'),
(71204, 2004, 'bio', 'GeneCluster 20: an advanced toolset for bioarray analysis', 'Reich, M|Ohm, K|Angelo, M|Tamayo, P|Mesirov, J P', 'The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA.|The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA.|The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA.|The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA.|The Eli and Edythe L. Broad Institute, Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02141, USA.', 'United States|United States|United States|United States|United States', 76, 'Algorithms|Cluster Analysis|Computer Graphics|DNA|Gene Expression Profiling|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth138', '14988123', 'GeneCluster 2.0 is a software package for analyzing gene expression and other bioarray data, giving users a variety of methods to build and evaluate class predictors, visualize marker lists, cluster data and validate results. GeneCluster 2.0 greatly expands the data analysis capabilities of GeneCluster 1.0 by adding classification, class discovery and permutation test methods. It includes algorithms for building and testing supervised models using weighted voting and k-nearest neighbor algorithms, a module for systematically finding and evaluating clustering via self-organizing maps, and modules for marker gene selection and heat map visualization that allow users to view and sort samples and genes by many criteria. GeneCluster 2.0 is a stand-alone Java application and runs on any platform that supports the Java Runtime Environment version 1.3.1 or greater.'),
(71205, 2004, 'bio', 'Mixture models for assessing differential expression in complex tissues using microarray data', 'Ghosh, Debashis', 'Department of Biostatistics, School of Public Health, University of Michigan, 1420 Washington Heights, Ann Arbor, MI 48109-2029, USA. ghoshd@umich.edu', 'United States', 43, 'Algorithms|Coculture Techniques|Colonic Neoplasms|Culture Techniques|Diagnosis, Computer-Assisted|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth139', '14988124', 'The use of DNA microarrays has become quite popular in many scientific and medical disciplines, such as in cancer research. One common goal of these studies is to determine which genes are differentially expressed between cancer and healthy tissue, or more generally, between two experimental conditions. A major complication in the molecular profiling of tumors using gene expression data is that the data represent a combination of tumor and normal cells. Much of the methodology developed for assessing differential expression with microarray data has assumed that tissue samples are homogeneous.'),
(71206, 2004, 'bio', 'Decoupling dynamical systems for pathway identification from metabolic profiles', 'Voit, Eberhard O|Almeida, Jonas', 'Department of Biometry and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. Voiteo@musc.edu|Department of Biometry and Epidemiology, Medical University of South Carolina, Charleston, SC 29425, USA. Voiteo@musc.edu', 'United States|United States', 246, 'Algorithms|Artificial Intelligence|Computer Simulation|Kinetics|Metabolism|Models, Biological|Neural Networks (Computer)|Numerical Analysis, Computer-Assisted|Proteome|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth140', '14988125', 'Modern molecular biology is generating data of unprecedented quantity and quality. Particularly exciting for biochemical pathway modeling and proteomics are comprehensive, time-dense profiles of metabolites or proteins that are measurable, for instance, with mass spectrometry, nuclear magnetic resonance or protein kinase phosphorylation. These profiles contain a wealth of information about the structure and dynamics of the pathway or network from which the data were obtained. The retrieval of this information requires a combination of computational methods and mathematical models, which are typically represented as systems of ordinary differential equations.'),
(71207, 2004, 'bio', 'Protein homology detection using string alignment kernels', 'Saigo, Hiroto|Vert, Jean-Philippe|Ueda, Nobuhisa|Akutsu, Tatsuya', 'Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Japan.|Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611-0011, Japan.', 'Japan|Japan|Japan|Japan', 273, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computing Methodologies|Molecular Sequence Data|Pattern Recognition, Automated|Protein Structure, Tertiary|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth141', '14988126', 'Remote homology detection between protein sequences is a central problem in computational biology. Discriminative methods involving support vector machines (SVMs) are currently the most effective methods for the problem of superfamily recognition in the Structural Classification Of Proteins (SCOP) database. The performance of SVMs depends critically on the kernel function used to quantify the similarity between sequences.'),
(71208, 2004, 'bio', 'Fuzzy J-Means and VNS methods for clustering genes from microarray data', 'Belacel, Nabil|Cuperlovixc4x87-Culf, Miroslava|Laflamme, Mark|Ouellette, Rodney', 'National Research Council Canada, Institute for Information Technology-e-Health group, 127 Carleton Street, St-John, NB, Canada E2L2Z6. Nabil.Belacel@nrc-cnrc.gc.ca|National Research Council Canada, Institute for Information Technology-e-Health group, 127 Carleton Street, St-John, NB, Canada E2L2Z6. Nabil.Belacel@nrc-cnrc.gc.ca|National Research Council Canada, Institute for Information Technology-e-Health group, 127 Carleton Street, St-John, NB, Canada E2L2Z6. Nabil.Belacel@nrc-cnrc.gc.ca|National Research Council Canada, Institute for Information Technology-e-Health group, 127 Carleton Street, St-John, NB, Canada E2L2Z6. Nabil.Belacel@nrc-cnrc.gc.ca', 'Canada|Canada|Canada|Canada', 51, 'Algorithms|Blood Proteins|Breast Neoplasms|Cluster Analysis|Computer Simulation|Fuzzy Logic|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Genetic Testing|Genetic Variation|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth142', '14988127', 'In the interpretation of gene expression data from a group of microarray experiments that include samples from either different patients or conditions, special consideration must be given to the pleiotropic and epistatic roles of genes, as observed in the variation of gene coexpression patterns. Crisp clustering methods assign each gene to one cluster, thereby omitting information about the multiple roles of genes.'),
(71209, 2004, 'bio', 'A knowledge-based scale for the analysis and prediction of buried and exposed faces of transmembrane domain proteins', 'Beuming, Thijs|Weinstein, Harel', 'Department of Physiology and Biophysics, Mount Sinai School of Medicine, New York, NY 10029, USA.|Department of Physiology and Biophysics, Mount Sinai School of Medicine, New York, NY 10029, USA.', 'United States|United States', 60, 'Algorithms|Amino Acids|Artificial Intelligence|Cell Membrane|Membrane Lipids|Membrane Proteins|Models, Chemical|Models, Statistical|Protein Conformation|Protein Structure, Secondary|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth143', '14988128', 'The dearth of structural data on alpha-helical membrane proteins (MPs) has hampered thus far the development of reliable knowledge-based potentials that can be used for automatic prediction of transmembrane (TM) protein structure. While algorithms for identifying TM segments are available, modeling of the TM domains of alpha-helical MPs involves assembling the segments into a bundle. This requires the correct assignment of the buried and lipid-exposed faces of the TM domains.'),
(71210, 2004, 'bio', 'Why neural networks should not be used for HIV-1 protease cleavage site prediction', 'Rögnvaldsson, Thorsteinn|You, Liwen', 'Intelligent Systems Laboratory, School of Information Science, Computer and Electrical Engineering, Halmstad University, Box 823, 301 18 Sweden. denni@ide.hh.se|Intelligent Systems Laboratory, School of Information Science, Computer and Electrical Engineering, Halmstad University, Box 823, 301 18 Sweden. denni@ide.hh.se', 'Sweden|Sweden', 0, 'Algorithms|Artificial Intelligence|Binding Sites|Computer Simulation|Databases, Protein|Enzyme Activation|HIV Protease|Linear Models|Models, Chemical|Neural Networks (Computer)|Nonlinear Dynamics|Pattern Recognition, Automated|Protein Binding|Protein Interaction Mapping|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth144', '14988129', 'Several papers have been published where nonlinear machine learning algorithms, e.g. artificial neural networks, support vector machines and decision trees, have been used to model the specificity of the HIV-1 protease and extract specificity rules. We show that the dataset used in these studies is linearly separable and that it is a misuse of nonlinear classifiers to apply them to this problem. The best solution on this dataset is achieved using a linear classifier like the simple perceptron or the linear support vector machine, and it is straightforward to extract rules from these linear models. We identify key residues in peptides that are efficiently cleaved by the HIV-1 protease and list the most prominent rules, relating them to experimental results for the HIV-1 protease.'),
(71211, 2004, 'bio', 'HMMGEP: clustering gene expression data using hidden Markov models', 'Ji, Xinglai|Yuan, Yuan|Li-Ling, Jesse|Li, Yanda|Sun, Zhirong', 'Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China.|Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China.|Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China.|Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China.|Institute of Bioinformatics, Tsinghua University, Beijing 100084, Peoples Republic of China.', 'China|China|China|China|China', 0, 'Algorithms|Cluster Analysis|Computer Graphics|DNA|Gene Expression Profiling|Markov Chains|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bth145', '14988130', 'The package HMMGEP performs cluster analysis on gene expression data using hidden Markov models.'),
(71212, 2004, 'bio', 'Translational polymorphism as a potential source of plant proteins variety in Arabidopsis thaliana', 'Kochetov, Alex V|Sarai, Akinori', 'Institute of Cytology and Genetics, Pr. Lavrentieva 10, Novosibirsk 630090, Russia. Alex.Kochetov@bionet.nsc.ru|Institute of Cytology and Genetics, Pr. Lavrentieva 10, Novosibirsk 630090, Russia. Alex.Kochetov@bionet.nsc.ru', '-|-', 0, 'Arabidopsis|Arabidopsis Proteins|Cellular Structures|Gene Expression Profiling|Gene Expression Regulation, Plant|Gene Frequency|Genetic Variation|Polymorphism, Genetic|Protein Biosynthesis|Proteome|RNA, Messenger|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/btg443', '14990439', 'According to scanning model, 40S ribosomal subunits can either initiate translation at start AUG codon in suboptimal context or miss it and initiate translation at downstream AUG(s), thereby producing several proteins. Functional significance of such a protein translational polymorphism is still unknown.'),
(71213, 2004, 'bio', 'A simple fold with variations: the pacifastin inhibitor family', 'Gáspári, Zoltán|Ortutay, Csaba|Perczel, András', 'Department of Organic Chemistry, Eötvös University, Pázmány Péter sétány 1/A, Budapest, Hungary. szpari@para.chem.elte.hu|Department of Organic Chemistry, Eötvös University, Pázmány Péter sétány 1/A, Budapest, Hungary. szpari@para.chem.elte.hu|Department of Organic Chemistry, Eötvös University, Pázmány Péter sétány 1/A, Budapest, Hungary. szpari@para.chem.elte.hu', 'Hungary|Hungary|Hungary', 14, 'Binding Sites|Computer Simulation|Expressed Sequence Tags|Models, Molecular|Phylogeny|Protein Binding|Protein Conformation|Protein Folding|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Serine Proteinase Inhibitors|Species Specificity|Structure-Activity Relationship', 'Comparative Study', '10.1093/bioinformatics/btg451', '14990440', 'Members of the pacifastin family are small, approximately 35-residue serine protease inhibitors isolated from arthropod species. Several locust inhibitors exhibit intriguing taxon specificity while others do not. The structural basis of this phenomenon may lie in the different dynamical properties of the proteins originating from different stabilizing interactions. In this study, we identify new members of the family to confirm the universal role of these interactions in the family. Structural investigations show that both the disulfide pattern and the stabilizing interactions are unique among small all-beta proteins.'),
(71214, 2004, 'bio', 'RAD and the RAD Study-Annotator: an approach to collection, organization and exchange of all relevant information for high-throughput gene expression studies', 'Manduchi, E|Grant, G R|He, H|Liu, J|Mailman, M D|Pizarro, A D|Whetzel, P L|Stoeckert, C J', 'Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu|Center for Bioinformatics, University of Pennsylvania, 14th Floor Blockley Hall, 423 Guardian Drive, Philadelphia, PA 19104-6021, USA. manduchi@pcbi.upenn.edu', 'United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Abstracting and Indexing as Topic|Database Management Systems|Databases, Nucleic Acid|Documentation|Gene Expression Profiling|Information Storage and Retrieval|Internet|Oligonucleotide Array Sequence Analysis|RNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg428', '14990441', 'Gene expression array technology has become increasingly widespread among researchers who recognize its numerous promises. At the same time, bench biologists and bioinformaticians have come to appreciate increasingly the importance of establishing a collaborative dialog from the onset of a study and of collecting and exchanging detailed information on the many experimental and computational procedures using a structured mechanism. This is crucial for adequate analyses of this kind of data.'),
(71215, 2004, 'bio', 'Mismatch string kernels for discriminative protein classification', 'Leslie, Christina S|Eskin, Eleazar|Cohen, Adiel|Weston, Jason|Noble, William Stafford', 'Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, Mail Code 0401, New York, NY 10027, USA. cleslie@cs.columbia.edu|Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, Mail Code 0401, New York, NY 10027, USA. cleslie@cs.columbia.edu|Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, Mail Code 0401, New York, NY 10027, USA. cleslie@cs.columbia.edu|Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, Mail Code 0401, New York, NY 10027, USA. cleslie@cs.columbia.edu|Department of Computer Science, Columbia University, 1214 Amsterdam Avenue, Mail Code 0401, New York, NY 10027, USA. cleslie@cs.columbia.edu', 'United States|United States|United States|United States|United States', 391, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Molecular Sequence Data|Nuclear Proteins|Pattern Recognition, Automated|Phosphoprotein Phosphatases|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg431', '14990442', 'Classification of proteins sequences into functional and structural families based on sequence homology is a central problem in computational biology. Discriminative supervised machine learning approaches provide good performance, but simplicity and computational efficiency of training and prediction are also important concerns.'),
(71216, 2004, 'bio', 'Analysis and prediction of DNA-binding proteins and their binding residues based on composition, sequence and structural information', 'Ahmad, Shandar|Gromiha, M Michael|Sarai, Akinori', 'Department of Biochemical Science and Engineering, Kyushu Institute of Technology, Fukuoka, Iizuka 820 8502, Japan. shandar@bse.kyutech.ac.jp|Department of Biochemical Science and Engineering, Kyushu Institute of Technology, Fukuoka, Iizuka 820 8502, Japan. shandar@bse.kyutech.ac.jp|Department of Biochemical Science and Engineering, Kyushu Institute of Technology, Fukuoka, Iizuka 820 8502, Japan. shandar@bse.kyutech.ac.jp', 'Japan|Japan|Japan', 0, 'Algorithms|Amino Acid Sequence|Amino Acids|Artificial Intelligence|Binding Sites|Computer Simulation|DNA|DNA-Binding Proteins|Models, Chemical|Models, Molecular|Molecular Sequence Data|Neural Networks (Computer)|Protein Binding|Protein Structure, Secondary|Protein Structure, Tertiary|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/btg432', '14990443', 'Though vitally important to cell function, the mechanism of protein-DNA binding has not yet been completely understood. We therefore analysed the relationship between DNA binding and protein sequence composition, solvent accessibility and secondary structure. Using non-redundant databases of transcription factors and protein-DNA complexes, neural network models were developed to utilize the information present in this relationship to predict DNA-binding proteins and their binding residues.'),
(71217, 2004, 'bio', 'Inverse modeling using multi-block PLS to determine the environmental conditions that provide optimal cellular function', 'Hwang, Daehee|Stephanopoulos, George|Chan, Christina', 'Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge MA 02139, USA.|Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge MA 02139, USA.', 'United States|United States|United States', 21, 'Amino Acids|Animals|Cell Culture Techniques|Cell Division|Cells, Cultured|Combinatorial Chemistry Techniques|Computer Simulation|Environment Design|Environment, Controlled|Hepatocytes|Hormones|Humans|Insulin|Least-Squares Analysis|Lipid Metabolism|Models, Biological|Models, Statistical|Tissue Engineering|Urea', 'Comparative Study', '10.1093/bioinformatics/btg433', '14990444', 'Tissue engineering constitutes an important field with its potential of addressing the current shortage in organ availability. To successfully develop tissue-engineered organs, it is crucial to understand how to maintain the cells under conditions that maximize their ability to perform their physiological roles, regardless of the environment, whether the cells are part of an extracorporeal system, such as the bioartificial liver assist device, or an implantable tissue-engineered device. Our goals are to (1) provide insight into how cells will behave when confronted with changes in its environment and (2) determine the optimal environmental factors to achieve a desired level of cellular function.'),
(71218, 2004, 'bio', 'Comparison of Li-Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays', 'Chu, Tzu-Ming|Weir, B S|Wolfinger, Russell D', 'Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA. tzu-ming.ch@sas.com|Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA. tzu-ming.ch@sas.com|Department of Statistics, North Carolina State University, Raleigh, NC 27695, USA. tzu-ming.ch@sas.com', 'United States|United States|United States', 16, 'Algorithms|Computer Simulation|DNA|Gene Expression Profiling|Linear Models|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg435', '14990445', 'Li and Wong have described some useful statistical models for probe-level, oligonucleotide array data based on a multiplicative parametrization. In earlier work, we proposed similar analysis-of-variance-style mixed models fit on a log scale. With only subtle differences in the specification of their mean and stochastic error components, a question arises as to whether these models could lead to varying conclusions in practical application.'),
(71219, 2004, 'bio', 'Tailored gene array databases: applications in mechanistic toxicology', 'Karpinets, Tatiana V|Foy, Brent D|Frazier, John M', 'Department of Physics, Wright State University, 3640 Colonel Glenn Hwy, Dayton, OH 45435, USA.|Department of Physics, Wright State University, 3640 Colonel Glenn Hwy, Dayton, OH 45435, USA.|Department of Physics, Wright State University, 3640 Colonel Glenn Hwy, Dayton, OH 45435, USA.', 'United States|United States|United States', 14, 'Abstracting and Indexing as Topic|Animals|Database Management Systems|Databases, Factual|Databases, Genetic|Documentation|Gene Expression Profiling|Humans|Hydrazines|Information Storage and Retrieval|Liver|Natural Language Processing|Oligonucleotide Array Sequence Analysis|Toxicogenetics|Toxicology', 'Evaluation Studies', '10.1093/bioinformatics/btg436', '14990446', 'The development of an annotated global database suitable for a wide range of investigations is a challenging and labor-intensive task. Thus, the development of databases tailored for specific applications remains necessary. For example, in the field of toxicology, no annotated gene array databases are now available that may assist in the correlation of changes in gene activity to cellular functions and processes associated with the toxic response.'),
(71220, 2004, 'bio', 'Reducing the variability in cDNA microarray image processing by Bayesian inference', 'Lawrence, Neil D|Milo, Marta|Niranjan, Mahesan|Rashbass, Penny|Soullier, Stephan', 'Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. neil@dcs.shef.ac.uk|Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. neil@dcs.shef.ac.uk|Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. neil@dcs.shef.ac.uk|Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. neil@dcs.shef.ac.uk|Department of Computer Science, Regent Court, 211 Portobello Road, Sheffield, S1 4DP, UK. neil@dcs.shef.ac.uk', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Artifacts|Bayes Theorem|Gene Expression Profiling|Genetic Variation|Image Enhancement|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Observer Variation|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg438', '14990447', 'Gene expression levels are obtained from microarray experiments through the extraction of pixel intensities from a scanned image of the slide. It is widely acknowledged that variabilities can occur in expression levels extracted from the same images by different users with the same software packages. These inconsistencies arise due to differences in the refinement of the placement of the microarray grids. We introduce a novel automated approach to the refinement of grid placements that is based upon the use of Bayesian inference for determining the size, shape and positioning of the microarray spots, capturing uncertainty that can be passed to downstream analysis.'),
(71221, 2004, 'bio', 'SaRAD: a Simple and Robust Abbreviation Dictionary', 'Adar, Eytan', 'HP Laboratories, 1501 Page Mill Rd, Palo Alto, CA 94304, USA. eytan@hpl.hp.com', 'United States', 47, 'Abbreviations as Topic|Algorithms|Cluster Analysis|Database Management Systems|Databases, Bibliographic|Databases, Factual|Dictionaries, Medical as Topic|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Software|Software Validation|Terminology as Topic|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg439', '14990448', 'Due to recent interest in the use of textual material to augment traditional experiments it has become necessary to automatically cluster, classify and filter natural language information.'),
(71222, 2004, 'bio', 'Fundamentals of massive automatic pairwise alignments of protein sequences: theoretical significance of Z-value statistics', 'Bastien, Olivier|Aude, Jean-Christophe|Roy, Sylvaine|Maréchal, Eric', 'Laboratoire de Physiologie Cellulaire Végétale, Département Réponse et Dynamique Cellulaire, UMR 5168 CNRS-CEA-INRA-Université J. Fourier, CEA Grenoble, 17 rue des Martyrs, F-38054, Grenoble cedex 09, France.|Laboratoire de Physiologie Cellulaire Végétale, Département Réponse et Dynamique Cellulaire, UMR 5168 CNRS-CEA-INRA-Université J. Fourier, CEA Grenoble, 17 rue des Martyrs, F-38054, Grenoble cedex 09, France.|Laboratoire de Physiologie Cellulaire Végétale, Département Réponse et Dynamique Cellulaire, UMR 5168 CNRS-CEA-INRA-Université J. Fourier, CEA Grenoble, 17 rue des Martyrs, F-38054, Grenoble cedex 09, France.|Laboratoire de Physiologie Cellulaire Végétale, Département Réponse et Dynamique Cellulaire, UMR 5168 CNRS-CEA-INRA-Université J. Fourier, CEA Grenoble, 17 rue des Martyrs, F-38054, Grenoble cedex 09, France.', 'France|France|France|France', 27, 'Algorithms|Amino Acid Sequence|Amino Acids|Cluster Analysis|Data Interpretation, Statistical|Molecular Sequence Data|Proteins|Quality Control|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/btg440', '14990449', 'Different automatic methods of sequence alignments are routinely used as a starting point for homology searches and function inference. Confidence in an alignment probability is one of the major fundamentals of massive automatic genome-scale pairwise comparisons, for clustering of putative orthologs and paralogs, sequenced genome annotation or multiple-genomic tree constructions. Extreme value distribution based on the Karlin-Altschul model, usually advised for large-scale comparisons are not always valid, particularly in the case of comparisons of non-biased with nucleotide-biased genomes (such that of Plasmodium falciparum). Z-values estimates based on Monte Carlo technics, can be calculated experimentally for any alignment output, whatever the method used. Empirically, a Z-value higher than approximately 8 is supposed reasonable to assess that an alignment score is significant, but this arbitrary figure was never theoretically justified.'),
(71223, 2004, 'bio', 'A multi-algorithm, multi-timescale method for cell simulation', 'Takahashi, Kouichi|Kaizu, Kazunari|Hu, Bin|Tomita, Masaru', 'Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, 252-8520, Japan.|Institute for Advanced Biosciences, Keio University, Fujisawa, Kanagawa, 252-8520, Japan.', 'Japan|Japan|Japan|Japan', 127, 'Algorithms|Biological Clocks|Cell Physiological Phenomena|Computer Simulation|Escherichia coli|Heat-Shock Proteins|Heat-Shock Response|Models, Biological|Models, Statistical|Stochastic Processes|Systems Integration|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btg442', '14990450', 'Many important problems in cell biology require the dense nonlinear interactions between functional modules to be considered. The importance of computer simulation in understanding cellular processes is now widely accepted, and a variety of simulation algorithms useful for studying certain subsystems have been designed. Many of these are already widely used, and a large number of models constructed on these existing formalisms are available. A significant computational challenge is how we can integrate such sub-cellular models running on different types of algorithms to construct higher order models.'),
(71224, 2004, 'bio', 'Predicting subcellular localization of proteins using machine-learned classifiers', 'Lu, Z|Szafron, D|Greiner, R|Lu, P|Wishart, D S|Poulin, B|Anvik, J|Macdonell, C|Eisner, R', 'Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.|Department of Computing Science, University of Alberta, Edmonton, AB, Canada, T6G 2E8.', 'Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada|Canada', 280, 'Algorithms|Artificial Intelligence|Cellular Structures|Cluster Analysis|Databases, Protein|Information Storage and Retrieval|Natural Language Processing|Pattern Recognition, Automated|Proteins|Proteome|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Tissue Distribution|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/btg447', '14990451', 'Identifying the destination or localization of proteins is key to understanding their function and facilitating their purification. A number of existing computational prediction methods are based on sequence analysis. However, these methods are limited in scope, accuracy and most particularly breadth of coverage. Rather than using sequence information alone, we have explored the use of database text annotations from homologs and machine learning to substantially improve the prediction of subcellular location.'),
(71225, 2004, 'bio', 'Automated extraction of mutation data from the literature: application of MuteXt to G protein-coupled receptors and nuclear hormone receptors', 'Horn, Florence|Lau, Anthony L|Cohen, Fred E', 'Department of Cellular and Molecular Pharmacology, University of California of San Francisco, 94143, USA. horn@cmpharm.ucsf.edu|Department of Cellular and Molecular Pharmacology, University of California of San Francisco, 94143, USA. horn@cmpharm.ucsf.edu|Department of Cellular and Molecular Pharmacology, University of California of San Francisco, 94143, USA. horn@cmpharm.ucsf.edu', 'United States|United States|United States', 105, 'Algorithms|Amino Acid Substitution|Database Management Systems|Databases, Bibliographic|Databases, Protein|Information Storage and Retrieval|MEDLINE|Mutation|Natural Language Processing|Periodicals as Topic|Proteins|Receptors, G-Protein-Coupled|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|Software Validation', 'Comparative Study', '10.1093/bioinformatics/btg449', '14990452', 'The amount of genomic and proteomic data that is published daily in the scientific literature is outstripping the ability of experimental scientists to stay current. Reviews, the traditional medium for collating published observations, are also unable to keep pace. For some specific classes of information (e.g. sequences and protein structures), obligatory data deposition policies have helped. However, a great deal of other valuable information is spread throughout the literature hindering coherent access. We are involved in the Molecular Class-Specific Information System (MCSIS) project, a collaborative effort to design and automate the maintenance of protein family databases. The first two databases, the GPCRDB and NucleaRDB, are focused on G protein-coupled receptors (GPCRs) and nuclear hormone receptors (NRs), respectively. The main aim of the MCSIS project is to gather heterogeneous data from across a variety of electronic and literature sources in order to draw new inferences about the target protein families.'),
(71226, 2004, 'bio', 'Enrichment of transcriptional regulatory sites in non-coding genomic region', 'Xue, Wen|Wang, Jin|Shen, Zhirong|Zhu, Huaiqiu', 'The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.|The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Science, Nanjing University, Nanjing 210093, China.', 'China|China|China|China', 7, 'Algorithms|Animals|Conserved Sequence|Drosophila melanogaster|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Genome|Genome, Fungal|Genome, Viral|Herpesvirus 4, Human|Open Reading Frames|Saccharomyces cerevisiae|Sequence Alignment|Sequence Analysis, DNA|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg450', '14990453', 'Over-represented k-mers in non-coding genomic regions often lead to identification of potential transcriptional regulatory sites (TRS). This phenomenon has been employed by many algorithms to predict TRS in silico. Yet, the improvement of these algorithms should be based on deeper understanding of the enrichment feature. To obtain a general distributional profile of TRS in different regions of genomes as well as in different genomes, we here performed a systematic analysis on the over-representation of TRS in intergenic regions and gene upstream regions of yeasts and viral genomes, and the distributional pattern of TRS in intergenic and intron regions of the Drosophila genome. We also explored the way to evaluate the accuracy of TRS consensus sequences by measuring their enrichment.'),
(71227, 2004, 'bio', 'ChromoWheel: a new spin on eukaryotic chromosome visualization', 'Ekdahl, Sven|Sonnhammer, Erik L L', 'Center for Genomics and Bioinformatics, Karolinska Institutet, S-17177 Stockholm, Sweden.|Center for Genomics and Bioinformatics, Karolinska Institutet, S-17177 Stockholm, Sweden.', 'Sweden|Sweden', 11, 'Animals|Chromosome Mapping|Chromosomes|Computer Graphics|Eukaryotic Cells|Humans|Hypermedia|Information Storage and Retrieval|Internet|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/btg448', '14990454', 'ChromoWheel is an Internet browser application for generating whole-genome illustrations. It can be used to depict chromosomes, genes and relations between chromosomal loci. The circular layout of chromosomes is advantageous for showing relationships between different chromosomes, as the connecting line never crosses over a chromosome. All graphical image components are in the vector-based format Scalable Vector Graphics, which are highly scaleable and admit user interaction. ChromoWheel can either be run with user-provided data in the generic SFS format, or as a browser front-end for precompiled genomic data.'),
(71228, 2004, 'bio', 'FatiGO: a web tool for finding significant associations of Gene Ontology terms with groups of genes', 'Al-Shahrour, Fátima|Díaz-Uriarte, Ramón|Dopazo, Joaquín', 'Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro 3, 28029 Madrid, Spain.|Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro 3, 28029 Madrid, Spain.|Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas (CNIO), Melchor Fernández Almagro 3, 28029 Madrid, Spain.', 'Spain|Spain|Spain', 825, 'Algorithms|Artificial Intelligence|Databases, Genetic|Gene Expression Profiling|Hypermedia|Information Storage and Retrieval|Internet|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/btg455', '14990455', 'We present a simple but powerful procedure to extract Gene Ontology (GO) terms that are significantly over- or under-represented in sets of genes within the context of a genome-scale experiment (DNA microarray, proteomics, etc.). Said procedure has been implemented as a web application, FatiGO, allowing for easy and interactive querying. FatiGO, which takes the multiple-testing nature of statistical contrast into account, currently includes GO associations for diverse organisms (human, mouse, fly, worm and yeast) and the TrEMBL/Swissprot GOAnnotations@EBI correspondences from the European Bioinformatics Institute.'),
(71229, 2004, 'bio', 'AntiHunter: searching BLAST output for EST antisense transcripts', 'Lavorgna, Giovanni|Sessa, Luca|Guffanti, Alessandro|Lassandro, Lelio|Casari, Giorgio', 'Istituto Scientifico H. S. Raffaele, Via Olgettina 60, 20132 Milan, Italy. giovanni.lavorgna@hsr.it|Istituto Scientifico H. S. Raffaele, Via Olgettina 60, 20132 Milan, Italy. giovanni.lavorgna@hsr.it|Istituto Scientifico H. S. Raffaele, Via Olgettina 60, 20132 Milan, Italy. giovanni.lavorgna@hsr.it|Istituto Scientifico H. S. Raffaele, Via Olgettina 60, 20132 Milan, Italy. giovanni.lavorgna@hsr.it|Istituto Scientifico H. S. Raffaele, Via Olgettina 60, 20132 Milan, Italy. giovanni.lavorgna@hsr.it', 'Italy|Italy|Italy|Italy|Italy', 10, 'Algorithms|DNA, Antisense|Expressed Sequence Tags|Hypermedia|Information Storage and Retrieval|Internet|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/btg460', '14990456', 'AntiHunter is a new web-based tool for the identification of expressed sequence tag (EST) antisense transcripts from BLAST output. In order to perform an analysis, user is required to input a genomic sequence plus an associated list of transcript names and coordinates of the genomic region (i.e. genome annotation). After masking the repeated regions (if any), program will perform a BLASTN search of the input sequence versus the selected EST database, reporting by Email the EST entries that reveal a putative antisense transcript with respect to the user supplied list.'),
(71230, 2004, 'bio', 'Support vector machine classification on the web', 'Pavlidis, Paul|Wapinski, Ilan|Noble, William Stafford', 'Columbia Genome Center and Department of Biomedical Informatics, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu|Columbia Genome Center and Department of Biomedical Informatics, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu|Columbia Genome Center and Department of Biomedical Informatics, Columbia University, 1150 St Nicholas Avenue, New York, NY 10032, USA. pp175@columbia.edu', 'United States|United States|United States', 85, 'Algorithms|Artificial Intelligence|Cluster Analysis|Computing Methodologies|Information Storage and Retrieval|Internet|Pattern Recognition, Automated|Software', 'Journal Article', '10.1093/bioinformatics/btg461', '14990457', 'The support vector machine (SVM) learning algorithm has been widely applied in bioinformatics. We have developed a simple web interface to our implementation of the SVM algorithm, called Gist. This interface allows novice or occasional users to apply a sophisticated machine learning algorithm easily to their data. More advanced users can download the software and source code for local installation. The availability of these tools will permit more widespread application of this powerful learning algorithm in bioinformatics.'),
(71231, 2004, 'bio', 'me-PCR: a refined ultrafast algorithm for identifying sequence-defined genomic elements', 'Murphy, Kevin|Raj, Towfique|Winters, R Scott|White, Peter S', 'Division of Oncology, Childrens Hospital of Philadelphia, University of Pennsylvania, Philadelphia 19104-4318, USA.|Division of Oncology, Childrens Hospital of Philadelphia, University of Pennsylvania, Philadelphia 19104-4318, USA.|Division of Oncology, Childrens Hospital of Philadelphia, University of Pennsylvania, Philadelphia 19104-4318, USA.|Division of Oncology, Childrens Hospital of Philadelphia, University of Pennsylvania, Philadelphia 19104-4318, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Gene Expression Profiling|Genome|Internet|Quality Control|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/btg466', '14990458', 'We have adapted the originally described electronic PCR (e-PCR) algorithm to perform string searches more accurately and much more rapidly than previously possible. Our implementation [multithreaded e-PCR (me-PCR)] runs sufficiently fast to allow even desktop machines to query quickly large genomes with very large genomic element sets. In addition, me-PCR is multithreaded, interprets all IUPAC nucleotide symbols, allows searches with elements specified by long sequences (such as SNPs), accepts ranges in the expected PCR size input field, requires substantially less memory for analysis of large sequences and corrects a number of minor flaws causing misreporting of hits in exceptional cases. Thus, me-PCR provides increased annotation capabilities for complex genomes to non-expert laboratories.'),
(71232, 2004, 'bio', 'CisML: an XML-based format for sequence motif detection software', 'Haverty, Peter M|Weng, Zhiping', 'Bioinformatics Program, Boston University, Boston, MA 02215, USA.|Bioinformatics Program, Boston University, Boston, MA 02215, USA.', 'United States|United States', 6, 'Amino Acid Motifs|Database Management Systems|Databases, Protein|Hypermedia|Information Storage and Retrieval|Internet|Programming Languages|Sequence Alignment|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bth162', '15001475', 'CisML is an XML-based format for sequence motif detection software. This proposed standard is applicable to many types of sequence motif detection programs. It is intended to facilitate the integration of data and the comparison of results from different software packages, and to simplify the development of downstream tools. XSL stylesheets are provided for easy generation of text, html and graphical reports from CisML-formatted data.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71233, 2004, 'bio', 'Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs', 'Kashtan, N|Itzkovitz, S|Milo, R|Alon, U', 'Department of Molecular Cell biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Cell biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Cell biology, Weizmann Institute of Science, Rehovot 76100, Israel.|Department of Molecular Cell biology, Weizmann Institute of Science, Rehovot 76100, Israel.', 'Israel|Israel|Israel|Israel', 342, 'Algorithms|Animals|Artificial Intelligence|Caenorhabditis elegans|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Neurological|Nerve Net|Sample Size|Signal Transduction', 'Comparative Study', '10.1093/bioinformatics/bth163', '15001476', 'Biological and engineered networks have recently been shown to display network motifs: a small set of characteristic patterns that occur much more frequently than in randomized networks with the same degree sequence. Network motifs were demonstrated to play key information processing roles in biological regulation networks. Existing algorithms for detecting network motifs act by exhaustively enumerating all subgraphs with a given number of nodes in the network. The runtime of such algorithms increases strongly with network size. Here, we present a novel algorithm that allows estimation of subgraph concentrations and detection of network motifs at a runtime that is asymptotically independent of the network size. This algorithm is based on random sampling of subgraphs. Network motifs are detected with a surprisingly small number of samples in a wide variety of networks. Our method can be applied to estimate the concentrations of larger subgraphs in larger networks than was previously possible with exhaustive enumeration algorithms. We present results for high-order motifs in several biological networks and discuss their possible functions.'),
(71234, 2004, 'bio', 'A Web-based design center for vector-based siRNA and siRNA cassette', 'Wang, Luquan|Mu, Forest Y', 'GenScript Corporation, 120 Centennial Avenue, Piscataway, NJ 08854, USA. larryw@genscript.com|GenScript Corporation, 120 Centennial Avenue, Piscataway, NJ 08854, USA. larryw@genscript.com', 'United States|United States', 44, 'Computer-Aided Design|Genetic Vectors|Internet|Mutagenesis, Insertional|Online Systems|RNA, Small Interfering|Sequence Analysis, RNA|Software', 'Journal Article', '10.1093/bioinformatics/bth164', '15001477', 'To facilitate the designing process for vector-based siRNA and siRNA cassette, a tool set has been developed consisting of a siRNA target finder, a siRNA construct builder and a siRNA sequence scrambler. The siRNA target finder is used to identify candidate siRNA target sites. The program automates homology filtering, minimizes non-specific cross-reaction, filters target sites based on RNA duplex internal stability and siRNA sense/anti-sense strand secondary structure. The siRNA construct builder is used to create a siRNA hairpin construct as a vector insert or a cassette insert. The siRNA sequence scrambler is used to generate a negative control sequence for siRNA experiments. Together, these programs provide a comprehensive utility set to address the specific bioinformatics need of DNA-based siRNA design.'),
(71235, 2003, 'bio', 'Bioinformatics: from sequence analysis to molecular structure Proceedings of a symposium May 30, 2002, Cagliari, Italy', '-', '-', '-', 44, 'Computational Biology|Molecular Structure|Sequence Analysis', 'Congress', '10.1093/bioinformatics/bth164', '15025142', '-'),
(71236, 2004, 'bio', 'Conservation analysis of small RNA genes in Escherichia coli', 'Zhang, Yong|Zhang, Zhihua|Ling, Lunjiang|Shi, Baochen|Chen, Runsheng', 'Bioinformatics Laboratory, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|Bioinformatics Laboratory, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|Bioinformatics Laboratory, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|Bioinformatics Laboratory, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.|Bioinformatics Laboratory, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China.', 'China|China|China|China|China', 0, 'Algorithms|Base Sequence|Conserved Sequence|Escherichia coli|Evolution, Molecular|Gene Expression Profiling|Genome, Bacterial|Molecular Sequence Data|Phylogeny|RNA, Bacterial|RNA, Ribosomal, 16S|Sequence Alignment|Sequence Analysis, RNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/btg457', '15033865', 'Small RNA (sRNA) genes in Escherichia coli have been in focus recently, as 44 out of 55 experimentally confirmed sRNA genes have been precisely located in the genome. The object of this study is to analyze quantitatively the conservation of these sRNA genes and compare it with the conservation of protein-encoding genes, function-unknown regions and tRNA genes.'),
(71237, 2004, 'bio', 'Extracting human protein interactions from MEDLINE using a full-sentence parser', 'Daraselia, Nikolai|Yuryev, Anton|Egorov, Sergei|Novichkova, Svetalana|Nikitin, Alexander|Mazo, Ilya', 'Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com|Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com|Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com|Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com|Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com|Ariadne Genomics, Inc., 9700 Great Seneca Hwy, Rockville, MD 20850, USA. nikolai@ariadnegenomics.com', 'United States|United States|United States|United States|United States|United States', 178, 'Abstracting and Indexing as Topic|Artificial Intelligence|Database Management Systems|Databases, Protein|Humans|Information Storage and Retrieval|MEDLINE|Natural Language Processing|Pattern Recognition, Automated|Periodicals as Topic|Protein Interaction Mapping|Proteins|Reproducibility of Results|Semantics|Sensitivity and Specificity|Vocabulary, Controlled', 'Comparative Study', '10.1093/bioinformatics/btg452', '15033866', 'The living cell is a complex machine that depends on the proper functioning of its numerous parts, including proteins. Understanding protein functions and how they modify and regulate each other is the next great challenge for life-sciences researchers. The collective knowledge about protein functions and pathways is scattered throughout numerous publications in scientific journals. Bringing the relevant information together becomes a bottleneck in a research and discovery process. The volume of such information grows exponentially, which renders manual curation impractical. As a viable alternative, automated literature processing tools could be employed to extract and organize biological data into a knowledge base, making it amenable to computational analysis and data mining.'),
(71238, 2004, 'bio', 'A systematic method to identify genomic islands and its applications in analyzing the genomes of Corynebacterium glutamicum and Vibrio vulnificus CMCP6 chromosome I', 'Zhang, Ren|Zhang, Chun-Ting', 'Department of Epidemiology and Biostatistics, Tianjin Cancer Institute and Hospital, Tianjin 300060, China.|Department of Epidemiology and Biostatistics, Tianjin Cancer Institute and Hospital, Tianjin 300060, China.', 'China|China', 64, 'Algorithms|Base Composition|Base Sequence|Chromosome Mapping|Corynebacterium|Gene Expression Profiling|Genome, Bacterial|Genomic Islands|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Vibrio vulnificus', 'Comparative Study', '10.1093/bioinformatics/btg453', '15033867', 'Some genomic islands contain horizontally transferred genes, which play critical roles in altering the genotypes and phenotypes of organisms, and horizontal gene transfer has been recognized as a universal event throughout bacterial evolution. A windowless method to display the distribution of genomic GC content, the cumulative GC profile, is proposed to identify genomic islands in genomes whose complete genome sequences are available. Two new indices are proposed to assess the codon usage bias and amino acid usage bias in genomic islands.'),
(71239, 2004, 'bio', 'Enhancing scatterplots with smoothed densities', 'Eilers, Paul H C|Goeman, Jelle J', 'Department of Medical Statistics, Leiden University Medical Centre, The Netherlands. p.eilers@lumc.nl|Department of Medical Statistics, Leiden University Medical Centre, The Netherlands. p.eilers@lumc.nl', 'Netherlands|Netherlands', 0, 'Algorithms|Computer Graphics|Gene Expression Profiling|Models, Genetic|Models, Statistical|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Software|Statistical Distributions|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg454', '15033868', 'Scatterplots of microarray data generally contain a very large number of dots, making it difficult to get a good impression of their distribution in dense areas.'),
(71240, 2004, 'bio', 'PHIRE, a deterministic approach to reveal regulatory elements in bacteriophage genomes', 'Lavigne, R|Sun, W D|Volckaert, G', 'Laboratory of Gene Technology, Katholieke Universiteit Leuven, Kasteelpark Arenberg 21, Leuven, B-3001, Belgium.|Laboratory of Gene Technology, Katholieke Universiteit Leuven, Kasteelpark Arenberg 21, Leuven, B-3001, Belgium.|Laboratory of Gene Technology, Katholieke Universiteit Leuven, Kasteelpark Arenberg 21, Leuven, B-3001, Belgium.', 'Belgium|Belgium|Belgium', 65, 'Bacteriophages|Base Sequence|Gene Expression Profiling|Gene Expression Regulation, Viral|Genes, Regulator|Genome, Viral|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software', 'Comparative Study', '10.1093/bioinformatics/btg456', '15033869', 'In silico genome analysis of bacteriophage genomes focuses mainly on gene discovery and functional assignment. The search for regulatory elements contained within these genome sequences is often based on prior knowledge of other genomic elements or on learning algorithms of experimentally determined data, potentially leading to a biased prediction output. The PHage In silico Regulatory Elements (PHIRE) program is a standalone program in Visual Basic. It performs an algorithmic string-based search on bacteriophage genome sequences to uncover and extract subsequence alignments hinting at regulatory elements contained within these genomes, in a deterministic manner without any prior experimental or predictive knowledge.'),
(71241, 2004, 'bio', 'Phylo-VISTA: interactive visualization of multiple DNA sequence alignments', 'Shah, Nameeta|Couronne, Olivier|Pennacchio, Len A|Brudno, Michael|Batzoglou, Serafim|Bethel, E Wes|Rubin, Edward M|Hamann, Bernd|Dubchak, Inna', 'Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov|Center for Image Processing and Integrated Computing, Department of Computer Science, One Shields Avenue, University of California, Davis, CA 95616-8562, USA. phylovista@lbl.gov', 'United States|United States|United States|United States|United States|United States|United States|United States|United States', 0, 'Algorithms|Animals|Base Sequence|Computer Graphics|Gene Expression Profiling|Humans|Leukemia|Molecular Sequence Data|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/btg459', '15033870', 'The power of multi-sequence comparison for biological discovery is well established. The need for new capabilities to visualize and compare cross-species alignment data is intensified by the growing number of genomic sequence datasets being generated for an ever-increasing number of organisms. To be efficient these visualization algorithms must support the ability to accommodate consistently a wide range of evolutionary distances in a comparison framework based upon phylogenetic relationships.'),
(71242, 2004, 'bio', 'Optimization models for cancer classification: extracting gene interaction information from microarray expression data', 'Antonov, Alexey V|Tetko, Igor V|Mader, Michael T|Budczies, Jan|Mewes, Hans W', 'GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. antonov@gsf.de|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. antonov@gsf.de|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. antonov@gsf.de|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. antonov@gsf.de|GSF National Research Center for Environment and Health, Institute for Bioinformatics, Ingolstädter Landstrasse 1, D-85764 Neuherberg, Germany. antonov@gsf.de', 'Germany|Germany|Germany|Germany|Germany', 56, 'Algorithms|Animals|Gene Expression Profiling|Gene Expression Regulation, Neoplastic|Humans|Models, Genetic|Neoplasms|Numerical Analysis, Computer-Assisted|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Programming, Linear|Protein Interaction Mapping', 'Evaluation Studies', '10.1093/bioinformatics/btg462', '15033871', 'Microarray data appear particularly useful to investigate mechanisms in cancer biology and represent one of the most powerful tools to uncover the genetic mechanisms causing loss of cell cycle control. Recently, several different methods to employ microarray data as a diagnostic tool in cancer classification have been proposed. These procedures take changes in the expression of particular genes into account but do not consider disruptions in certain gene interactions caused by the tumor. It is probable that some genes participating in tumor development do not change their expression level dramatically. Thus, they cannot be detected by simple classification approaches used previously. For these reasons, a classification procedure exploiting information related to changes in gene interactions is needed.'),
(71243, 2004, 'bio', 'Disulfide connectivity prediction using recursive neural networks and evolutionary information', 'Vullo, Alessandro|Frasconi, Paolo', 'Department of Systems and Computer Science, Università di Firenze Via di S. Marta 3, 50139-I Firenze, Italy. vullo@dsi.unifi.it|Department of Systems and Computer Science, Università di Firenze Via di S. Marta 3, 50139-I Firenze, Italy. vullo@dsi.unifi.it', 'Italy|Italy', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Binding Sites|Cysteine|Disulfides|Evolution, Molecular|Gene Expression Profiling|Molecular Sequence Data|Neural Networks (Computer)|Protein Binding|Proteins|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg463', '15033872', 'We focus on the prediction of disulfide bridges in proteins starting from their amino acid sequence and from the knowledge of the disulfide bonding state of each cysteine. The location of disulfide bridges is a structural feature that conveys important information about the protein main chain conformation and can therefore help towards the solution of the folding problem. Existing approaches based on weighted graph matching algorithms do not take advantage of evolutionary information. Recursive neural networks (RNN), on the other hand, can handle in a natural way complex data structures such as graphs whose vertices are labeled by real vectors, allowing us to incorporate multiple alignment profiles in the graphical representation of disulfide connectivity patterns.'),
(71244, 2004, 'bio', 'Variance-stabilizing transformations for two-color microarrays', 'Durbin, Blythe P|Rocke, David M', 'Center for Image Processing and Integrated Computing, University of California, Davis 95616, USA. bpdurbin@ucdavis.edu|Center for Image Processing and Integrated Computing, University of California, Davis 95616, USA. bpdurbin@ucdavis.edu', 'United States|United States', 40, 'Algorithms|Analysis of Variance|Color|Fluorescent Dyes|Gene Expression Profiling|Genetic Variation|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/btg464', '15033873', 'Authors of several recent papers have independently introduced a family of transformations (the generalized-log family), which stabilizes the variance of microarray data up to the first order. However, for data from two-color arrays, tests for differential expression may require that the variance of the difference of transformed observations be constant, rather than that of the transformed observations themselves.'),
(71245, 2004, 'bio', '404 not found: the stability and persistence of URLs published in MEDLINE', 'Wren, Jonathan D', 'Advanced Center for Genome Technology, Department of Botany and Microbiology, The University of Oklahoma, 620 Parrington Oval Rm. 106, Norman, OK 73019, USA. Jonathan.Wren@OU.edu', 'United States', 0, 'Abstracting and Indexing as Topic|Bibliometrics|Database Management Systems|Databases, Bibliographic|Hypermedia|Information Dissemination|Information Storage and Retrieval|Internet|MEDLINE|Reproducibility of Results|Sensitivity and Specificity|Terminology as Topic|Time Factors', 'Comparative Study', '10.1093/bioinformatics/btg465', '15033874', 'The advent of the World Wide Web has enabled unprecedented supplementation of traditional journal publications, allowing access to resources, such as video, sound, software, databases, datasets too large to publish, and even supplementary information and discussion. However, unlike traditional publications, continued availability of these online resources is not guaranteed. An automated survey was conducted to quantify the growth in Uniform Resource Locators (URLs) published to date in MEDLINE abstracts, their current availability and distribution by journal.'),
(71246, 2004, 'bio', 'Degrees of differential gene expression: detecting biologically significant expression differences and estimating their magnitudes', 'Bickel, David R', 'Medical College of Georgia, Office of Biostatistics and Bioinformatics, Augusta, GA 30912-4900, USA. bickel@preuba.info', 'Georgia', 37, 'Algorithms|Computer Simulation|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/btg468', '15033875', 'Many methods of identifying differential expression in genes depend on testing the null hypotheses of exactly equal means or distributions of expression levels for each gene across groups, even though a statistically significant difference in the expression level does not imply the occurrence of any difference of biological or clinical significance. This is because a mathematical definition of differential expression as any non-zero difference does not correspond to the differential expression biologists seek. Furthermore, while some current methods account for multiple comparisons in hypothesis tests, they do not accordingly adjust estimates of the degrees to which genes are differentially expressed. Both problems lead to overstating the relevance of findings.'),
(71247, 2004, 'bio', 'A statistical framework for combining and interpreting proteomic datasets', 'Gilchrist, Michael A|Salter, Laura A|Wagner, Andreas', 'Department of Biology, University of New Mexico, Albuquerque 87106, USA.|Department of Biology, University of New Mexico, Albuquerque 87106, USA.|Department of Biology, University of New Mexico, Albuquerque 87106, USA.', 'Mexico|Mexico|Mexico', 45, 'Algorithms|Computer Simulation|Databases, Protein|Information Storage and Retrieval|Models, Biological|Models, Statistical|Protein Interaction Mapping|Proteome|Reproducibility of Results|Saccharomyces cerevisiae Proteins|Sensitivity and Specificity|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/btg469', '15033876', 'To identify accurately protein function on a proteome-wide scale requires integrating data within and between high-throughput experiments. High-throughput proteomic datasets often have high rates of errors and thus yield incomplete and contradictory information. In this study, we develop a simple statistical framework using Bayes law to interpret such data and combine information from different high-throughput experiments. In order to illustrate our approach we apply it to two protein complex purification datasets.'),
(71248, 2004, 'bio', 'Omic space: coordinate-based integration and analysis of genomic phenomic interactions', 'Toyoda, Tetsuro|Wada, Akiyoshi', 'Genomic Knowledge Base Research Team, Bioinformatics Group, RIKEN Yokohama Institute, Kanagawa 230-0045, Japan. toyop@gsc.riken.go.jp|Genomic Knowledge Base Research Team, Bioinformatics Group, RIKEN Yokohama Institute, Kanagawa 230-0045, Japan. toyop@gsc.riken.go.jp', 'Japan|Japan', 12, 'Algorithms|Database Management Systems|Databases, Genetic|Gene Expression Profiling|Gene Expression Regulation|Genomics|Information Storage and Retrieval|Models, Genetic|Systems Integration|Transcription, Genetic|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth165', '15037505', 'With the recent progress in genomics, various data sets of omic interactions describing networks of omic elements have become available. In order to obtain reliable hypotheses from the data, it is effective to integrate interactions from different sorts of data sets. In order to facilitate a coordinate-based integration and analysis of omic interactions, we introduce the concept of an omic space comprising a comprehensive set of omic planes. Genomic, transcriptomic, proteomic, metabolomic, phenomic and other omic planes are defined by two orthogonal genomic-coordinate axes.'),
(71249, 2004, 'bio', 'Decomposition of metabolic network into functional modules based on the global connectivity structure of reaction graph', 'Ma, Hong-Wu|Zhao, Xue-Ming|Yuan, Ying-Jin|Zeng, An-Ping', 'Department of Genome Analysis, GBF-German Research Center for Biotechnology Mascheroder Weg 1, 38124 Braunschweig, Germany.|Department of Genome Analysis, GBF-German Research Center for Biotechnology Mascheroder Weg 1, 38124 Braunschweig, Germany.|Department of Genome Analysis, GBF-German Research Center for Biotechnology Mascheroder Weg 1, 38124 Braunschweig, Germany.|Department of Genome Analysis, GBF-German Research Center for Biotechnology Mascheroder Weg 1, 38124 Braunschweig, Germany.', 'Germany|Germany|Germany|Germany', 39, 'Algorithms|Computer Graphics|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Regulation, Bacterial|Models, Biological|Signal Transduction|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth167', '15037506', 'Metabolic networks are organized in a modular, hierarchical manner. Methods for a rational decomposition of the metabolic network into relatively independent functional subsets are essential to better understand the modularity and organization principle of a large-scale, genome-wide network. Network decomposition is also necessary for functional analysis of metabolism by pathway analysis methods that are often hampered by the problem of combinatorial explosion due to the complexity of metabolic network. Decomposition methods proposed in literature are mainly based on the connection degree of metabolites. To obtain a more reasonable decomposition, the global connectivity structure of metabolic networks should be taken into account.'),
(71250, 2004, 'bio', 'Non-linear conversion between genetic and physical chromosomal distances', 'Voigt, Claudia|Möller, Steffen|Ibrahim, Saleh M|Serrano-Fernández, Pablo', 'Proteome Center Rostock, Joachim-Jungius-Strasse 9, 18059 Rostock, Germany.|Proteome Center Rostock, Joachim-Jungius-Strasse 9, 18059 Rostock, Germany.|Proteome Center Rostock, Joachim-Jungius-Strasse 9, 18059 Rostock, Germany.|Proteome Center Rostock, Joachim-Jungius-Strasse 9, 18059 Rostock, Germany.', 'Germany|Germany|Germany|Germany', 7, 'Algorithms|Animals|Computer Graphics|Genetic Markers|Humans|Internet|Linkage Disequilibrium|Models, Genetic|Nonlinear Dynamics|Numerical Analysis, Computer-Assisted|Physical Chromosome Mapping|Rats|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth168', '15037507', 'A supervised nonlinear interpolation significantly improves the reliability of conversions from genetic distances to physical distances as compared with the linear ones. A webaccessible application was created that addresses this question with a graphical presentation that may be wrapped by local installations.'),
(71251, 2004, 'bio', 'Normalization of single-channel DNA array data by principal component analysis', 'Stoyanova, Radka|Querec, Troy D|Brown, Truman R|Patriotis, Christos', 'Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111-2497, USA.|Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111-2497, USA.|Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111-2497, USA.|Division of Population Science, Fox Chase Cancer Center, 333 Cottman Avenue, Philadelphia, PA 19111-2497, USA.', 'United States|United States|United States|United States', 21, 'Algorithms|Computer Simulation|Epithelium|Female|Gene Expression Profiling|Gene Expression Regulation|Humans|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Ovary|Principal Component Analysis|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth170', '15037508', 'Detailed comparison and analysis of the output of DNA gene expression arrays from multiple samples require global normalization of the measured individual gene intensities from the different hybridizations. This is needed for accounting for variations in array preparation and sample hybridization conditions.'),
(71252, 2004, 'bio', 'MITOPRED: a genome-scale method for prediction of nucleus-encoded mitochondrial proteins', 'Guda, Chittibabu|Fahy, Eoin|Subramaniam, Shankar', 'San Diego Supercomputer Center, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505, USA.|San Diego Supercomputer Center, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505, USA.|San Diego Supercomputer Center, University of California at San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0505, USA.', 'United States|United States|United States', 114, 'Algorithms|Animals|Cell Nucleus|Gene Expression Profiling|Genome|Humans|Mitochondrial Proteins|Proteome|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software|Tissue Distribution', 'Comparative Study', '10.1093/bioinformatics/bth171', '15037509', 'Currently available methods for the prediction of subcellular location of mitochondrial proteins rely largely on the presence of mitochondrial targeting signals in the protein sequences. However, a large fraction of mitochondrial proteins lack such signals, making those tools ineffective for genome-scale prediction of mitochondria-targeted proteins. Here, we propose a method for genome-scale prediction of nucleus-encoded mitochondrial proteins. The new method, MITOPRED, is based on the Pfam domain occurrence patterns and the amino acid compositional differences between mitochondrial and non-mitochondrial proteins.'),
(71253, 2004, 'bio', 'BLAST2GENE: a comprehensive conversion of BLAST output into independent genes and gene fragments', 'Suyama, Mikita|Torrents, David|Bork, Peer', 'Biocomputing, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69012 Heidelberg, Germany.|Biocomputing, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69012 Heidelberg, Germany.|Biocomputing, European Molecular Biology Laboratory, Meyerhofstrasse 1, D-69012 Heidelberg, Germany.', 'Germany|Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Gene Dosage|Genetic Variation|Information Storage and Retrieval|Internet|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth172', '15037510', 'BLAST2GENE is a program that allows a detailed analysis of genomic regions containing completely or partially duplicated genes. From a BLAST (or BL2SEQ) comparison of a protein or nucleotide query sequence with any genomic region of interest, BLAST2GENE processes all high scoring pairwise alignments (HSPs) and provides the disposition of all independent copies along the genomic fragment. The results are provided in text and PostScript formats to allow an automatic and visual evaluation of the respective region.'),
(71254, 2004, 'bio', 'Inferring dynamic architecture of cellular networks using time series of gene expression, protein and metabolite data', 'Sontag, Eduardo|Kiyatkin, Anatoly|Kholodenko, Boris N', 'Department of Mathematics, Rutgers University, Piscataway, NJ 08854, USA.|Department of Mathematics, Rutgers University, Piscataway, NJ 08854, USA.|Department of Mathematics, Rutgers University, Piscataway, NJ 08854, USA.', 'United States|United States|United States', 123, 'Algorithms|Cell Physiological Phenomena|Computer Graphics|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation|Models, Biological|Multienzyme Complexes|Signal Transduction|Time Factors|User-Computer Interface', 'Evaluation Studies', '10.1093/bioinformatics/bth173', '15037511', 'High-throughput technologies have facilitated the acquisition of large genomics and proteomics datasets. However, these data provide snapshots of cellular behavior, rather than help us reveal causal relations. Here, we propose how these technologies can be utilized to infer the topology and strengths of connections among genes, proteins and metabolites by monitoring time-dependent responses of cellular networks to experimental interventions.'),
(71255, 2004, 'bio', 'Identifying multiple alignment regions satisfying simple formulas and patterns', 'Stojanovic, Nikola|Dewar, Ken', 'Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA. nick@cse.uta.edu|Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, TX 76019, USA. nick@cse.uta.edu', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Conserved Sequence|Gene Frequency|PPAR gamma|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth196', '15044226', 'When studying multiple alignments of genomic sequences one frequently aims to locate and count regions which satisfy a set of constraints. These regions may be putatively functional, but researchers may also be interested in quantifying the frequency of occurrences of certain patterns.'),
(71256, 2004, 'bio', 'The DISOPRED server for the prediction of protein disorder', 'Ward, Jonathan J|McGuffin, Liam J|Bryson, Kevin|Buxton, Bernard F|Jones, David T', 'Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.|Bioinformatics Group, Department of Computer Science, University College London, Gower Street, London, WC1E 6BT, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 0, 'Algorithms|Amino Acid Sequence|Artificial Intelligence|Computing Methodologies|Databases, Protein|Molecular Sequence Data|Pattern Recognition, Automated|Proteins|Sequence Alignment|Sequence Analysis, Protein', 'Journal Article', '10.1093/bioinformatics/bth195', '15044227', 'Dynamically disordered regions appear to be relatively abundant in eukaryotic proteomes. The DISOPRED server allows users to submit a protein sequence, and returns a probability estimate of each residue in the sequence being disordered. The results are sent in both plain text and graphical formats, and the server can also supply predictions of secondary structure to provide further structural information.'),
(71257, 2004, 'bio', 'Repair-FunMap: a functional database of proteins of the DNA repair systems', 'Wen, Liting|Feng, Jin-An', 'Department of Chemistry, Temple University, Philadelphia, PA 19122, USA.|Department of Chemistry, Temple University, Philadelphia, PA 19122, USA.', 'United States|United States', 5, 'Abstracting and Indexing as Topic|Algorithms|DNA Repair|Databases, Protein|Models, Biological|Natural Language Processing|Periodicals as Topic|Protein Interaction Mapping|Signal Transduction', 'Journal Article', '10.1093/bioinformatics/bth194', '15044228', 'Repair-FunMap is a functional database of the DNA repair systems. This database contains not only the proteins directly involved in DNA repair, but also the proteins that interact with the DNA repair proteins. A protein interaction network associated with the human DNA repair processes was established according to the functional relationship between proteins in the database. This network represents the current knowledge on the intrinsic signaling pathways related to DNA repair. The Repair-FunMap could become an essential resource center for cancer research, providing clues to understanding the inter-relationship between proteins in the network, and to building scientific models of the DNA repair processes.'),
(71258, 2004, 'bio', 'DNA microarray normalization methods can remove bias from differential protein expression analysis of 2D difference gel electrophoresis results', 'Kreil, David P|Karp, Natasha A|Lilley, Kathryn S', 'Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. D.Kreil@gen.cam.ac.uk|Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. D.Kreil@gen.cam.ac.uk|Department of Genetics/Inference Group (Cavendish Laboratory), University of Cambridge, Cambridge, UK. D.Kreil@gen.cam.ac.uk', 'United Kingdom|United Kingdom|United Kingdom', 77, 'Algorithms|Bayes Theorem|Computer Simulation|Data Interpretation, Statistical|Electrophoresis, Gel, Two-Dimensional|Gene Expression Profiling|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth193', '15044229', 'Two-dimensional Difference Gel Electrophoresis (DIGE) measures expression differences for thousands of proteins in parallel. In contrast to DNA microarray analysis, however, there have been few systematic studies on the validity of differential protein expression analysis, and the effects of normalization methods have not yet been investigated. To address this need, we assessed a series of same-same comparisons, evaluating how random experimental variance influenced differential expression analysis.'),
(71259, 2004, 'bio', 'Bayesian hierarchical error model for analysis of gene expression data', 'Cho, HyungJun|Lee, Jae K', 'Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. hcho@virginia.edu|Department of Health Evaluation Sciences, University of Virginia School of Medicine, Hospital West Complex, Charlottesville, VA 22908-0717, USA. hcho@virginia.edu', 'United States|United States', 28, 'Algorithms|Animals|Bayes Theorem|Brain|Computer Simulation|Data Interpretation, Statistical|Gene Expression Profiling|Humans|Mice|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pan troglodytes|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein', 'Comparative Study', '10.1093/bioinformatics/bth192', '15044230', 'Analysis of genome-wide microarray data requires the estimation of a large number of genetic parameters for individual genes and their interaction expression patterns under multiple biological conditions. The sources of microarray error variability comprises various biological and experimental factors, such as biological and individual replication, sample preparation, hybridization and image processing. Moreover, the same gene often shows quite heterogeneous error variability under different biological and experimental conditions, which must be estimated separately for evaluating the statistical significance of differential expression patterns. Widely used linear modeling approaches are limited because they do not allow simultaneous modeling and inference on the large number of these genetic parameters and heterogeneous error components on different genes, different biological and experimental conditions, and varying intensity ranges in microarray data.'),
(71260, 2004, 'bio', 'UniProt archive', 'Leinonen, Rasko|Diez, Federico Garcia|Binns, David|Fleischmann, Wolfgang|Lopez, Rodrigo|Apweiler, Rolf', 'EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.|EMBL Outstation, The European Bioinformatics Institute (EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.', 'United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom|United Kingdom', 110, 'Amino Acid Sequence|Computer Communication Networks|Database Management Systems|Databases, Protein|Documentation|Information Dissemination|Information Storage and Retrieval|Internet|Molecular Sequence Data|Proteins|Sequence Analysis, Protein|Systems Integration', 'Journal Article', '10.1093/bioinformatics/bth191', '15044231', 'UniProt Archive (UniParc) is the most comprehensive, non-redundant protein sequence database available. Its protein sequences are retrieved from predominant, publicly accessible resources. All new and updated protein sequences are collected and loaded daily into UniParc for full coverage. To avoid redundancy, each unique sequence is stored only once with a stable protein identifier, which can be used later in UniParc to identify the same protein in all source databases. When proteins are loaded into the database, database cross-references are created to link them to the origins of the sequences. As a result, performing a sequence search against UniParc is equivalent to performing the same search against all databases cross-referenced by UniParc. UniParc contains only protein sequences and database cross-references, all other information must be retrieved from the source databases.'),
(71261, 2004, 'bio', 'Defining 3D residue environment in protein structures using SCORPION and FORMIGA', 'Higa, R H|Oliveira, A G|Horita, L G|Miura, R T|Inoue, M K|Kuser, P R|Mancini, A L|Yamagishi, M E B|Togawa, R C|Neshich, G', 'Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 3, 'Algorithms|Amino Acids|Computer Graphics|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth190', '15044232', 'Two web-based applications to analyze amino acids three-dimensional (3D) local environment within protein structures-SCORPION and FORMIGA-are presented. SCORPION and FORMIGA produce a graphical presentation for simple statistical data showing the frequency of residue occurrence within a given sphere (defined here as the 3D contacts). The center of that sphere is placed at the Calpha and at the last heavy atom in the side chain of the selected amino acid. Further depth of detail is given in terms of a secondary structure to which the profiled amino acid belongs. Results obtained with those two applications are relevant for estimating the importance of the amino acid 3D local environment for protein folding and stability. Effectively, SCORPION and FORMIGA construct knowledge-based force fields. The difference between SCORPION and FORMIGA is in that the latter operates on protein interfaces, while the former only functions for a single protein chain. Both applications are implemented as stand-alone components of STING Millennium Suite.'),
(71262, 2004, 'bio', 'CEBS object model for systems biology data, SysBio-OM', 'Xirasagar, Sandhya|Gustafson, Scott|Merrick, B Alex|Tomer, Kenneth B|Stasiewicz, Stanley|Chan, Denny D|Yost, Kenneth J|Yates, John R|Sumner, Susan|Xiao, Nianqing|Waters, Michael D', 'Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com|Science Applications International Corporation, 20201 Century Building, 3rd Floor, Germantown, MD 20874, USA. xirasagars@saic.com', 'United States|United States|United States|United States|United States|United States|United States|United States|United States|United States|United States', 48, 'Database Management Systems|Databases, Factual|Gene Expression Profiling|Information Storage and Retrieval|Metabolism|Models, Biological|Protein Interaction Mapping|Proteomics|Systems Biology', 'Evaluation Studies', '10.1093/bioinformatics/bth189', '15044233', 'To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics).'),
(71263, 2004, 'bio', 'A novel approach for increasing sensitivity and correcting saturation artifacts of radioactively labeled cDNA arrays', 'Querec, Troy D|Stoyanova, Radka|Ross, Eric|Patriotis, Christos', 'Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111-2497, USA.|Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111-2497, USA.|Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111-2497, USA.|Department of Medical Oncology, Fox Chase Cancer Center, Philadelphia, PA 19111-2497, USA.', 'United States|United States|United States|United States', 3, 'Algorithms|Artifacts|Autoradiography|Biomarkers, Tumor|Cell Line|Female|Gene Expression Profiling|Humans|Neoplasm Proteins|Oligonucleotide Array Sequence Analysis|Ovarian Neoplasms|Radioisotope Dilution Technique|Reproducibility of Results|Sensitivity and Specificity', 'Comparative Study', '10.1093/bioinformatics/bth188', '15044234', 'The radioactivity labeled DNA array platform is a robust and accurate way for a high-throughput measurement of gene expression levels in biological samples. Despite its high degree of sensitivity and reproducibility, this platform has several sources of variation. These are related to the presence of saturation effects in the array images and impede the degree of accuracy at which gene expression levels are determined.');
INSERT INTO `papers` (`id`, `ano`, `journal`, `titulo`, `autores`, `afiliacao`, `pais`, `citacoes`, `palavra_chave`, `categorias`, `doi`, `pubmed`, `abstract`) VALUES
(71264, 2004, 'bio', 'Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry', 'Fu, Yan|Yang, Qiang|Sun, Ruixiang|Li, Dequan|Zeng, Rong|Ling, Charles X|Gao, Wen', 'Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn|Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100080, China. yfu@ict.ac.cn', 'China|China|China|China|China|China|China', 93, 'Algorithms|Ions|Mass Spectrometry|Models, Chemical|Models, Molecular|Models, Statistical|Peptide Fragments|Peptides|Sequence Alignment|Sequence Analysis, Protein|Software|Statistics as Topic', 'Comparative Study', '10.1093/bioinformatics/bth186', '15044235', 'The correlation among fragment ions in a tandem mass spectrum is crucial in reducing stochastic mismatches for peptide identification by database searching. Until now, an efficient scoring algorithm that considers the correlative information in a tunable and comprehensive manner has been lacking.'),
(71265, 2004, 'bio', 'ConSSeq: a web-based application for analysis of amino acid conservation based on HSSP database and within context of structure', 'Higa, R H|Montagner, A J|Togawa, R C|Kuser, P R|Yamagishi, M E B|Mancini, A L|Pappas, G|Miura, R T|Horita, L G|Neshich, G', 'Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.|Núcleo de Bioinformática, Centro Nacional de Pesquisa Agropecuária, Empresa Brasileira de Pesquisa Agropecuária, Campinas, SP, Brazil.', 'Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil|Brazil', 6, 'Amino Acids|Conserved Sequence|Databases, Protein|Internet|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth185', '15044236', 'A web-based application to analyze protein amino acids conservation-Consensus Sequence (ConSSeq) is presented. ConSSeq graphically represents information about amino acid conservation based on sequence alignments reported in homology-derived structures of proteins. Beyond the relative entropy for each position in the alignment, ConSSeq also presents the consensus sequence and information about the amino acids, which are predominant at each position of the alignment. ConSSeq is part of the STING Millennium Suite and is implemented as a Java Applet.'),
(71266, 2004, 'bio', 'A case study of high-throughput biological data processing on parallel platforms', 'Pekurovsky, D|Shindyalov, I N|Bourne, P E', 'San Diego Supercomputer Center, University of California San Diego, La Jolla 92093, USA.|San Diego Supercomputer Center, University of California San Diego, La Jolla 92093, USA.|San Diego Supercomputer Center, University of California San Diego, La Jolla 92093, USA.', 'United States|United States|United States', 7, 'Algorithms|Computational Biology|Computing Methodologies|Information Storage and Retrieval|Models, Molecular|Protein Conformation|Proteins|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid', 'Comparative Study', '10.1093/bioinformatics/bth184', '15044237', 'Analysis of large biological data sets using a variety of parallel processor computer architectures is a common task in bioinformatics. The efficiency of the analysis can be significantly improved by properly handling redundancy present in these data combined with taking advantage of the unique features of these compute architectures.'),
(71267, 2004, 'bio', 'A tool for gene expression based PubMed search through combining data sources', 'Korotkiy, Maksym|Middelburg, Rutger|Dekker, Henk|van Harmelen, Frank|Lankelma, Jan', 'Division of Computer Science, VU University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands.|Division of Computer Science, VU University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands.|Division of Computer Science, VU University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands.|Division of Computer Science, VU University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands.|Division of Computer Science, VU University Medical Center, Vrije Universiteit, Amsterdam, The Netherlands.', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands', 6, 'Database Management Systems|Databases, Genetic|Gene Expression Profiling|Information Storage and Retrieval|Natural Language Processing|Oligonucleotide Array Sequence Analysis|PubMed|Publications|Software|Terminology as Topic|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth183', '15044238', 'We present a new tool for the semi-automated querying of PubMed using a batch of tens to thousands of GenBank accession numbers or UniGene cluster ids. By combining information from UniGene and SWISS-PROT, microGENIE obtains information on the biological relevance of expressed genes, as identified by micro-array experiments, with minimal user intervention and time investment.'),
(71268, 2004, 'bio', 'Hypothesis-driven approach to predict transcriptional units from gene expression data', 'Steinhauser, Dirk|Junker, Björn H|Luedemann, Alexander|Selbig, Joachim|Kopka, Joachim', 'Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de|Max Planck Institute of Molecular Plant Physiology, 14476 Golm, Germany. Steinhauser@mpimp-golm.mpg.de', 'Germany|Germany|Germany|Germany|Germany', 24, 'Algorithms|Chromosome Mapping|Cluster Analysis|Computer Simulation|Escherichia coli|Escherichia coli Proteins|Gene Expression Profiling|Gene Expression Regulation, Bacterial|Models, Biological|Oligonucleotide Array Sequence Analysis|Operon|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth182', '15044239', 'A major issue in computational biology is the reconstruction of functional relationships among genes, for example the definition of regulatory or biochemical pathways. One step towards this aim is the elucidation of transcriptional units, which are characterized by co-responding changes in mRNA expression levels. These units of genes will allow the generation of hypotheses about respective functional interrelationships. Thus, the focus of analysis currently moves from well-established functional assignment through comparison of protein and DNA sequences towards analysis of transcriptional co-response. Tools that allow deducing common control of gene expression have the potential to complement and extend routine BLAST comparisons, because gene function may be inferred from common transcriptional control.'),
(71269, 2004, 'bio', 'Performance of an iterated T-HMM for homology detection', 'Qian, Bin|Goldstein, Richard A', 'Biophysics Research Division, University of Michigan, Ann Arbor, MI 48109-1055, USA.|Biophysics Research Division, University of Michigan, Ann Arbor, MI 48109-1055, USA.', 'United States|United States', 0, 'Algorithms|Amino Acid Sequence|Evolution, Molecular|Markov Chains|Models, Chemical|Models, Statistical|Molecular Sequence Data|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Sequence Homology, Amino Acid|Software', 'Comparative Study', '10.1093/bioinformatics/bth181', '15044240', 'Much information about new protein sequences is derived from identifying homologous proteins. Such tasks are difficult when the evolutionary relationships are distant. Some modern methods achieve better results by building a model of a set of related sequences, and then identifying new proteins that fit the model. A further advance was the development of iterative methods that refine the model as more homologs are discovered. These methods are generally limited by ad hoc methods of sequence weighting, neglect of underlying evolutionary relationships and the representation of the set with a single one-size-fits-all model. These limitations are avoided through the use of a Tree hidden Markov model (T-HMM) approach. Our previous work described how a non-iterative version of the T-HMM method could identify distant homologs with superior performance compared with other non-iterated approaches, and described how this method was particularly appropriate for being implemented as an iterative algorithm.'),
(71270, 2004, 'bio', 'LumberJack: a heuristic tool for sequence alignment exploration and phylogenetic inference', 'Lawrence, Carolyn J|Zmasek, Christian M|Dawe, R Kelly|Malmberg, Russell L', 'Department of Plant Biology, The University of Georgia, Athens 30602, USA.|Department of Plant Biology, The University of Georgia, Athens 30602, USA.|Department of Plant Biology, The University of Georgia, Athens 30602, USA.|Department of Plant Biology, The University of Georgia, Athens 30602, USA.', 'Georgia|Georgia|Georgia|Georgia', 4, 'Algorithms|Conserved Sequence|Likelihood Functions|Phylogeny|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth180', '15044241', 'LumberJack is a phylogenetic tool intended to serve two purposes: to facilitate sampling treespace to find likely tree topologies quickly, and to map phylogenetic signal onto regions of an alignment in a revealing way. LumberJack creates non-random jackknifed alignments by progressively sliding a window of omission along the alignment. A neighbor-joining tree is built from the full alignment and from each jackknifed alignment, and then the likelihood for each topology (given the original full alignment) is calculated. To determine whether any of the topologies generated is significantly more likely than the others, Kishino-Hasegawa, Shimodaira-Hasegawa and ELW tests are implemented. Availability and'),
(71271, 2004, 'bio', 'A genetic algorithm for the detection of new cis-regulatory modules in sets of coregulated genes', 'Aerts, Stein|Van Loo, Peter|Moreau, Yves|De Moor, Bart', 'Department of Electrical Engineering (ESAT-SCD), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Heverlee (Leuven), Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering (ESAT-SCD), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Heverlee (Leuven), Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering (ESAT-SCD), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Heverlee (Leuven), Belgium. stein.aerts@esat.kuleuven.ac.be|Department of Electrical Engineering (ESAT-SCD), Katholieke Universiteit Leuven, Kasteelpark Arenberg 10, 3001 Heverlee (Leuven), Belgium. stein.aerts@esat.kuleuven.ac.be', 'Belgium|Belgium|Belgium|Belgium', 0, 'Algorithms|Chromosome Mapping|Gene Expression Profiling|Gene Expression Regulation|Genes, Regulator|Models, Genetic|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bth179', '15044242', 'The implementation of a genetic algorithm is described that provides a fast method of searching for the optimal combination of transcription factor binding sites in a set of regulatory sequences.'),
(71272, 2004, 'bio', 'Quantitative characterization of the transcriptional regulatory network in the yeast cell cycle', 'Chen, Hong-Chu|Lee, Hsiao-Ching|Lin, Tsai-Yun|Li, Wen-Hsiung|Chen, Bor-Sen', 'Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.|Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.|Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.|Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.|Department of Electrical Engineering, National Tsing Hua University, Hsinchu, Taiwan.', '-|-|-|-|-', 0, 'Algorithms|Cell Cycle Proteins|Computer Simulation|Gene Expression Profiling|Gene Expression Regulation, Fungal|Models, Biological|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Signal Transduction|Transcription Factors', 'Comparative Study', '10.1093/bioinformatics/bth178', '15044243', 'Genome-wide gene expression programs have been monitored and analyzed in the yeast Saccharomyces cerevisiae, but how cells regulate global gene expression programs in response to environmental changes is still far from being understood. We present a systematic approach to quantitatively characterize the transcriptional regulatory network of the yeast cell cycle. For the interpretative purpose, 20 target genes were selected because their expression patterns fluctuated in a periodic manner concurrent with the cell cycle and peaked at different phases. In addition to the most significant five possible regulators of each specific target gene, the expression pattern of each target gene affected by synergy of the regulators during the cell cycle was characterized. Our first step includes modeling the dynamics of gene expression and extracting the transcription rate from a time-course microarray data. The second step embraces finding the regulators that possess a high correlation with the transcription rate of the target gene, and quantifying the regulatory abilities of the identified regulators.'),
(71273, 2004, 'bio', 'Supervised cluster analysis for microarray data based on multivariate Gaussian mixture', 'Qu, Yi|Xu, Shizhong', 'Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA.|Department of Botany and Plant Sciences, University of California, Riverside, CA 92521, USA.', 'United States|United States', 0, 'Algorithms|Artificial Intelligence|Cell Cycle Proteins|Cluster Analysis|Gene Expression Profiling|Models, Genetic|Models, Statistical|Multivariate Analysis|Normal Distribution|Oligonucleotide Array Sequence Analysis|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth177', '15044244', 'Grouping genes having similar expression patterns is called gene clustering, which has been proved to be a useful tool for extracting underlying biological information of gene expression data. Many clustering procedures have shown success in microarray gene clustering, most of them belong to the family of heuristic clustering algorithms. Model-based algorithms are alternative clustering algorithms, which are based on the assumption that the whole set of microarray data is a finite mixture of a certain type of distributions with different parameters. Application of the model-based algorithms to unsupervised clustering has been reported. Here, for the first time, we demonstrated the use of the model-based algorithm in supervised clustering of microarray data.'),
(71274, 2004, 'bio', 'A comparison of cluster analysis methods using DNA methylation data', 'Siegmund, Kimberly D|Laird, Peter W|Laird-Offringa, Ite A', 'Department of Preventive Medicine, Norris Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles 90089, USA. kims@usc.edu|Department of Preventive Medicine, Norris Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles 90089, USA. kims@usc.edu|Department of Preventive Medicine, Norris Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles 90089, USA. kims@usc.edu', 'United States|United States|United States', 0, 'Algorithms|Cluster Analysis|CpG Islands|DNA Methylation|DNA, Neoplasm|Genetic Testing|Humans|Lung Neoplasms|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth176', '15044245', 'Aberrant DNA methylation is common in cancer. DNA methylation profiles differ between tumor types and subtypes and provide a powerful diagnostic tool for identifying clusters of samples and/or genes. DNA methylation data obtained with the quantitative, highly sensitive MethyLight technology is not normally distributed, it frequently contains an excess of zeros. Established tools to analyze this type of data do not exist. Here, we evaluate a variety of methods for cluster analysis to determine which is most reliable.'),
(71275, 2004, 'bio', 'Simultaneous search for multiple QTL using the global optimization algorithm DIRECT', 'Ljungberg, K|Holmgren, S|Carlborg, O', 'Information Technology, Division of Scientific Computing, Uppsala University, P.O. Box 337,751 05 Uppsala, Sweden. Kajsa.Ljungberg@it.uu.se|Information Technology, Division of Scientific Computing, Uppsala University, P.O. Box 337,751 05 Uppsala, Sweden. Kajsa.Ljungberg@it.uu.se|Information Technology, Division of Scientific Computing, Uppsala University, P.O. Box 337,751 05 Uppsala, Sweden. Kajsa.Ljungberg@it.uu.se', 'Sweden|Sweden|Sweden', 52, 'Algorithms|Chromosome Mapping|Pattern Recognition, Automated|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software', 'Comparative Study', '10.1093/bioinformatics/bth175', '15044246', 'A simultaneous search is necessary for maximizing the power to detect epistatic quantitative trait loci (QTL). The computational complexity demands that the traditional exhaustive search be replaced by a more efficient global optimization algorithm.'),
(71276, 2004, 'bio', 'Defining transcription modules using large-scale gene expression data', 'Ihmels, Jan|Bergmann, Sven|Barkai, Naama', 'Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.|Department of Molecular Genetics, Weizmann Institute of Science, Rehovot, Israel.', 'Israel|Israel|Israel', 243, 'Algorithms|Cluster Analysis|Gene Expression Profiling|Gene Expression Regulation, Fungal|Genes, Regulator|Proteome|Saccharomyces cerevisiae Proteins|Sequence Analysis, Protein|Transcription, Genetic', 'Comparative Study', '10.1093/bioinformatics/bth166', '15044247', 'Large-scale gene expression data comprising a variety of cellular conditions hold the promise of a global view on the transcription program. While conventional clustering algorithms have been successfully applied to smaller datasets, the utility of many algorithms for the analysis of large-scale data is limited by their inability to capture combinatorial and condition-specific co-regulation. In addition, there is an increasing need to integrate the rapidly accumulating body of other high-throughput biological data with the expression analysis. In a previous work, we introduced the signature algorithm, which overcomes the problems of conventional clustering and allows for intuitive integration of additional biological data. However, this approach is constrained by the comprehensiveness of relevant external data and its lacking ability to capture hierarchical modularity.'),
(71277, 2004, 'bio', 'Phylogenetic trees based on gene content', 'Huson, Daniel H|Steel, Mike', 'Center for Bioinformatics, Tübingen University, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de|Center for Bioinformatics, Tübingen University, Sand 14, 72076 Tübingen, Germany. huson@informatik.uni-tuebingen.de', 'Germany|Germany', 0, 'Algorithms|Chromosome Mapping|Computer Simulation|Evolution, Molecular|Genetic Variation|Likelihood Functions|Models, Genetic|Models, Statistical|Phylogeny|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth198', '15044248', 'Comparing gene content between species can be a useful approach for reconstructing phylogenetic trees. In this paper, we derive a maximum-likelihood estimation of evolutionary distance between species under a simple model of gene genesis and gene loss. Using simulated data on a biological tree with 107 taxa (and on a number of randomly generated trees), we compare the accuracy of tree reconstruction using this ML distance measure to an earlier ad hoc distance. We then compare these distance-based approaches to a character-based tree reconstruction method (Dollo parsimony) which seems well suited to the analysis of gene content data. To simplify simulations, we give a formal proof of the well-known fact that the Dollo parsimony score is independent of the choice of root. Our results show a consistent trend, with the character-based method and ML distance measure outperforming the earlier ad hoc distance method.'),
(71278, 2004, 'bio', 'AliasServer: a web server to handle multiple aliases used to refer to proteins', 'Iragne, Florian|Barré, Aurélien|Goffard, Nicolas|De Daruvar, Antoine', 'Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.|Centre de Bioinformatique Bordeaux, Université V. Segalen Bordeaux 2, 146 rue Léo Saignat, 33076 Bordeaux Cedex, France.', 'France|France|France|France', 19, 'Algorithms|Database Management Systems|Databases, Protein|Documentation|Information Storage and Retrieval|Internet|Natural Language Processing|Proteins|Sequence Alignment|Sequence Analysis, Protein|Software|User-Computer Interface|Vocabulary, Controlled', 'Journal Article', '10.1093/bioinformatics/bth241', '15059813', 'AliasServer provides services that facilitate the assembly of data or datasets that make use of different identifiers for refering to the same protein. This resource relies on a database which contains, for a given organism, a non-redundant list of protein sequences associated with a set of aliases.'),
(71279, 2004, 'bio', 'Estimating and comparing the rates of gene discovery and expressed sequence tag (EST) frequencies in EST surveys', 'Susko, Edward|Roger, Andrew J', 'Genome Atlantic, Department of Mathematics and Statistics, Dahlhousie University, Nova Scotia, Canada. susko@mathstat.dal.ca|Genome Atlantic, Department of Mathematics and Statistics, Dahlhousie University, Nova Scotia, Canada. susko@mathstat.dal.ca', 'Canada|Canada', 12, 'Algorithms|Chromosome Mapping|Expressed Sequence Tags|Gene Expression Profiling|Gene Library|Models, Genetic|Models, Statistical|Sequence Alignment|Sequence Analysis, DNA|Sequence Homology, Nucleic Acid', 'Comparative Study', '10.1093/bioinformatics/bth239', '15059814', 'Expressed sequence tag (EST) surveys are an efficient way to characterize large numbers of genes from an organism. The rate of gene discovery in an EST survey depends on the degree of redundancy of the cDNA libraries from which sequences are obtained. However, few statistical methods have been developed to assess and compare redundancies of various libraries from preliminary EST surveys.'),
(71280, 2004, 'bio', 'INCA: synonymous codon usage analysis and clustering by means of self-organizing map', 'Supek, Fran|Vlahovicek, Kristian', 'Department of Molecular Biology, Division of Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia.|Department of Molecular Biology, Division of Biology, Faculty of Science, Zagreb University, Rooseveltov trg 6, 10000 Zagreb, Croatia.', 'Croatia|Croatia', 45, 'Algorithms|Chromosome Mapping|Cluster Analysis|Codon|Computer Graphics|Internet|Neural Networks (Computer)|Pattern Recognition, Automated|Sequence Alignment|Sequence Analysis, DNA|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth238', '15059815', 'INteractive Codon usage Analysis (INCA) provides an array of features useful in analysis of synonymous codon usage in whole genomes. In addition to computing codon frequencies and several usage indices, such as codon bias, effective Nc and CAI, the primary strength of INCA has numerous options for the interactive graphical display of calculated values, thus allowing visual detection of various trends in codon usage. Finally, INCA includes a specific unsupervised neural network algorithm, the self-organizing map, used for gene clustering according to the preferred utilization of codons.'),
(71281, 2004, 'bio', 'Spot shape modelling and data transformations for microarrays', 'Ekstrøm, Claus Thorn|Bak, Søren|Kristensen, Charlotte|Rudemo, Mats', 'Department of Mathematics and Physics, Center of Molecular Plant Physiology, Royal Veterinary and Agricultural University, Thorvaldsensvej, Fredriksberg, Denmark. ekstrom@dina.kvl.dk|Department of Mathematics and Physics, Center of Molecular Plant Physiology, Royal Veterinary and Agricultural University, Thorvaldsensvej, Fredriksberg, Denmark. ekstrom@dina.kvl.dk|Department of Mathematics and Physics, Center of Molecular Plant Physiology, Royal Veterinary and Agricultural University, Thorvaldsensvej, Fredriksberg, Denmark. ekstrom@dina.kvl.dk|Department of Mathematics and Physics, Center of Molecular Plant Physiology, Royal Veterinary and Agricultural University, Thorvaldsensvej, Fredriksberg, Denmark. ekstrom@dina.kvl.dk', 'Denmark|Denmark|Denmark|Denmark', 28, 'Algorithms|Arabidopsis|Arabidopsis Proteins|Artificial Intelligence|Gene Expression Profiling|Gene Expression Regulation, Plant|Genetic Variation|Image Interpretation, Computer-Assisted|Microscopy, Fluorescence|Models, Genetic|Models, Statistical|Oligonucleotide Array Sequence Analysis|Pattern Recognition, Automated|Photometry|Signal Processing, Computer-Assisted|Transcription Factors', 'Evaluation Studies', '10.1093/bioinformatics/bth237', '15059816', 'To study lowly expressed genes in microarray experiments, it is useful to increase the photometric gain in the scanning. However, a large gain may cause some pixels for highly expressed genes to become saturated. Spatial statistical models that model spot shapes on the pixel level may be used to infer information about the saturated pixel intensities. Other possible applications for spot shape models include data quality control and accurate determination of spot centres and spot diameters.'),
(71282, 2004, 'bio', 'TRMP: a database of therapeutically relevant multiple pathways', 'Zheng, C J|Zhou, H|Xie, B|Han, L Y|Yap, C W|Chen, Y Z', 'Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.|Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.|Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.|Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.|Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.|Department of Computational Science, National University of Singapore, Blk S17, Level 7, 3 Science Drive 2, Singapore 117543.', 'Singapore|Singapore|Singapore|Singapore|Singapore|Singapore', 14, 'Biomarkers|Database Management Systems|Databases, Factual|Disease|Information Storage and Retrieval|Internet|Multienzyme Complexes|Proteins|Signal Transduction|Therapeutics|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth233', '15059817', 'Disease processes often involve crosstalks between proteins in different pathways. Different proteins have been used as separate therapeutic targets for the same disease. Synergetic targeting of multiple targets has been explored in combination therapy of a number of diseases. Potential harmful interactions of multiple targeting have also been closely studied. To facilitate mechanistic study of drug actions and a more comprehensive understanding the relationship between different targets of the same disease, it is useful to develop a database of known therapeutically relevant multiple pathways (TRMPs). Information about non-target proteins and natural small molecules involved in these pathways also provides useful hint for searching new therapeutic targets and facilitate the understanding of how therapeutic targets interact with other molecules in performing specific tasks. The TRMPs database is designed to provide information about such multiple pathways along with related therapeutic targets, corresponding drugs/ligands, targeted disease conditions, constituent individual pathways, structural and functional information about each protein in the pathways. Cross links to other databases are also introduced to facilitate the access of information about individual pathways and proteins.'),
(71283, 2004, 'bio', 'Arby: automatic protein structure prediction using profile-profile alignment and confidence measures', 'von Ohsen, Niklas|Sommer, Ingolf|Zimmer, Ralf|Lengauer, Thomas', 'Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, Sankt Augustin, 53754, Germany. Niklas.von-Oehsen@scai.fhg.de|Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, Sankt Augustin, 53754, Germany. Niklas.von-Oehsen@scai.fhg.de|Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, Sankt Augustin, 53754, Germany. Niklas.von-Oehsen@scai.fhg.de|Institute for Algorithms and Scientific Computing (SCAI), Fraunhofer Gesellschaft, Schloss Birlinghoven, Sankt Augustin, 53754, Germany. Niklas.von-Oehsen@scai.fhg.de', 'Germany|Germany|Germany|Germany', 0, 'Algorithms|Computer Simulation|Models, Molecular|Protein Conformation|Protein Folding|Protein Structure, Secondary|Proteins|Reproducibility of Results|Sensitivity and Specificity|Sequence Alignment|Sequence Analysis, Protein|Software', 'Comparative Study', '10.1093/bioinformatics/bth232', '15059818', 'Arby is a new server for protein structure prediction that combines several homology-based methods for predicting the three-dimensional structure of a protein, given its sequence. The methods used include a threading approach, which makes use of structural information, and a profile-profile alignment approach that incorporates secondary structure predictions. The combination of the different methods with the help of empirically derived confidence measures affords reliable template selection.'),
(71284, 2004, 'bio', 'Pelican: pedigree editor for linkage computer analysis', 'Dudbridge, Frank|Carver, Tim|Williams, Gary W', 'MRC Rosalind Franklin Centre for Genomics Research, Hinxton, Cambridge CB10 1SB, UK.|MRC Rosalind Franklin Centre for Genomics Research, Hinxton, Cambridge CB10 1SB, UK.|MRC Rosalind Franklin Centre for Genomics Research, Hinxton, Cambridge CB10 1SB, UK.', 'United Kingdom|United Kingdom|United Kingdom', 12, 'Chromosome Mapping|Computer Graphics|Documentation|Information Storage and Retrieval|Internet|Linkage Disequilibrium|Pedigree|Software|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth231', '15059819', 'Linkage analysis software requires an input text file that describes the structure of the pedigrees to be analysed. Manual creation of these files is tedious and error-prone, and a graphical input tool is desirable. This is currently only available in commercial packages that include much greater functionality. We have therefore developed Pelican, a lightweight graphical pedigree editor for rapid construction of linkage pedigree files and diagrams.'),
(71285, 2004, 'bio', 'BioMercator: integrating genetic maps and QTL towards discovery of candidate genes', 'Arcade, Anne|Labourdette, Aymeric|Falque, Matthieu|Mangin, Brigitte|Chardon, Fabien|Charcosset, Alain|Joets, Johann', 'UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.|UMR, INRA UPS-XI INAPG CNRS Génétique Végétale, Ferme du Moulon, 91190 Gif-sur-Yvette, France.', 'France|France|France|France|France|France|France', 262, 'Algorithms|Chromosome Mapping|Computer Graphics|Consensus Sequence|Quantitative Trait Loci|Sequence Alignment|Sequence Analysis, DNA|Software|Systems Integration|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth230', '15059820', 'Breeding programs face the challenge of integrating information from genomics and from quantitative trait loci (QTL) analysis in order to identify genomic sequences controlling the variation of important traits. Despite the development of integrative databases, building a consensus map of genes, QTL and other loci gathered from multiple maps remains a manual and tedious task. Nevertheless, this is a critical step to reveal co-locations between genes and QTL. Another important matter is to determine whether QTL linked to same traits or related ones is detected in independent experiments and located in the same region, and represents a single locus or not. Statistical tools such as meta-analysis can be used to answer this question. BioMercator has been developed to automate map compilation and QTL meta-analysis, and to visualize co-locations between genes and QTL through a graphical interface.'),
(71286, 2004, 'bio', 'Drawing phylogenetic trees in LATEX and Microsoft Word', 'Savva, George|Conn, Jenn|Dicks, Jo', 'Computational Biology Research, John Innes Centre, Colney Lane, Norwich, Norfolk, UK.|Computational Biology Research, John Innes Centre, Colney Lane, Norwich, Norfolk, UK.|Computational Biology Research, John Innes Centre, Colney Lane, Norwich, Norfolk, UK.', 'United Kingdom|United Kingdom|United Kingdom', 0, 'Computer Graphics|Documentation|Pedigree|Phylogeny|Programming Languages|Software|User-Computer Interface|Word Processing', 'Evaluation Studies', '10.1093/bioinformatics/bth228', '15059821', 'newicktree is a PSTricks-based LATEX package which enables phylogenetic trees described in the Newick format to be drawn directly into LATEX documents. mswordtree is a macro for producing phylogenetic trees using the drawing elements available in Microsoft Word.'),
(71287, 2004, 'bio', 'PedSplit: pedigree management for stratified analysis', 'Lanktree, M B|VanderBeek, L|Macciardi, F M|Kennedy, J L', 'Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, 250 College Street, Toronto M5T 1R8, Canada.|Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, 250 College Street, Toronto M5T 1R8, Canada.|Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, 250 College Street, Toronto M5T 1R8, Canada.|Neurogenetics Section, Centre for Addiction and Mental Health, Department of Psychiatry, University of Toronto, 250 College Street, Toronto M5T 1R8, Canada.', 'Canada|Canada|Canada|Canada', 7, 'Algorithms|Chromosome Mapping|DNA Mutational Analysis|Gene Frequency|Genetic Predisposition to Disease|Genetic Testing|Genetic Variation|Haplotypes|Internet|Linkage Disequilibrium|Pedigree|Risk Assessment|Risk Factors|Sex Factors|Software', 'Journal Article', '10.1093/bioinformatics/bth224', '15059823', 'PedSplit facilitates pedigree management for gene-gene interaction and sex specific tests for increased homogeneity within subgroups. PedSplit also provides a simple approach for calculating haplotype relative risk and generating internal controls.'),
(71288, 2004, 'bio', 'SPrCY: comparison of structural predictions in the Saccharomyces cerevisiae genome', 'Dolinsky, T J|Burgers, P M J|Karplus, K|Baker, N A', 'Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St Louis, St Louis, MO 63110, USA.|Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St Louis, St Louis, MO 63110, USA.|Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St Louis, St Louis, MO 63110, USA.|Department of Biochemistry and Molecular Biophysics, Center for Computational Biology, Washington University in St Louis, St Louis, MO 63110, USA.', 'United States|United States|United States|United States', 0, 'Algorithms|Chromosome Mapping|Databases, Genetic|Information Storage and Retrieval|Internet|Models, Molecular|Protein Conformation|Saccharomyces cerevisiae|Saccharomyces cerevisiae Proteins|Sequence Alignment|Sequence Analysis, Protein|Structure-Activity Relationship|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth223', '15059824', 'SPrCY is a web-accessible database which provides comparison of structure prediction results for the Saccharomyces cerevisiae genome. This web service offers the ability to search, analyze and compare the yeast structural predictions from sequence-only (Superfamily, PDBAA BLAST and Pfam) and sequence-structure-based (SAM-T02, 3D-PSSM, mGenTHREADER) methods.'),
(71289, 2004, 'bio', 'A database for management of gene expression data in situ', 'Poustelnikova, Ekaterina|Pisarev, Andrei|Blagov, Maxim|Samsonova, Maria|Reinitz, John', 'St. Petersburg State Polytechnic University, 29, Polytehnicheskaya ul., St Petersburg, 195251, Russia.|St. Petersburg State Polytechnic University, 29, Polytehnicheskaya ul., St Petersburg, 195251, Russia.|St. Petersburg State Polytechnic University, 29, Polytehnicheskaya ul., St Petersburg, 195251, Russia.|St. Petersburg State Polytechnic University, 29, Polytehnicheskaya ul., St Petersburg, 195251, Russia.|St. Petersburg State Polytechnic University, 29, Polytehnicheskaya ul., St Petersburg, 195251, Russia.', '-|-|-|-|-', 0, 'Animals|Body Patterning|Database Management Systems|Databases, Genetic|Drosophila|Drosophila Proteins|Gene Expression Profiling|Gene Expression Regulation, Developmental|Information Storage and Retrieval|Internet|Morphogenesis|Tissue Distribution|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth222', '15059825', 'To create a spatiotemporal atlas of Drosophila segmentation gene expression at cellular resolution.'),
(71290, 2004, 'bio', 'Design and implementation of a mosquito database through an entomological ontology', 'Koum, Guillaume|Yekel, Augustin|Ndifon, Bengyella|Simard, Frédéric', 'Laborima, Ecole Polytechnique B.P 8390 Yaounde, Cameroon. g_koum@yahoo.fr|Laborima, Ecole Polytechnique B.P 8390 Yaounde, Cameroon. g_koum@yahoo.fr|Laborima, Ecole Polytechnique B.P 8390 Yaounde, Cameroon. g_koum@yahoo.fr|Laborima, Ecole Polytechnique B.P 8390 Yaounde, Cameroon. g_koum@yahoo.fr', 'Cameroon|Cameroon|Cameroon|Cameroon', 0, 'Animals|Anopheles|Culicidae|Database Management Systems|Databases, Factual|Databases, Genetic|Documentation|Entomology|Geographic Information Systems|Geography|Humans|Information Storage and Retrieval|Insect Vectors|Malaria|User-Computer Interface', 'Journal Article', '10.1093/bioinformatics/bth221', '15059826', 'There have been constant changes in the biology and behavior of the vector and parasite involved in the transmission of malaria. There is limited interest in developing new technologies and procedures for controlling the underlying factors of this threat, which poses an enormous challenge to health systems. To understand the various vector species and their interrelations is of prime importance in understanding the transmission mechanisms of malaria in order to react efficiently. To attain this objective, we have used an ontological approach to producing a database that we consider to be our own contribution in helping to control malaria vectors if eradication has been unsuccessful in the previous control campaign.'),
(71291, 2004, 'bio', 'SCANMS: adjusting for multiple comparisons in sliding window neutrality tests', 'Ardell, David H', 'Department of Cell and Molecular Biology, Biomedical Center, Uppsala University, Box 596, SE-751 24 Uppsala, Sweden.', 'Sweden', 9, 'Algorithms|Internet|Numerical Analysis, Computer-Assisted|Sequence Alignment|Sequence Analysis, DNA|Software', 'Journal Article', '10.1093/bioinformatics/bth187', '15059827', 'A Perl utility called SCANMS was written that operates on parametric bootstrap data generated by Hudsons simulator MS. SCANMS simulates sliding window analysis of Tajimas D or Fu and Lis D(*) or F(*) over the replicates and generates the empirical joint distribution of window minima and maxima. This distribution may then be used to calculate achieved significance values or significance cutoffs that account for multiple comparisons in sliding window analysis of real data.'),
(71292, 2004, 'bio', 'ProMode: a database of normal mode analyses on protein molecules with a full-atom model', 'Wako, Hiroshi|Kato, Masaki|Endo, Shigeru', 'School of Social Sciences, Waseda University, Tokyo 169-8050, Japan. wako@waseda.jp|School of Social Sciences, Waseda University, Tokyo 169-8050, Japan. wako@waseda.jp|School of Social Sciences, Waseda University, Tokyo 169-8050, Japan. wako@waseda.jp', 'Japan|Japan|Japan', 37, 'Computer Graphics|Computer Simulation|Database Management Systems|Databases, Protein|Information Storage and Retrieval|Models, Chemical|Models, Molecular|Protein Conformation|Protein Structure, Tertiary|Proteins|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth197', '15059828', 'Although information from protein dynamics simulation is important to understand principles of architecture of a protein structure and its function, simulations such as molecular dynamics and Monte Carlo are very CPU-intensive. Although the ability of normal mode analysis (NMA) is limited because of the need for a harmonic approximation on which NMA is based, NMA is adequate to carry out routine analyses on many proteins to compute aspects of the collective motions essential to protein dynamics and function. Furthermore, it is hoped that realistic animations of the protein dynamics can be observed easily without expensive software and hardware, and that the dynamic properties for various proteins can be compared with each other.'),
(71293, 2004, 'bio', 'TIP: protein backtranslation aided by genetic algorithms', 'Moreira, Andrés|Maass, Alejandro', 'Centro de Modelamiento Matemático and Departamento de Ingeniería Matemática FCFM, U. de Chile, Casilla 170/3-Correo 3, Santiago, Chile. anmoreir@dim.uchile.cl|Centro de Modelamiento Matemático and Departamento de Ingeniería Matemática FCFM, U. de Chile, Casilla 170/3-Correo 3, Santiago, Chile. anmoreir@dim.uchile.cl', 'Chile|Chile', 0, 'Algorithms|Models, Genetic|Protein Biosynthesis|Proteins|Sequence Alignment|Sequence Analysis, DNA|Sequence Analysis, Protein|Software', 'Journal Article', '10.1093/bioinformatics/bth204', '15059829', 'Several applications require the backtranslation of a protein sequence into a nucleic acid sequence. The degeneracy of the genetic code makes this process ambiguous, moreover, not every translation is equally viable. The usual answer is to mimic the codon usage of the target species, however, this does not capture all the relevant features of the genomic styles from different taxa. The program TIP  Traducción Inversa de Proteínas) applies genetic algorithms to improve the backtranslation, by minimizing the difference of some coding statistics with respect to their average value in the target.'),
(71294, 2004, 'bio', 'Fragment assembly with short reads', 'Chaisson, Mark|Pevzner, Pavel|Tang, Haixu', 'Bioinformatics Program, University of California San Diego, La Jolla, CA 92093, USA. mchaisso@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, CA 92093, USA. mchaisso@bioinf.ucsd.edu|Bioinformatics Program, University of California San Diego, La Jolla, CA 92093, USA. mchaisso@bioinf.ucsd.edu', 'United States|United States|United States', 135, 'Algorithms|Base Sequence|Contig Mapping|Feasibility Studies|Gene Expression Profiling|Molecular Sequence Data|Sequence Alignment|Sequence Analysis, DNA', 'Comparative Study', '10.1093/bioinformatics/bth205', '15059830', 'Current DNA sequencing technology produces reads of about 500-750 bp, with typical coverage under 10x. New sequencing technologies are emerging that produce shorter reads (length 80-200 bp) but allow one to generate significantly higher coverage (30x and higher) at low cost. Modern assembly programs and error correction routines have been tuned to work well with current read technology but were not designed for assembly of short reads.'),
(71295, 2004, 'bio', 'Molecular Genetics Information System (MOLGENIS): alternatives in developing local experimental genomics databases', 'Swertz, Morris A|De Brock, E O|Van Hijum, Sacha A F T|De Jong, Anne|Buist, Girbe|Baerends, Richard J S|Kok, Jan|Kuipers, Oscar P|Jansen, Ritsert C', 'Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl|Groningen Bioinformatics Center, Faculty of Medical Sciences and Faculty of Mathematics and Natural Sciences, University of Groningen, Groningen, The Netherlands. m.a.swertz@cs.rug.nl', 'Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Netherlands|Neth', 22, 'Computational Biology|Database Management Systems|Databases, Genetic|Decision Support Techniques|Genomics|Information Storage and Retrieval|Molecular Biology|Needs Assessment|Research Design|Technology Assessment, Biomedical|User-Computer Interface', 'Comparative Study', '10.1093/bioinformatics/bth206', '15059831', 'Genomic research laboratories need adequate infrastructure to support management of their data production and research workflow. But what makes infrastructure adequate? A lack of appropriate criteria makes any decision on buying or developing a system difficult. Here, we report on the decision process for the case of a molecular genetics group establishing a microarray laboratory.');
