@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 {1126, title = {BRCA1 Alternative splicing landscape in breast tissue samples.}, journal = {BMC cancer}, volume = {15}, year = {2015}, month = {2015}, pages = {219}, abstract = {BACKGROUND: BRCA1 is a key protein in cell network, involved in DNA repair pathways and cell cycle. Recently, the ENIGMA consortium has reported a high number of alternative splicing (AS) events at this locus in blood-derived samples. However, BRCA1 splicing pattern in breast tissue samples is unknown. Here, we provide an accurate description of BRCA1 splicing events distribution in breast tissue samples. METHODS: BRCA1 splicing events were scanned in 70 breast tumor samples, 4 breast samples from healthy individuals and in 72 blood-derived samples by capillary electrophoresis (capillary EP). Molecular subtype was identified in all tumor samples. Splicing events were considered predominant if their relative expression level was at least the 10\% of the full-length reference signal. RESULTS: 54 BRCA1 AS events were identified, 27 of them were annotated as predominant in at least one sample. Δ5q, Δ13, Δ9, Δ5 and ▼1aA were significantly more frequently annotated as predominant in breast tumor samples than in blood-derived samples. Predominant splicing events were, on average, more frequent in tumor samples than in normal breast tissue samples (P = 0.010). Similarly, likely inactivating splicing events (PTC-NMDs, Non-Coding, Δ5 and Δ18) were more frequently annotated as predominant in tumor than in normal breast samples (P = 0.020), whereas there were no significant differences for other splicing events (No-Fs) frequency distribution between tumor and normal breast samples (P = 0.689). CONCLUSIONS: Our results complement recent findings by the ENIGMA consortium, demonstrating that BRCA1 AS, despite its tremendous complexity, is similar in breast and blood samples, with no evidences for tissue specific AS events. Further on, we conclude that somatic inactivation of BRCA1 through spliciogenic mutations is, at best, a rare mechanism in breast carcinogenesis, albeit our data detects an excess of likely inactivating AS events in breast tumor samples.}, issn = {1471-2407}, doi = {10.1186/s12885-015-1145-9}, url = {http://www.biomedcentral.com/1471-2407/15/219}, author = {Romero, Atocha and Garcia-Garcia, Francisco and L{\'o}pez-Perolio, Irene and Ruiz de Garibay, Gorka and Garc{\'\i}a-S{\'a}enz, Jos{\'e} A and Garre, Pilar and Ayll{\'o}n, Patricia and Benito, Esperanza and Joaqu{\'\i}n Dopazo and D{\'\i}az-Rubio, Eduardo and Cald{\'e}s, Trinidad and de la Hoya, Miguel} } @article {21335611, title = {B2G-FAR, a species centered GO annotation repository.}, journal = {Bioinformatics (Oxford, England)}, volume = {27}, number = {7}, year = {2011}, month = {2011 Feb 18}, pages = {919-924}, abstract = {

MOTIVATION: Functional genomics research has expanded enormously in the last decade thanks to the cost-reduction in high-throughput technologies and the development of computational tools that generate, standardize and share information on gene and protein function such as the Gene Ontology (GO). Nevertheless many biologists, especially working with non-model organisms, still suffer from non-existing or low coverage functional annotation, or simply struggle retrieving, summarizing and querying these data. RESULTS: The Blast2GO Functional Annotation Repository (B2G-FAR) is a bioinformatics resource envisaged to provide functional information for otherwise uncharacterized sequence-data and offers data-mining tools to analyze a larger repertoire of species than currently available. This new annotation resource has been created by applying the Blast2GO functional annotation engine in a strongly high-throughput manner to the entire space of public available sequences. The resulting repository contains GO term predictions for over 13.2 million non-redundant protein sequences based on BLAST search alignments from the SIMAP database. We generated GO annotation for approximately 150.000 different taxa making available the 2000 species with the highest coverage through B2G-FAR. A second section within B2G-FAR holds functional annotations for 17 non-model organism Affymetrix GeneChips. Conclusions: B2G-FAR provides easy access to exhaustive functional annotation for 2000 species offering a good balance between quality and quantity, thereby supporting functional genomics research especially in the case of non-model organisms. AVAILABILITY: The annotation resource is available at http://b2gfar.bioinfo.cipf.es. CONTACT: aconesa@cipf.es, sgoetz@cipf.es.

}, author = {G{\"o}tz, Stefan and Arnold, Roland and Sebasti{\'a}n-Leon, Patricia and Mart{\'\i}n-Rodr{\'\i}guez, Samuel and Tischler, Patrick and Jehl, Marc-Andr{\'e} and Joaqu{\'\i}n Dopazo and Rattei, Thomas and Ana Conesa} } @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 {764, title = {Bioinform{\'a}tica, Gen{\'o}mica y Evoluci{\'o}n. Una alianza estrat{\'e}gica para la biolog{\'\i}a de este siglo.}, journal = {Ciencia Hoy}, volume = {19}, number = {113}, year = {2009}, pages = {88-93}, author = {H. Dopazo} } @article {18515841, title = {Babelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments}, journal = {Nucleic Acids Res}, volume = {36}, year = {2008}, note = {

Al-Shahrour, Fatima Carbonell, Jose Minguez, Pablo Goetz, Stefan Conesa, Ana Tarraga, Joaquin Medina, Ignacio Alloza, Eva 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):W341-6. Epub 2008 May 31.

}, pages = {W341-6}, abstract = {

We present a new version of Babelomics, a complete suite of web tools for the functional profiling of genome scale experiments, with new and improved methods as well as more types of functional definitions. Babelomics includes different flavours of conventional functional enrichment methods as well as more advanced gene set analysis methods that makes it a unique tool among the similar resources available. In addition to the well-known functional definitions (GO, KEGG), Babelomics includes new ones such as Biocarta pathways or text mining-derived functional terms. Regulatory modules implemented include transcriptional control (Transfac, CisRed) and other levels of regulation such as miRNA-mediated interference. Moreover, Babelomics allows for sub-selection of terms in order to test more focused hypothesis. Also gene annotation correspondence tables can be imported, which allows testing with user-defined functional modules. Finally, a tool for the {\textquoteright}de novo{\textquoteright} functional annotation of sequences has been included in the system. This allows using yet unannotated organisms in the program. Babelomics has been extensively re-engineered and now it 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. Babelomics is available at http://www.babelomics.org.

}, keywords = {babelomics, funtional profiling}, url = {http://nar.oxfordjournals.org/content/36/suppl_2/W341.long}, author = {Fatima Al-Shahrour and Carbonell, J. and Minguez, P. and Goetz, S. and A. Conesa and Tarraga, J. and Medina, Ignacio and Alloza, E. and Montaner, D. and Dopazo, J.} } @article {19094230, title = {Biological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes}, journal = {BMC Med Genomics}, volume = {1}, year = {2008}, note = {

Bonifaci, Nuria Berenguer, Antoni Diez, Javier Reina, Oscar Medina, Ignacio Dopazo, Joaquin Moreno, Victor Pujana, Miguel Angel England BMC medical genomics BMC Med Genomics. 2008 Dec 18;1:62.

}, pages = {62}, abstract = {

ABSTRACT: BACKGROUND: Recent advances in whole-genome association studies (WGASs) for human cancer risk are beginning to provide the part lists of low-penetrance susceptibility genes. However, statistical analysis in these studies is complicated by the vast number of genetic variants examined and the weak effects observed, as a result of which constraints must be incorporated into the study design and analytical approach. In this scenario, biological attributes beyond the adjusted statistics generally receive little attention and, more importantly, the fundamental biological characteristics of low-penetrance susceptibility genes have yet to be determined. METHODS: We applied an integrative approach for identifying candidate low-penetrance breast cancer susceptibility genes, their characteristics and molecular networks through the analysis of diverse sources of biological evidence. RESULTS: First, examination of the distribution of Gene Ontology terms in ordered WGAS results identified asymmetrical distribution of Cell Communication and Cell Death processes linked to risk. Second, analysis of 11 different types of molecular or functional relationships in genomic and proteomic data sets defined the \"omic\" properties of candidate genes: i/ differential expression in tumors relative to normal tissue; ii/ somatic genomic copy number changes correlating with gene expression levels; iii/ differentially expressed across age at diagnosis; and iv/ expression changes after BRCA1 perturbation. Finally, network modeling of the effects of variants on germline gene expression showed higher connectivity than expected by chance between novel candidates and with known susceptibility genes, which supports functional relationships and provides mechanistic hypotheses of risk. CONCLUSION: This study proposes that cell communication and cell death are major biological processes perturbed in risk of breast cancer conferred by low-penetrance variants, and defines the common omic properties, molecular interactions and possible functional effects of candidate genes and proteins.

}, keywords = {gene set, GWAS, SNP}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=19094230}, author = {Bonifaci, N. and Berenguer, A. and Diez, J. and Reina, O. and Medina, Ignacio and Dopazo, J. and Moreno, V. and Pujana, M. A.} } @article {18483572, title = {Blast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics}, journal = {Int J Plant Genomics}, volume = {2008}, year = {2008}, note = {

Conesa, Ana Gotz, Stefan Egypt International journal of plant genomics Int J Plant Genomics. 2008;2008:619832.

}, pages = {619832}, abstract = {

Functional annotation of novel sequence data is a primary requirement for the utilization of functional genomics approaches in plant research. In this paper, we describe the Blast2GO suite as a comprehensive bioinformatics tool for functional annotation of sequences and data mining on the resulting annotations, primarily based on the gene ontology (GO) vocabulary. Blast2GO optimizes function transfer from homologous sequences through an elaborate algorithm that considers similarity, the extension of the homology, the database of choice, the GO hierarchy, and the quality of the original annotations. The tool includes numerous functions for the visualization, management, and statistical analysis of annotation results, including gene set enrichment analysis. The application supports InterPro, enzyme codes, KEGG pathways, GO direct acyclic graphs (DAGs), and GOSlim. Blast2GO is a suitable tool for plant genomics research because of its versatility, easy installation, and friendly use.

}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=18483572}, author = {A. Conesa and Gotz, S.} } @article {16845052, title = {BABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments}, journal = {Nucleic Acids Res}, volume = {34}, year = {2006}, note = {

Al-Shahrour, Fatima Minguez, Pablo Tarraga, Joaquin Montaner, David Alloza, Eva Vaquerizas, Juan M Conde, Lucia Blaschke, Christian Vera, Javier Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2006 Jul 1;34(Web Server issue):W472-6.

}, pages = {W472-6}, abstract = {

We present a new version of Babelomics, a complete suite of web tools for functional analysis of genome-scale experiments, with new and improved tools. New functionally relevant terms have been included such as CisRed motifs or bioentities obtained by text-mining procedures. An improved indexing has considerably speeded up several of the modules. An improved version of the FatiScan method for studying the coordinate behaviour of groups of functionally related genes is presented, along with a similar tool, the Gene Set Enrichment Analysis. Babelomics is now more oriented to test systems biology inspired hypotheses. Babelomics can be found at http://www.babelomics.org.

}, keywords = {babelomics, functional profiling}, url = {http://nar.oxfordjournals.org/content/34/suppl_2/W472.long}, author = {Fatima Al-Shahrour and Minguez, P. and Tarraga, J. and Montaner, D. and Alloza, E. and Vaquerizas, J. M. and L. Conde and Blaschke, C. and Vera, J. and Dopazo, J.} } @article {16790393, title = {Bioinformatics and cancer: an essential alliance}, journal = {Clin Transl Oncol}, volume = {8}, number = {6}, year = {2006}, note = {

Dopazo, Joaquin Comparative Study Research Support, Non-U.S. Gov{\textquoteright}t Review Spain Clinical \& translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico Clin Transl Oncol. 2006 Jun;8(6):409-15.

}, pages = {409-15}, abstract = {

Modern research in cancer has been revolutionized by the introduction of new high-throughput methodologies such as DNA microarrays. Keeping the pace with these technologies, the bioinformatics offer new solutions for data analysis and, what is more important, it permits to formulate a new class of hypothesis inspired in systems biology, more oriented to blocks of functionally-related genes. Although software implementations for this new methodologies is new there are some options already available. Bioinformatic solutions for other high-throughput techniques such as array-CGH of large-scale genotyping is also revised.

}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16790393}, author = {Dopazo, J.} } @article {16823138, title = {Blast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis}, journal = {Stud Health Technol Inform}, volume = {120}, year = {2006}, note = {

Aparicio, G Gotz, S Conesa, A Segrelles, D Blanquer, I Garcia, J M Hernandez, V Robles, M Talon, M Netherlands Studies in health technology and informatics Stud Health Technol Inform. 2006;120:194-204.

}, pages = {194-204}, abstract = {

The vast amount in complexity of data generated in Genomic Research implies that new dedicated and powerful computational tools need to be developed to meet their analysis requirements. Blast2GO (B2G) is a bioinformatics tool for Gene Ontology-based DNA or protein sequence annotation and function-based data mining. The application has been developed with the aim of affering an easy-to-use tool for functional genomics research. Typical B2G users are middle size genomics labs carrying out sequencing, ETS and microarray projects, handling datasets up to several thousand sequences. In the current version of B2G. The power and analytical potential of both annotation and function data-mining is somehow restricted to the computational power behind each particular installation. In order to be able to offer the possibility of an enhanced computational capacity within this bioinformatics application, a Grid component is being developed. A prototype has been conceived for the particular problem of speeding up the Blast searches to obtain fast results for large datasets. Many efforts have been done in the literature concerning the speeding up of Blast searches, but few of them deal with the use of large heterogeneous production Grid Infrastructures. These are the infrastructures that could reach the largest number of resources and the best load balancing for data access. The Grid Service under development will analyse requests based on the number of sequences, splitting them accordingly to the available resources. Lower-level computation will be performed through MPIBLAST. The software architecture is based on the WSRF standard.

}, keywords = {babelomics}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16823138}, author = {Aparicio, G. and Gotz, S. and A. Conesa and Segrelles, D. and Blanquer, I. and Garcia, J. M. and Hernandez, V. and Robles, M. and Talon, M.} } @article {15980512, title = {BABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments}, journal = {Nucleic Acids Res}, volume = {33}, year = {2005}, note = {

Al-Shahrour, Fatima Minguez, Pablo Vaquerizas, Juan M Conde, Lucia Dopazo, Joaquin Research Support, Non-U.S. Gov{\textquoteright}t England Nucleic acids research Nucleic Acids Res. 2005 Jul 1;33(Web Server issue):W460-4.

}, pages = {W460-4}, abstract = {

We present Babelomics, a complete suite of web tools for the functional analysis of groups of genes in high-throughput experiments, which includes the use of information on Gene Ontology terms, interpro motifs, KEGG pathways, Swiss-Prot keywords, analysis of predicted transcription factor binding sites, chromosomal positions and presence in tissues with determined histological characteristics, through five integrated modules: FatiGO (fast assignment and transference of information), FatiWise, transcription factor association test, GenomeGO and tissues mining tool, respectively. Additionally, another module, FatiScan, provides a new procedure that integrates biological information in combination with experimental results in order to find groups of genes with modest but coordinate significant differential behaviour. FatiScan is highly sensitive and is capable of finding significant asymmetries in the distribution of genes of common function across a list of ordered genes even if these asymmetries were not extreme. The strong multiple-testing nature of the contrasts made by the tools is taken into account. All the tools are integrated in the gene expression analysis package GEPAS. Babelomics is the natural evolution of our tool FatiGO (which analysed almost 22,000 experiments during the last year) to include more sources on information and new modes of using it. Babelomics can be found at http://www.babelomics.org.

}, keywords = {babelomics, functional profiling}, url = {http://nar.oxfordjournals.org/content/33/suppl_2/W460.long}, author = {Fatima Al-Shahrour and Minguez, P. and Vaquerizas, J. M. and L. Conde and Dopazo, J.} } @article {16081474, title = {Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research}, journal = {Bioinformatics}, volume = {21}, number = {18}, year = {2005}, note = {

Conesa, Ana Gotz, Stefan Garcia-Gomez, Juan Miguel Terol, Javier Talon, Manuel Robles, Montserrat Research Support, Non-U.S. Gov{\textquoteright}t England Bioinformatics (Oxford, England) Bioinformatics. 2005 Sep 15;21(18):3674-6. Epub 2005 Aug 4.

}, pages = {3674-6}, abstract = {

SUMMARY: We present here Blast2GO (B2G), a research tool designed with the main purpose of enabling Gene Ontology (GO) based data mining on sequence data for which no GO annotation is yet available. B2G joints in one application GO annotation based on similarity searches with statistical analysis and highlighted visualization on directed acyclic graphs. This tool offers a suitable platform for functional genomics research in non-model species. B2G is an intuitive and interactive desktop application that allows monitoring and comprehension of the whole annotation and analysis process. AVAILABILITY: Blast2GO is freely available via Java Web Start at http://www.blast2go.de. SUPPLEMENTARY MATERIAL: http://www.blast2go.de -\> Evaluation.

}, keywords = {babelomics}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=16081474}, author = {A. Conesa and Gotz, S. and Garcia-Gomez, J. M. and Terol, J. and Talon, M. and Robles, M.} } @article {12141992, title = {Bioinformatics methods for the analysis of expression arrays: data clustering and information extraction}, journal = {J Biotechnol}, volume = {98}, number = {2-3}, year = {2002}, note = {Tamames, Javier Clark, Dominic Herrero, Javier Dopazo, Joaquin Blaschke, Christian Fernandez, Jose M Oliveros, Juan C Valencia, Alfonso Review Netherlands Journal of biotechnology J Biotechnol. 2002 Sep 25;98(2-3):269-83.}, pages = {269-83}, abstract = {Expression arrays facilitate the monitoring of changes in the expression patterns of large collections of genes. The analysis of expression array data has become a computationally-intensive task that requires the development of bioinformatics technology for a number of key stages in the process, such as image analysis, database storage, gene clustering and information extraction. Here, we review the current trends in each of these areas, with particular emphasis on the development of the related technology being carried out within our groups.}, keywords = {Abstracting and Indexing as Topic/methods *Cluster Analysis *Database Management Systems Databases, Computer-Assisted/methods Information Storage and Retrieval/*methods Internet Medline National Library of Medicine (U.S.) Oligonucleotide Array Sequence Analysis/*methods United States, Genetic Gene Expression Gene Expression Profiling/*methods Image Processing}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve\&db=PubMed\&dopt=Citation\&list_uids=12141992}, author = {J. Tamames and Clark, D. and Herrero, J. and Dopazo, J. and Blaschke, C. and Fernandez, J. M. and Oliveros, J. C. and Valencia, A.} }