@article {18508806, title = {GEPAS, a web-based tool for microarray data analysis and interpretation}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, note = {

Tarraga, Joaquin Medina, Ignacio Carbonell, Jose Huerta-Cepas, Jaime Minguez, Pablo Alloza, Eva Al-Shahrour, Fatima Vegas-Azcarate, Susana Goetz, Stefan Escobar, Pablo Garcia-Garcia, Francisco Conesa, Ana Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2008 Jul 1;36(Web Server issue):W308-14. Epub 2008 May 28.

}, pages = {W308-14}, abstract = {

Gene Expression Profile Analysis Suite (GEPAS) is one of the most complete and extensively used web-based packages for microarray data analysis. During its more than 5 years of activity it has continuously been updated to keep pace with the state-of-the-art in the changing microarray data analysis arena. GEPAS offers diverse analysis options that include well established as well as novel algorithms for normalization, gene selection, class prediction, clustering and functional profiling of the experiment. New options for time-course (or dose-response) experiments, microarray-based class prediction, new clustering methods and new tests for differential expression have been included. The new pipeliner module allows automating the execution of sequential analysis steps by means of a simple but powerful graphic interface. An extensive re-engineering of GEPAS has been carried out which includes the use of web services and Web 2.0 technology features, a new user interface with persistent sessions and a new extended database of gene identifiers. GEPAS is nowadays the most quoted web tool in its field and it is extensively used by researchers of many countries and its records indicate an average usage rate of 500 experiments per day. GEPAS, is available at http://www.gepas.org.

}, keywords = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18508806}, author = {Tarraga, J. and Medina, Ignacio and Carbonell, J. and Huerta-Cepas, J. and Minguez, P. and Alloza, E. and Fatima Al-Shahrour and Vegas-Azcarate, S. and Goetz, S. and Escobar, P. and Garcia-Garcia, F. and A. Conesa and Montaner, D. and Dopazo, J.} } @article {18238804, title = {Interoperability with Moby 1.0{\textendash}it{\textquoteright}s better than sharing your toothbrush!}, journal = {Brief Bioinform}, volume = {9}, number = {3}, year = {2008}, note = {

BioMoby Consortium Wilkinson, Mark D Senger, Martin Kawas, Edward Bruskiewich, Richard Gouzy, Jerome Noirot, Celine Bardou, Philippe Ng, Ambrose Haase, Dirk Saiz, Enrique de Andres Wang, Dennis Gibbons, Frank Gordon, Paul M K Sensen, Christoph W Carrasco, Jose Manuel Rodriguez Fernandez, Jose M Shen, Lixin Links, Matthew Ng, Michael Opushneva, Nina Neerincx, Pieter B T Leunissen, Jack A M Ernst, Rebecca Twigger, Simon Usadel, Bjorn Good, Benjamin Wong, Yan Stein, Lincoln Crosby, William Karlsson, Johan Royo, Romina Parraga, Ivan Ramirez, Sergio Gelpi, Josep Lluis Trelles, Oswaldo Pisano, David G Jimenez, Natalia Kerhornou, Arnaud Rosset, Roman Zamacola, Leire Tarraga, Joaquin Huerta-Cepas, Jaime Carazo, Jose Maria Dopazo, Joaquin Guigo, Roderic Navarro, Arcadi Orozco, Modesto Valencia, Alfonso Claros, M Gonzalo Perez, Antonio J Aldana, Jose Rojano, M Mar Fernandez-Santa Cruz, Raul Navas, Ismael Schiltz, Gary Farmer, Andrew Gessler, Damian Schoof, Heiko Groscurth, Andreas Research Support, Non-U.S. Gov{\textquoteright}t Review England Briefings in bioinformatics Brief Bioinform. 2008 May;9(3):220-31. Epub 2008 Jan 31.

}, pages = {220-31}, abstract = {

The BioMoby project was initiated in 2001 from within the model organism database community. It aimed to standardize methodologies to facilitate information exchange and access to analytical resources, using a consensus driven approach. Six years later, the BioMoby development community is pleased to announce the release of the 1.0 version of the interoperability framework, registry Application Programming Interface and supporting Perl and Java code-bases. Together, these provide interoperable access to over 1400 bioinformatics resources worldwide through the BioMoby platform, and this number continues to grow. Here we highlight and discuss the features of BioMoby that make it distinct from other Semantic Web Service and interoperability initiatives, and that have been instrumental to its deployment and use by a wide community of bioinformatics service providers. The standard, client software, and supporting code libraries are all freely available at http://www.biomoby.org/.

}, keywords = {Computational Biology/*methods *Database Management Systems *Databases, Factual Information Storage and Retrieval/*methods *Internet *Programming Languages Systems Integration}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18238804}, author = {Wilkinson, M. D. and Senger, M. and Kawas, E. and Bruskiewich, R. and Gouzy, J. and Noirot, C. and Bardou, P. and Ng, A. and Haase, D. and Saiz Ede, A. and Wang, D. and Gibbons, F. and Gordon, P. M. and Sensen, C. W. and Carrasco, J. M. and Fernandez, J. M. and Shen, L. and Links, M. and Ng, M. and Opushneva, N. and Neerincx, P. B. and Leunissen, J. A. and Ernst, R. and Twigger, S. and Usadel, B. and Good, B. and Wong, Y. and Stein, L. and Crosby, W. and Karlsson, J. and Royo, R. and Parraga, I. and Ramirez, S. and Gelpi, J. L. and Trelles, O. and Pisano, D. G. and Jimenez, N. and Kerhornou, A. and Rosset, R. and Zamacola, L. and Tarraga, J. and Huerta-Cepas, J. and Carazo, J. M. and Dopazo, J. and R. Guigo and Navarro, A. and Orozco, M. and Valencia, A. and Claros, M. G. and Perez, A. J. and Aldana, J. and Rojano, M. M. and Fernandez-Santa Cruz, R. and Navas, I. and Schiltz, G. and Farmer, A. and Gessler, D. and Schoof, H. and Groscurth, A.} } @article {17962297, title = {PhylomeDB: a database for genome-wide collections of gene phylogenies}, journal = {Nucleic Acids Res}, volume = {36}, number = {Database issue}, year = {2008}, note = {Huerta-Cepas, Jaime Bueno, Anibal Dopazo, Joaquin Gabaldon, Toni Historical Article Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2008 Jan;36(Database issue):D491-6. Epub 2007 Oct 25.}, pages = {D491-6}, abstract = {The complete collection of evolutionary histories of all genes in a genome, also known as phylome, constitutes a valuable source of information. The reconstruction of phylomes has been previously prevented by large demands of time and computer power, but is now feasible thanks to recent developments in computers and algorithms. To provide a publicly available repository of complete phylomes that allows researchers to access and store large-scale phylogenomic analyses, we have developed PhylomeDB. PhylomeDB is a database of complete phylomes derived for different genomes within a specific taxonomic range. All phylomes in the database are built using a high-quality phylogenetic pipeline that includes evolutionary model testing and alignment trimming phases. For each genome, PhylomeDB provides the alignments, phylogentic trees and tree-based orthology predictions for every single encoded protein. The current version of PhylomeDB includes the phylomes of Human, the yeast Saccharomyces cerevisiae and the bacterium Escherichia coli, comprising a total of 32 289 seed sequences with their corresponding alignments and 172 324 phylogenetic trees. PhylomeDB can be publicly accessed at http://phylomedb.bioinfo.cipf.es.}, keywords = {Ancient Humans *Phylogeny Proteins/classification/genetics Saccharomyces cerevisiae/classification/genetics Sequence Alignment, Base Sequence Escherichia coli/classification/genetics Genes *Genomics History}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17962297}, author = {Huerta-Cepas, J. and Bueno, A. and Dopazo, J. and Gabald{\'o}n, T.} } @article {17584915, title = {Evidence for systems-level molecular mechanisms of tumorigenesis}, journal = {BMC Genomics}, volume = {8}, year = {2007}, note = {Hernandez, Pilar Huerta-Cepas, Jaime Montaner, David Al-Shahrour, Fatima Valls, Joan Gomez, Laia Capella, Gabriel Dopazo, Joaquin Pujana, Miguel Angel Research Support, Non-U.S. Gov{\textquoteright}t England BMC genomics BMC Genomics. 2007 Jun 20;8:185.}, pages = {185}, abstract = {BACKGROUND: Cancer arises from the consecutive acquisition of genetic alterations. Increasing evidence suggests that as a consequence of these alterations, molecular interactions are reprogrammed in the context of highly connected and regulated cellular networks. Coordinated reprogramming would allow the cell to acquire the capabilities for malignant growth. RESULTS: Here, we determine the coordinated function of cancer gene products (i.e., proteins encoded by differentially expressed genes in tumors relative to healthy tissue counterparts, hereafter referred to as "CGPs") defined as their topological properties and organization in the interactome network. We show that CGPs are central to information exchange and propagation and that they are specifically organized to promote tumorigenesis. Centrality is identified by both local (degree) and global (betweenness and closeness) measures, and systematically appears in down-regulated CGPs. Up-regulated CGPs do not consistently exhibit centrality, but both types of cancer products determine the overall integrity of the network structure. In addition to centrality, down-regulated CGPs show topological association that correlates with common biological processes and pathways involved in tumorigenesis. CONCLUSION: Given the current limited coverage of the human interactome, this study proposes that tumorigenesis takes place in a specific and organized way at the molecular systems-level and suggests a model that comprises the precise down-regulation of groups of topologically-associated proteins involved in particular functions, orchestrated with the up-regulation of specific proteins.}, keywords = {*Cell Transformation, Biological Models, Genetic Models, Messenger/metabolism Signal Transduction Systems Biology, Neoplastic *Gene Expression Profiling *Gene Expression Regulation, Neoplastic Humans Male Models, Statistical Neoplasm Proteins/*physiology Neoplasms/etiology/*genetics Prostatic Neoplasms/genetics Protein Interaction Mapping RNA}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17584915}, author = {Hernandez, P. and Huerta-Cepas, J. and Montaner, D. and Fatima Al-Shahrour and Valls, J. and Gomez, L. and Capella, G. and Dopazo, J. and Pujana, M. A.} } @article {17407596, title = {From genes to functional classes in the study of biological systems}, journal = {BMC Bioinformatics}, volume = {8}, year = {2007}, note = {

Al-Shahrour, Fatima Arbiza, Leonardo Dopazo, Hernan Huerta-Cepas, Jaime Minguez, Pablo Montaner, David Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England BMC bioinformatics BMC Bioinformatics. 2007 Apr 3;8:114.

}, pages = {114}, abstract = {

BACKGROUND: With the popularization of high-throughput techniques, the need for procedures that help in the biological interpretation of results has increased enormously. Recently, new procedures inspired in systems biology criteria have started to be developed. RESULTS: Here we present FatiScan, a web-based program which implements a threshold-independent test for the functional interpretation of large-scale experiments that does not depend on the pre-selection of genes based on the multiple application of independent tests to each gene. The test implemented aims to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes. In addition, the test does not depend on the type of the data used for obtaining significance values, and consequently different types of biologically informative terms (gene ontology, pathways, functional motifs, transcription factor binding sites or regulatory sites from CisRed) can be applied to different classes of genome-scale studies. We exemplify its application in microarray gene expression, evolution and interactomics. CONCLUSION: Methods for gene set enrichment which, in addition, are independent from the original data and experimental design constitute a promising alternative for the functional profiling of genome-scale experiments. A web server that performs the test described and other similar ones can be found at: http://www.babelomics.org.

}, keywords = {Algorithms Chromosome Mapping/*methods Computer Simulation Gene Expression Profiling/methods *Models, babelomics, Biological Multigene Family/*physiology Signal Transduction/*physiology *Software Systems Biology/*methods *User-Computer Interface}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17407596}, author = {Fatima Al-Shahrour and Arbiza, L. and H. Dopazo and Huerta-Cepas, J. and Minguez, P. and Montaner, D. and Dopazo, J.} } @article {17567924, title = {The human phylome}, journal = {Genome Biol}, volume = {8}, number = {6}, year = {2007}, note = {Huerta-Cepas, Jaime Dopazo, Hernan Dopazo, Joaquin Gabaldon, Toni Research Support, Non-U.S. Gov{\textquoteright}t England Genome biology Genome Biol. 2007;8(6):R109.}, pages = {R109}, abstract = {BACKGROUND: Phylogenomics analyses serve to establish evolutionary relationships among organisms and their genes. A phylome, the complete collection of all gene phylogenies in a genome, constitutes a valuable source of information, but its use in large genomes still constitutes a technical challenge. The use of phylomes also requires the development of new methods that help us to interpret them. RESULTS: We reconstruct here the human phylome, which includes the evolutionary relationships of all human proteins and their homologs among 39 fully sequenced eukaryotes. Phylogenetic techniques used include alignment trimming, branch length optimization, evolutionary model testing and maximum likelihood and Bayesian methods. Although differences with alternative topologies are minor, most of the trees support the Coelomata and Unikont hypotheses as well as the grouping of primates with laurasatheria to the exclusion of rodents. We assess the extent of gene duplication events and their relationship with the functional roles of the protein families involved. We find support for at least one, and probably two, rounds of whole genome duplications before vertebrate radiation. Using a novel algorithm that is independent from a species phylogeny, we derive orthology and paralogy relationships of human proteins among eukaryotic genomes. CONCLUSION: Topological variations among phylogenies for different genes are to be expected, highlighting the danger of gene-sampling effects in phylogenomic analyses. Several links can be established between the functions of gene families duplicated at certain phylogenetic splits and major evolutionary transitions in those lineages. The pipeline implemented here can be easily adapted for use in other organisms.}, keywords = {Animals *Evolution Evolution, DNA, Molecular Gene Duplication *Genome Humans *Phylogeny Proteins/genetics Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17567924}, author = {Huerta-Cepas, J. and H. Dopazo and Dopazo, J. and Gabald{\'o}n, T.} } @article {17135190, title = {PeroxisomeDB: a database for the peroxisomal proteome, functional genomics and disease}, journal = {Nucleic Acids Res}, volume = {35}, number = {Database issue}, year = {2007}, note = {Schluter, Agatha Fourcade, Stephane Domenech-Estevez, Enric Gabaldon, Toni Huerta-Cepas, Jaime Berthommier, Guillaume Ripp, Raymond Wanders, Ronald J A Poch, Olivier Pujol, Aurora Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2007 Jan;35(Database issue):D815-22. Epub 2006 Nov 28.}, pages = {D815-22}, abstract = {Peroxisomes are essential organelles of eukaryotic origin, ubiquitously distributed in cells and organisms, playing key roles in lipid and antioxidant metabolism. Loss or malfunction of peroxisomes causes more than 20 fatal inherited conditions. We have created a peroxisomal database (http://www.peroxisomeDB.org) that includes the complete peroxisomal proteome of Homo sapiens and Saccharomyces cerevisiae, by gathering, updating and integrating the available genetic and functional information on peroxisomal genes. PeroxisomeDB is structured in interrelated sections {\textquoteright}Genes{\textquoteright}, {\textquoteright}Functions{\textquoteright}, {\textquoteright}Metabolic pathways{\textquoteright} and {\textquoteright}Diseases{\textquoteright}, that include hyperlinks to selected features of NCBI, ENSEMBL and UCSC databases. We have designed graphical depictions of the main peroxisomal metabolic routes and have included updated flow charts for diagnosis. Precomputed BLAST, PSI-BLAST, multiple sequence alignment (MUSCLE) and phylogenetic trees are provided to assist in direct multispecies comparison to study evolutionary conserved functions and pathways. Highlights of the PeroxisomeDB include new tools developed for facilitating (i) identification of novel peroxisomal proteins, by means of identifying proteins carrying peroxisome targeting signal (PTS) motifs, (ii) detection of peroxisomes in silico, particularly useful for screening the deluge of newly sequenced genomes. PeroxisomeDB should contribute to the systematic characterization of the peroxisomal proteome and facilitate system biology approaches on the organelle.}, keywords = {Animals *Databases, Protein Genomics Humans Internet Mice Peroxisomal Disorders/*genetics Peroxisomes/*metabolism Protein Sorting Signals Proteome/chemistry/*genetics/*physiology Rats Saccharomyces cerevisiae Proteins/genetics/physiology Software User-Computer Interface}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17135190}, author = {Schluter, A. and Fourcade, S. and Domenech-Estevez, E. and Gabald{\'o}n, T. and Huerta-Cepas, J. and Berthommier, G. and Ripp, R. and Wanders, R. J. and Poch, O. and Pujol, A.} } @article {17452346, title = {Phylemon: a suite of web tools for molecular evolution, phylogenetics and phylogenomics}, journal = {Nucleic Acids Res}, volume = {35}, number = {Web Server issue}, year = {2007}, note = {Tarraga, Joaquin Medina, Ignacio Arbiza, Leonardo Huerta-Cepas, Jaime Gabaldon, Toni Dopazo, Joaquin Dopazo, Hernan Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2007 Jul;35(Web Server issue):W38-42. Epub 2007 Apr 22.}, pages = {W38-42}, abstract = {Phylemon is an online platform for phylogenetic and evolutionary analyses of molecular sequence data. It has been developed as a web server that integrates a suite of different tools selected among the most popular stand-alone programs in phylogenetic and evolutionary analysis. It has been conceived as a natural response to the increasing demand of data analysis of many experimental scientists wishing to add a molecular evolution and phylogenetics insight into their research. Tools included in Phylemon cover a wide yet selected range of programs: from the most basic for multiple sequence alignment to elaborate statistical methods of phylogenetic reconstruction including methods for evolutionary rates analyses and molecular adaptation. Phylemon has several features that differentiates it from other resources: (i) It offers an integrated environment that enables the direct concatenation of evolutionary analyses, the storage of results and handles required data format conversions, (ii) Once an outfile is produced, Phylemon suggests the next possible analyses, thus guiding the user and facilitating the integration of multi-step analyses, and (iii) users can define and save complete pipelines for specific phylogenetic analysis to be automatically used on many genes in subsequent sessions or multiple genes in a single session (phylogenomics). The Phylemon web server is available at http://phylemon.bioinfo.cipf.es.}, keywords = {Animals Computational Biology/*methods Databases, DNA Sequence Analysis, Genetic Evolution, Molecular Genetic Techniques Humans *Internet Models, Protein Software User-Computer Interface, Statistical *Phylogeny Programming Languages Sequence Alignment Sequence Analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=17452346}, author = {Tarraga, J. and Medina, Ignacio and Arbiza, L. and Huerta-Cepas, J. and Gabald{\'o}n, T. and Dopazo, J. and H. Dopazo} } @article {16845056, title = {Next station in microarray data analysis: GEPAS}, journal = {Nucleic Acids Res}, volume = {34}, year = {2006}, note = {

Montaner, David Tarraga, Joaquin Huerta-Cepas, Jaime Burguet, Jordi Vaquerizas, Juan M Conde, Lucia Minguez, Pablo Vera, Javier Mukherjee, Sach Valls, Joan Pujana, Miguel A G Alloza, Eva Herrero, Javier Al-Shahrour, Fatima Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W486-91.

}, pages = {W486-91}, abstract = {

The Gene Expression Profile Analysis Suite (GEPAS) has been running for more than four years. During this time it has evolved to keep pace with the new interests and trends in the still changing world of microarray data analysis. GEPAS has been designed to provide an intuitive although powerful web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-colour microarray experiments and other preprocessing options), to the final step of the functional annotation of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), and include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management. GEPAS is extensively used by researchers of many countries and its records indicate an average usage rate of 400 experiments per day. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

}, keywords = {gepas, microarray data analysis}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16845056}, author = {Montaner, D. and Tarraga, J. and Huerta-Cepas, J. and Burguet, J. and Vaquerizas, J. M. and L. Conde and Minguez, P. and Vera, J. and Mukherjee, S. and Valls, J. and Pujana, M. A. and Alloza, E. and Herrero, J. and Fatima Al-Shahrour and Dopazo, J.} }