@article {387, title = {HGVA: the Human Genome Variation Archive.}, journal = {Nucleic Acids Res}, volume = {45}, year = {2017}, month = {2017 Jul 03}, pages = {W189-W194}, abstract = {

High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK{\textquoteright}s 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.

}, keywords = {Genetic Variation, Genome, Human, Humans, Internet, Software, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkx445}, url = {https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkx445}, author = {Lopez, Javier and Coll, Jacobo and Haimel, Matthias and Kandasamy, Swaathi and T{\'a}rraga, Joaqu{\'\i}n and Furio-Tari, Pedro and Bari, Wasim and Bleda, Marta and Rueda, Antonio and Gr{\"a}f, Stefan and Rendon, Augusto and Dopazo, Joaquin and Medina, Ignacio} } @article {1230, title = {A new parallel pipeline for DNA methylation analysis of long reads datasets.}, journal = {BMC bioinformatics}, volume = {18}, year = {2017}, month = {2017 Mar 09}, pages = {161}, abstract = {BACKGROUND: DNA methylation is an important mechanism of epigenetic regulation in development and disease. New generation sequencers allow genome-wide measurements of the methylation status by reading short stretches of the DNA sequence (Methyl-seq). Several software tools for methylation analysis have been proposed over recent years. However, the current trend is that the new sequencers and the ones expected for an upcoming future yield sequences of increasing length, making these software tools inefficient and obsolete. RESULTS: In this paper, we propose a new software based on a strategy for methylation analysis of Methyl-seq sequencing data that requires much shorter execution times while yielding a better level of sensitivity, particularly for datasets composed of long reads. This strategy can be exported to other methylation, DNA and RNA analysis tools. CONCLUSIONS: The developed software tool achieves execution times one order of magnitude shorter than the existing tools, while yielding equal sensitivity for short reads and even better sensitivity for long reads.}, keywords = {Methyl-Seq, NGS}, issn = {1471-2105}, doi = {10.1186/s12859-017-1574-3}, url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-017-1574-3}, author = {Olanda, Ricardo and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and T{\'a}rraga, Joaqu{\'\i}n and Joaqu{\'\i}n Dopazo} } @article {382, title = {VISMapper: ultra-fast exhaustive cartography of viral insertion sites for gene therapy.}, journal = {BMC Bioinformatics}, volume = {18}, year = {2017}, month = {2017 Sep 20}, pages = {421}, abstract = {

BACKGROUND: The possibility of integrating viral vectors to become a persistent part of the host genome makes them a crucial element of clinical gene therapy. However, viral integration has associated risks, such as the unintentional activation of oncogenes that can result in cancer. Therefore, the analysis of integration sites of retroviral vectors is a crucial step in developing safer vectors for therapeutic use.

RESULTS: Here we present VISMapper, a vector integration site analysis web server, to analyze next-generation sequencing data for retroviral vector integration sites. VISMapper can be found at: http://vismapper.babelomics.org .

CONCLUSIONS: Because it uses novel mapping algorithms VISMapper is remarkably faster than previous available programs. It also provides a useful graphical interface to analyze the integration sites found in the genomic context.

}, keywords = {Base Sequence, Genetic Therapy, Genetic Vectors, High-Throughput Nucleotide Sequencing, Humans, Internet, User-Computer Interface, Virus Integration}, issn = {1471-2105}, doi = {10.1186/s12859-017-1837-z}, author = {Juanes, Jos{\'e} M and Gallego, Asunci{\'o}n and T{\'a}rraga, Joaqu{\'\i}n and Chaves, Felipe J and Marin-Garcia, Pablo and Medina, Ignacio and Arnau, Vicente and Dopazo, Joaquin} } @article {560, title = {HPG pore: an efficient and scalable framework for nanopore sequencing data}, journal = {BMC Bioinformatics}, volume = {17}, year = {2016}, month = {Jan-12-2016}, doi = {10.1186/s12859-016-0966-0}, url = {http://www.biomedcentral.com/1471-2105/17/107http://link.springer.com/content/pdf/10.1186/s12859-016-0966-0}, author = {T{\'a}rraga, Joaqu{\'\i}n and Gallego, Asunci{\'o}n and Arnau, Vicente and Medina, Ignacio and Dopazo, Joaquin} } @article {1195, title = {HPG pore: an efficient and scalable framework for nanopore sequencing data.}, journal = {BMC bioinformatics}, volume = {17}, year = {2016}, month = {2016}, pages = {107}, abstract = {BACKGROUND: The use of nanopore technologies is expected to spread in the future because they are portable and can sequence long fragments of DNA molecules without prior amplification. The first nanopore sequencer available, the MinION{\texttrademark} from Oxford Nanopore Technologies, is a USB-connected, portable device that allows real-time DNA analysis. In addition, other new instruments are expected to be released soon, which promise to outperform the current short-read technologies in terms of throughput. Despite the flood of data expected from this technology, the data analysis solutions currently available are only designed to manage small projects and are not scalable. RESULTS: Here we present HPG Pore, a toolkit for exploring and analysing nanopore sequencing data. HPG Pore can run on both individual computers and in the Hadoop distributed computing framework, which allows easy scale-up to manage the large amounts of data expected to result from extensive use of nanopore technologies in the future. CONCLUSIONS: HPG Pore allows for virtually unlimited sequencing data scalability, thus guaranteeing its continued management in near future scenarios. HPG Pore is available in GitHub at http://github.com/opencb/hpg-pore .}, keywords = {hadoop, HPC, nanopore, NGS}, issn = {1471-2105}, doi = {10.1186/s12859-016-0966-0}, url = {http://www.biomedcentral.com/1471-2105/17/107}, author = {T{\'a}rraga, Joaqu{\'\i}n and Gallego, Asunci{\'o}n and Arnau, Vicente and Medina, Ignacio and Dopazo, Joaquin} } @article {1129, title = {Babelomics 5.0: functional interpretation for new generations of genomic data.}, journal = {Nucleic acids research}, volume = {43}, number = {W1}, year = {2015}, month = {2015 Apr 20}, pages = {W117-W121}, abstract = {Babelomics has been running for more than one decade offering a user-friendly interface for the functional analysis of gene expression and genomic data. Here we present its fifth release, which includes support for Next Generation Sequencing data including gene expression (RNA-seq), exome or genome resequencing. Babelomics has simplified its interface, being now more intuitive. Improved visualization options, such as a genome viewer as well as an interactive network viewer, have been implemented. New technical enhancements at both, client and server sides, makes the user experience faster and more dynamic. Babelomics offers user-friendly access to a full range of methods that cover: (i) primary data analysis, (ii) a variety of tests for different experimental designs and (iii) different enrichment and network analysis algorithms for the interpretation of the results of such tests in the proper functional context. In addition to the public server, local copies of Babelomics can be downloaded and installed. Babelomics is freely available at: http://www.babelomics.org.}, keywords = {babelomics, data integration, gene set analysis, interactome, network analysis, NGS, RNA-seq, Systems biology, transcriptomics}, issn = {1362-4962}, doi = {10.1093/nar/gkv384}, url = {http://nar.oxfordjournals.org/content/43/W1/W117}, author = {Alonso, Roberto and Salavert, Francisco and Garcia-Garcia, Francisco and Carbonell-Caballero, Jos{\'e} and Bleda, Marta and Garc{\'\i}a-Alonso, Luz and Sanchis-Juan, Alba and Perez-Gil, Daniel and Marin-Garcia, Pablo and S{\'a}nchez, Rub{\'e}n and Cubuk, Cankut and Hidalgo, Marta R and Amadoz, Alicia and Hernansaiz-Ballesteros, Rosa D and Alem{\'a}n, Alejandro and T{\'a}rraga, Joaqu{\'\i}n and Montaner, David and Medina, Ignacio and Dopazo, Joaquin} } @article {1162, title = {Concurrent and Accurate Short Read Mapping on Multicore Processors.}, journal = {IEEE/ACM transactions on computational biology and bioinformatics / IEEE, ACM}, volume = {12}, year = {2015}, month = {2015 Sep-Oct}, pages = {995-1007}, abstract = {We introduce a parallel aligner with a work-flow organization for fast and accurate mapping of RNA sequences on servers equipped with multicore processors. Our software, [Formula: see text] ([Formula: see text] is an open-source application. The software is available at http://www.opencb.org, exploits a suffix array to rapidly map a large fraction of the RNA fragments (reads), as well as leverages the accuracy of the Smith-Waterman algorithm to deal with conflictive reads. The aligner is enhanced with a careful strategy to detect splice junctions based on an adaptive division of RNA reads into small segments (or seeds), which are then mapped onto a number of candidate alignment locations, providing crucial information for the successful alignment of the complete reads. The experimental results on a platform with Intel multicore technology report the parallel performance of [Formula: see text], on RNA reads of 100-400 nucleotides, which excels in execution time/sensitivity to state-of-the-art aligners such as TopHat 2+Bowtie 2, MapSplice, and STAR.}, keywords = {HPC, NGS, short real mapping}, issn = {1557-9964}, doi = {10.1109/TCBB.2015.2392077}, url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=\&arnumber=7010005}, author = {Martinez, Hector and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Barrachina, Sergio and Castillo, Maribel and Dopazo, Joaquin and Quintana-Orti, Enrique S} } @article {472, title = {Fast inexact mapping using advanced tree exploration on backward search methods.}, journal = {BMC Bioinformatics}, volume = {16}, year = {2015}, month = {2015 Jan 28}, pages = {18}, abstract = {

BACKGROUND: Short sequence mapping methods for Next Generation Sequencing consist on a combination of seeding techniques followed by local alignment based on dynamic programming approaches. Most seeding algorithms are based on backward search alignment, using the Burrows Wheeler Transform, the Ferragina and Manzini Index or Suffix Arrays. All these backward search algorithms have excellent performance, but their computational cost highly increases when allowing errors. In this paper, we discuss an inexact mapping algorithm based on pruning strategies for search tree exploration over genomic data.

RESULTS: The proposed algorithm achieves a 13x speed-up over similar algorithms when allowing 6 base errors, including insertions, deletions and mismatches. This algorithm can deal with 400 bps reads with up to 9 errors in a high quality Illumina dataset. In this example, the algorithm works as a preprocessor that reduces by 55\% the number of reads to be aligned. Depending on the aligner the overall execution time is reduced between 20-40\%.

CONCLUSIONS: Although not intended as a complete sequence mapping tool, the proposed algorithm could be used as a preprocessing step to modern sequence mappers. This step significantly reduces the number reads to be aligned, accelerating overall alignment time. Furthermore, this algorithm could be used for accelerating the seeding step of already available sequence mappers. In addition, an out-of-core index has been implemented for working with large genomes on systems without expensive memory configurations.

}, keywords = {Algorithms, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Sequence Alignment, Sequence Analysis, DNA, Software}, issn = {1471-2105}, doi = {10.1186/s12859-014-0438-3}, author = {Salavert, Jos{\'e} and Tom{\'a}s, Andr{\'e}s and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Dopazo, Joaquin and Blanquer, Ignacio} } @article {1149, title = {A Parallel and Sensitive Software Tool for Methylation Analysis on Multicore Platforms.}, journal = {Bioinformatics (Oxford, England)}, volume = {31}, number = {19}, year = {2015}, month = {2015 Jun 10}, pages = {3130-3138}, abstract = {MOTIVATION: DNA methylation analysis suffers from very long processing time, since the advent of Next-Generation Sequencers (NGS) has shifted the bottleneck of genomic studies from the sequencers that obtain the DNA samples to the software that performs the analysis of these samples. The existing software for methylation analysis does not seem to scale efficiently neither with the size of the dataset nor with the length of the reads to be analyzed. Since it is expected that the sequencers will provide longer and longer reads in the near future, efficient and scalable methylation software should be developed. RESULTS: We present a new software tool, called HPG-Methyl, which efficiently maps bisulfite sequencing reads on DNA, analyzing DNA methylation. The strategy used by this software consists of leveraging the speed of the Burrows-Wheeler Transform to map a large number of DNA fragments (reads) rapidly, as well as the accuracy of the Smith-Waterman algorithm, which is exclusively employed to deal with the most ambiguous and shortest reads. Experimental results on platforms with Intel multicore processors show that HPGMethyl significantly outperforms in both execution time and sensitivity state-of-the-art software such as Bismark, BS-Seeker or BSMAP, particularly for long bisulfite reads. AVAILABILITY: Software in the form of C libraries and functions, together with instructions to compile and execute this software. Available by sftp to anonymous@clariano.uv.es (password "anonymous"). CONTACT: Juan.Orduna@uv.es.}, keywords = {BS-seq, HPC, methylation, NGS}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btv357}, url = {http://bioinformatics.oxfordjournals.org/content/31/19/3130.long}, author = {T{\'a}rraga, Joaqu{\'\i}n and P{\'e}rez, Mariano and Ordu{\~n}a, Juan M and Duato, Jos{\'e} and Medina, Ignacio and Joaqu{\'\i}n Dopazo} } @article {1076, title = {Acceleration of short and long DNA read mapping without loss of accuracy using suffix array.}, journal = {Bioinformatics (Oxford, England)}, volume = {30}, year = {2014}, month = {2014 Aug 20}, pages = {3396-3398}, abstract = {HPG Aligner applies suffix arrays for DNA read mapping. This implementation produces a highly sensitive and extremely fast mapping of DNA reads that scales up almost linearly with read length. The approach presented here is faster (over 20x for long reads) and more sensitive (over 98\% in a wide range of read lengths) than the current, state-of-the-art mappers. HPG Aligner is not only an optimal alternative for current sequencers but also the only solution available to cope with longer reads and growing throughputs produced by forthcoming sequencing technologies.}, keywords = {NGS, short read mapping. HPC. suffix arrays}, issn = {1367-4811}, doi = {10.1093/bioinformatics/btu553}, url = {http://bioinformatics.oxfordjournals.org/content/early/2014/08/19/bioinformatics.btu553.long}, author = {T{\'a}rraga, Joaqu{\'\i}n and Arnau, Vicente and Martinez, Hector and Moreno, Raul and Cazorla, Diego and Salavert-Torres, Jos{\'e} and Blanquer-Espert, Ignacio and Joaqu{\'\i}n Dopazo and Medina, Ignacio} } @article {916, title = {CellBase, a comprehensive collection of RESTful web services for retrieving relevant biological information from heterogeneous sources.}, journal = {Nucleic acids research}, volume = {40}, year = {2012}, month = {2012 Jul}, pages = {W609-14}, abstract = {During the past years, the advances in high-throughput technologies have produced an unprecedented growth in the number and size of repositories and databases storing relevant biological data. Today, there is more biological information than ever but, unfortunately, the current status of many of these repositories is far from being optimal. Some of the most common problems are that the information is spread out in many small databases; frequently there are different standards among repositories and some databases are no longer supported or they contain too specific and unconnected information. In addition, data size is increasingly becoming an obstacle when accessing or storing biological data. All these issues make very difficult to extract and integrate information from different sources, to analyze experiments or to access and query this information in a programmatic way. CellBase provides a solution to the growing necessity of integration by easing the access to biological data. CellBase implements a set of RESTful web services that query a centralized database containing the most relevant biological data sources. The database is hosted in our servers and is regularly updated. CellBase documentation can be found at http://docs.bioinfo.cipf.es/projects/cellbase.}, issn = {1362-4962}, doi = {10.1093/nar/gks575}, url = {http://nar.oxfordjournals.org/content/40/W1/W609.long}, author = {Bleda, Marta and T{\'a}rraga, Joaqu{\'\i}n and De Maria, Alejandro and Salavert, Francisco and Garc{\'\i}a-Alonso, Luz and Celma, Matilde and Martin, Ainoha and Dopazo, Joaquin and Medina, Ignacio} } @article {539, title = {Phylemon 2.0: a suite of web-tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing.}, journal = {Nucleic Acids Res}, volume = {39}, year = {2011}, month = {2011 Jul}, pages = {W470-4}, abstract = {

Phylemon 2.0 is a new release of the suite of web tools for molecular evolution, phylogenetics, phylogenomics and hypotheses testing. It has been designed as a response to the increasing demand of molecular sequence analyses for experts and non-expert users. Phylemon 2.0 has several unique features that differentiates it from other similar web resources: (i) it offers an integrated environment that enables evolutionary analyses, format conversion, file storage and edition of results; (ii) it suggests further analyses, thereby guiding the users through the web server; and (iii) it allows users to design and save phylogenetic pipelines to be used over multiple genes (phylogenomics). Altogether, Phylemon 2.0 integrates a suite of 30 tools covering sequence alignment reconstruction and trimming; tree reconstruction, visualization and manipulation; and evolutionary hypotheses testing.

}, keywords = {Evolution, Molecular, Genomics, Internet, Phylogeny, Sequence Alignment, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkr408}, author = {S{\'a}nchez, Rub{\'e}n and Serra, Fran{\c c}ois and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and De Maria, Alejandro and Capella-Gut{\'\i}errez, Salvador and Huerta-Cepas, Jaime and Gabald{\'o}n, Toni and Dopazo, Joaquin and Dopazo, Hern{\'a}n} } @article {20478823, title = {Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.}, journal = {Nucleic Acids Research}, volume = {38}, year = {2010}, month = {2010 May 16}, pages = {W210-W213. Featured in NAR}, chapter = {Featured in NAR}, abstract = {

Babelomics is a response to the growing necessity of integrating and analyzing different types of genomic data in an environment that allows an easy functional interpretation of the results. Babelomics includes a complete suite of methods for the analysis of gene expression data that include normalization (covering most commercial platforms), pre-processing, differential gene expression (case-controls, multiclass, survival or continuous values), predictors, clustering; large-scale genotyping assays (case controls and TDTs, and allows population stratification analysis and correction). All these genomic data analysis facilities are integrated and connected to multiple options for the functional interpretation of the experiments. Different methods of functional enrichment or gene set enrichment can be used to understand the functional basis of the experiment analyzed. Many sources of biological information, which include functional (GO, KEGG, Biocarta, Reactome, etc.), regulatory (Transfac, Jaspar, ORegAnno, miRNAs, etc.), text-mining or protein-protein interaction modules can be used for this purpose. Finally a tool for the de novo functional annotation of sequences has been included in the system. This provides support for the functional analysis of non-model species. Mirrors of Babelomics or command line execution of their individual components are now possible. Babelomics is available at http://www.babelomics.org.

}, keywords = {babelomics, gene expression, genotyping, gepas, GSA, GWAS}, url = {http://nar.oxfordjournals.org/content/38/suppl_2/W210.full}, author = {Medina, Ignacio and Carbonell, Jos{\'e} and Pulido, Luis and Madeira, Sara C and Goetz, Stefan and Ana Conesa and T{\'a}rraga, Joaqu{\'\i}n and Pascual-Montano, Alberto and Nogales-Cadenas, Ruben and Santoyo, Javier and Garc{\'\i}a, Francisco and Marb{\`a}, Martina and Montaner, David and Joaqu{\'\i}n Dopazo} } @article {IgnacioMedina07012009, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies}, journal = {Nucl. Acids Res.}, volume = {37}, number = {suppl_2}, year = {2009}, pages = {W340-344}, abstract = {

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/

}, keywords = {babelomics, gene set, GESBAP, pathway-based analysis, SNP}, doi = {10.1093/nar/gkp481}, url = {http://nar.oxfordjournals.org/cgi/content/abstract/37/suppl_2/W340}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Fatima Al-Shahrour and Dopazo, Joaquin} } @article {583, title = {Gene set-based analysis of polymorphisms: finding pathways or biological processes associated to traits in genome-wide association studies.}, journal = {Nucleic Acids Res}, volume = {37}, year = {2009}, month = {2009 Jul}, pages = {W340-4}, abstract = {

Genome-wide association studies have become a popular strategy to find associations of genes to traits of interest. Despite the high-resolution available today to carry out genotyping studies, the success of its application in real studies has been limited by the testing strategy used. As an alternative to brute force solutions involving the use of very large cohorts, we propose the use of the Gene Set Analysis (GSA), a different analysis strategy based on testing the association of modules of functionally related genes. We show here how the Gene Set-based Analysis of Polymorphisms (GeSBAP), which is a simple implementation of the GSA strategy for the analysis of genome-wide association studies, provides a significant increase in the power testing for this type of studies. GeSBAP is freely available at http://bioinfo.cipf.es/gesbap/.

}, keywords = {Biological Phenomena, Breast Neoplasms, Female, Genes, Genetic Variation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Software, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkp481}, author = {Medina, Ignacio and Montaner, David and Bonifaci, N{\'u}ria and Pujana, Miguel Angel and Carbonell, Jos{\'e} and T{\'a}rraga, Joaqu{\'\i}n and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @article {593, title = {GEPAS, a web-based tool for microarray data analysis and interpretation.}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, month = {2008 Jul 01}, 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 = {Computer Graphics, Dose-Response Relationship, Drug, Gene Expression Profiling, Internet, Kinetics, Oligonucleotide Array Sequence Analysis, Software}, issn = {1362-4962}, doi = {10.1093/nar/gkn303}, author = {T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Carbonell, Jos{\'e} and Huerta-Cepas, Jaime and Minguez, Pablo and Alloza, Eva and Al-Shahrour, F{\'a}tima and Vegas-Azc{\'a}rate, Susana and Goetz, Stefan and Escobar, Pablo and Garcia-Garcia, Francisco and Conesa, Ana and Montaner, David and Dopazo, Joaquin} } @article {595, title = {Interoperability with Moby 1.0--it{\textquoteright}s better than sharing your toothbrush!}, journal = {Brief Bioinform}, volume = {9}, year = {2008}, month = {2008 May}, 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, Database Management Systems, Databases, Factual, Information Storage and Retrieval, Internet, Programming Languages, Systems Integration}, issn = {1477-4054}, doi = {10.1093/bib/bbn003}, author = {Wilkinson, Mark D and Senger, Martin and Kawas, Edward and Bruskiewich, Richard and Gouzy, Jerome and Noirot, Celine and Bardou, Philippe and Ng, Ambrose and Haase, Dirk and Saiz, Enrique de Andres and Wang, Dennis and Gibbons, Frank and Gordon, Paul M K and Sensen, Christoph W and Carrasco, Jose Manuel Rodriguez and Fern{\'a}ndez, Jos{\'e} M and Shen, Lixin and Links, Matthew and Ng, Michael and Opushneva, Nina and Neerincx, Pieter B T and Leunissen, Jack A M and Ernst, Rebecca and Twigger, Simon and Usadel, Bjorn and Good, Benjamin and Wong, Yan and Stein, Lincoln and Crosby, William and Karlsson, Johan and Royo, Romina and P{\'a}rraga, Iv{\'a}n and Ram{\'\i}rez, Sergio and Gelpi, Josep Lluis and Trelles, Oswaldo and Pisano, David G and Jimenez, Natalia and Kerhornou, Arnaud and Rosset, Roman and Zamacola, Leire and T{\'a}rraga, Joaqu{\'\i}n and Huerta-Cepas, Jaime and Carazo, Jose Mar{\'\i}a and Dopazo, Joaquin and Guig{\'o}, Roderic and Navarro, Arcadi and Orozco, Modesto and Valencia, Alfonso and Claros, M Gonzalo and P{\'e}rez, Antonio J and Aldana, Jose and Rojano, M Mar and Fernandez-Santa Cruz, Raul and Navas, Ismael and Schiltz, Gary and Farmer, Andrew and Gessler, Damian and Schoof, Heiko and Groscurth, Andreas} } @article {605, title = {FatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W91-6}, abstract = {

The ultimate goal of any genome-scale experiment is to provide a functional interpretation of the data, relating the available information with the hypotheses that originated the experiment. Thus, functional profiling methods have become essential in diverse scenarios such as microarray experiments, proteomics, etc. We present the FatiGO+, a web-based tool for the functional profiling of genome-scale experiments, specially oriented to the interpretation of microarray experiments. In addition to different functional annotations (gene ontology, KEGG pathways, Interpro motifs, Swissprot keywords and text-mining based bioentities related to diseases and chemical compounds) FatiGO+ includes, as a novelty, regulatory and structural information. The regulatory information used includes predictions of targets for distinct regulatory elements (obtained from the Transfac and CisRed databases). Additionally FatiGO+ uses predictions of target motifs of miRNA to infer which of these can be activated or deactivated in the sample of genes studied. Finally, properties of gene products related to their relative location and connections in the interactome have also been used. Also, enrichment of any of these functional terms can be directly analysed on chromosomal coordinates. FatiGO+ can be found at: http://www.fatigoplus.org and within the Babelomics environment http://www.babelomics.org.

}, keywords = {Amino Acid Motifs, Animals, Binding Sites, Computational Biology, Gene Expression Profiling, Genes, Genomics, Humans, Internet, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, Transcription Factors}, issn = {1362-4962}, doi = {10.1093/nar/gkm260}, author = {Al-Shahrour, F{\'a}tima and Minguez, Pablo and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Alloza, Eva and Montaner, David and Dopazo, Joaquin} } @article {607, title = {Functional profiling and gene expression analysis of chromosomal copy number alterations.}, journal = {Bioinformation}, volume = {1}, year = {2007}, month = {2007 Apr 10}, pages = {432-5}, abstract = {

Contrarily to the traditional view in which only one or a few key genes were supposed to be the causative factors of diseases, we discuss the importance of considering groups of functionally related genes in the study of pathologies characterised by chromosomal copy number alterations. Recent observations have reported the existence of regions in higher eukaryotic chromosomes (including humans) containing genes of related function that show a high degree of coregulation. Copy number alterations will consequently affect to clusters of functionally related genes, which will be the final causative agents of the diseased phenotype, in many cases. Therefore, we propose that the functional profiling of the regions affected by copy number alterations must be an important aspect to take into account in the understanding of this type of pathologies. To illustrate this, we present an integrated study of DNA copy number variations, gene expression along with the functional profiling of chromosomal regions in a case of multiple myeloma.

}, issn = {0973-2063}, doi = {10.6026/97320630001432}, author = {Conde, Lucia and Montaner, David and Burguet-Castell, Jordi and T{\'a}rraga, Joaqu{\'\i}n and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} } @article {608, title = {ISACGH: a web-based environment for the analysis of Array CGH and gene expression which includes functional profiling.}, journal = {Nucleic Acids Res}, volume = {35}, year = {2007}, month = {2007 Jul}, pages = {W81-5}, abstract = {

We present the ISACGH, a web-based system that allows for the combination of genomic data with gene expression values and provides different options for functional profiling of the regions found. Several visualization options offer a convenient representation of the results. Different efficient methods for accurate estimation of genomic copy number from array-CGH hybridization data have been included in the program. Moreover, the connection to the gene expression analysis package GEPAS allows the use of different facilities for data pre-processing and analysis. A DAS server allows exporting the results to the Ensembl viewer where contextual genomic information can be obtained. The program is freely available at: http://isacgh.bioinfo.cipf.es or within http://www.gepas.org.

}, keywords = {Animals, Cluster Analysis, Computational Biology, Computer Graphics, Gene Expression Profiling, Humans, Internet, Models, Genetic, Nucleic Acid Hybridization, Oligonucleotide Array Sequence Analysis, Programming Languages, Software, Systems Integration, User-Computer Interface}, issn = {1362-4962}, doi = {10.1093/nar/gkm257}, author = {Conde, Lucia and Montaner, David and Burguet-Castell, Jordi and T{\'a}rraga, Joaqu{\'\i}n and Medina, Ignacio and Al-Shahrour, F{\'a}tima and Dopazo, Joaquin} }