02445nas a2200469 4500008004100000022001400041245008300055210006900138260001600207300001400223490000700237520108700244653001501331653002101346653002201367653001601389653002101405653000801426653001201434653002001446653002001466100002001486700002401506700002901530700003101559700001701590700002401607700002301631700002201654700002401676700002101700700001801721700002201739700001901761700003601780700002301816700002301839700002001862700002001882700002001902856005301922 2015 eng d a1362-496200aBabelomics 5.0: functional interpretation for new generations of genomic data.0 aBabelomics 50 functional interpretation for new generations of g c2015 Apr 20 aW117-W1210 v433 aBabelomics 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.10ababelomics10adata integration10agene set analysis10ainteractome10anetwork analysis10aNGS10aRNA-seq10aSystems biology10atranscriptomics1 aAlonso, Roberto1 aSalavert, Francisco1 aGarcia-Garcia, Francisco1 aCarbonell-Caballero, José1 aBleda, Marta1 aGarcía-Alonso, Luz1 aSanchis-Juan, Alba1 aPerez-Gil, Daniel1 aMarin-Garcia, Pablo1 aSánchez, Rubén1 aCubuk, Cankut1 aHidalgo, Marta, R1 aAmadoz, Alicia1 aHernansaiz-Ballesteros, Rosa, D1 aAlemán, Alejandro1 aTárraga, Joaquín1 aMontaner, David1 aMedina, Ignacio1 aDopazo, Joaquin uhttp://nar.oxfordjournals.org/content/43/W1/W11702810nas a2200277 4500008004100000022001400041245006700055210006600122260000900188300000800197490000700205520198700212100001902199700002902218700002602247700002802273700002902301700001702330700002202347700002202369700002102391700002502412700002202437700002302459856005002482 2015 eng d a1471-240700aBRCA1 Alternative splicing landscape in breast tissue samples.0 aBRCA1 Alternative splicing landscape in breast tissue samples c2015 a2190 v153 aBACKGROUND: 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.1 aRomero, Atocha1 aGarcia-Garcia, Francisco1 aLópez-Perolio, Irene1 ade Garibay, Gorka, Ruiz1 aGarcía-Sáenz, José, A1 aGarre, Pilar1 aAyllón, Patricia1 aBenito, Esperanza1 aDopazo, Joaquín1 aDíaz-Rubio, Eduardo1 aCaldés, Trinidad1 ade la Hoya, Miguel uhttp://www.biomedcentral.com/1471-2407/15/21902490nas a2200229 4500008004100000245005800041210005500099260001600154300001200170490000700182520178000189100001801969700001901987700003002006700003102036700002202067700002202089700002102111700001902132700001602151856009302167 2011 eng d00aB2G-FAR, a species centered GO annotation repository.0 aB2GFAR a species centered GO annotation repository c2011 Feb 18 a919-9240 v273 a

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.

1 aGötz, Stefan1 aArnold, Roland1 aSebastián-Leon, Patricia1 aMartín-Rodríguez, Samuel1 aTischler, Patrick1 aJehl, Marc-André1 aDopazo, Joaquín1 aRattei, Thomas1 aConesa, Ana uhttps://www.clinbioinfosspa.es/content/b2g-far-species-centered-go-annotation-repository02554nas a2200361 4500008004100000245014100041210006900182260001600251300003100267490000700298520145100305653001501756653002001771653001501791653001001806653000801816653000901824100002001833700002101853700001701874700002101891700001801912700001601930700002301946700002901969700002701998700002002025700002302045700002002068700002002088700002102108856006302129 2010 eng d00aBabelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling.0 aBabelomics an integrative platform for the analysis of transcrip c2010 May 16 aW210-W213. Featured in NAR0 v383 a

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.

10ababelomics10agene expression10agenotyping10agepas10aGSA10aGWAS1 aMedina, Ignacio1 aCarbonell, José1 aPulido, Luis1 aMadeira, Sara, C1 aGoetz, Stefan1 aConesa, Ana1 aTárraga, Joaquín1 aPascual-Montano, Alberto1 aNogales-Cadenas, Ruben1 aSantoyo, Javier1 aGarcía, Francisco1 aMarbà, Martina1 aMontaner, David1 aDopazo, Joaquín uhttp://nar.oxfordjournals.org/content/38/suppl_2/W210.full00518nas a2200109 4500008004100000245010300041210007300144300001000217490000700227100001500234856015900249 2009 eng d00aBioinformática, Genómica y Evolución. Una alianza estratégica para la biología de este siglo.0 aBioinformática Genómica y Evolución Una alianza estratégica para a88-930 v191 aDopazo, H. uhttps://www.clinbioinfosspa.es/content/bioinform%C3%A1tica-gen%C3%B3mica-y-evoluci%C3%B3n-una-alianza-estrat%C3%A9gica-para-la-biolog%C3%ADa-de-este-siglo02142nas a2200253 4500008004100000245010200041210006900143300001100212490000700223520138600230653001501616653002401631100002401655700001801679700001601697700001401713700001501727700001601742700002001758700001501778700001701793700001501810856006301825 2008 eng d00aBabelomics: advanced functional profiling of transcriptomics, proteomics and genomics experiments0 aBabelomics advanced functional profiling of transcriptomics prot aW341-60 v363 a

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 ’de novo’ 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.

10ababelomics10afuntional profiling1 aAl-Shahrour, Fatima1 aCarbonell, J.1 aMinguez, P.1 aGoetz, S.1 aConesa, A.1 aTarraga, J.1 aMedina, Ignacio1 aAlloza, E.1 aMontaner, D.1 aDopazo, J. uhttp://nar.oxfordjournals.org/content/36/suppl_2/W341.long02872nas a2200241 4500008004100000245013000041210006900171300000700240490000600247520211000253653001302363653000902376653000802385100001702393700001802410700001302428700001402441700002002455700001502475700001502490700001902505856010602524 2008 eng d00aBiological processes, properties and molecular wiring diagrams of candidate low-penetrance breast cancer susceptibility genes0 aBiological processes properties and molecular wiring diagrams of a620 v13 a

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.

10agene set10aGWAS10aSNP1 aBonifaci, N.1 aBerenguer, A.1 aDiez, J.1 aReina, O.1 aMedina, Ignacio1 aDopazo, J.1 aMoreno, V.1 aPujana, M., A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1909423001483nas a2200133 4500008004100000245007800041210006900119300001100188490000900199520100700208100001501215700001301230856010601243 2008 eng d00aBlast2GO: A Comprehensive Suite for Functional Analysis in Plant Genomics0 aBlast2GO A Comprehensive Suite for Functional Analysis in Plant  a6198320 v20083 a

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.

1 aConesa, A.1 aGotz, S. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1848357201445nas a2200253 4500008004100000245010300041210006900144300001100213490000700224520068700231653001500918653002500933100002400958700001600982700001600998700001701014700001501031700002301046700001401069700001701083700001301100700001501113856006301128 2006 eng d00aBABELOMICS: a systems biology perspective in the functional annotation of genome-scale experiments0 aBABELOMICS a systems biology perspective in the functional annot aW472-60 v343 a

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.

10ababelomics10afunctional profiling1 aAl-Shahrour, Fatima1 aMinguez, P.1 aTarraga, J.1 aMontaner, D.1 aAlloza, E.1 aVaquerizas, J., M.1 aConde, L.1 aBlaschke, C.1 aVera, J.1 aDopazo, J. uhttp://nar.oxfordjournals.org/content/34/suppl_2/W472.long01043nas a2200121 4500008004100000245005300041210005200094300001100146490000600157520063700163100001500800856010600815 2006 eng d00aBioinformatics and cancer: an essential alliance0 aBioinformatics and cancer an essential alliance a409-150 v83 a

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.

1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1679039302376nas a2200229 4500008004100000245009300041210006900134300001200203490000800215520165600223653001501879100001701894700001301911700001501924700001801939700001701957700001901974700001801993700001502011700001402026856010602040 2006 eng d00aBlast2GO goes grid: developing a grid-enabled prototype for functional genomics analysis0 aBlast2GO goes grid developing a gridenabled prototype for functi a194-2040 v1203 a

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.

10ababelomics1 aAparicio, G.1 aGotz, S.1 aConesa, A.1 aSegrelles, D.1 aBlanquer, I.1 aGarcia, J., M.1 aHernandez, V.1 aRobles, M.1 aTalon, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1682313802090nas a2200193 4500008004100000245012600041210006900167300001100236490000700247520144700254653001501701653002501716100002401741700001601765700002301781700001401804700001501818856006301833 2005 eng d00aBABELOMICS: a suite of web tools for functional annotation and analysis of groups of genes in high-throughput experiments0 aBABELOMICS a suite of web tools for functional annotation and an aW460-40 v333 a

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.

10ababelomics10afunctional profiling1 aAl-Shahrour, Fatima1 aMinguez, P.1 aVaquerizas, J., M.1 aConde, L.1 aDopazo, J. uhttp://nar.oxfordjournals.org/content/33/suppl_2/W460.long01401nas a2200193 4500008004100000245010600041210006900147300001100216490000700227520075600234653001500990100001501005700001301020700002501033700001401058700001401072700001501086856010601101 2005 eng d00aBlast2GO: a universal tool for annotation, visualization and analysis in functional genomics research0 aBlast2GO a universal tool for annotation visualization and analy a3674-60 v213 a

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.

10ababelomics1 aConesa, A.1 aGotz, S.1 aGarcia-Gomez, J., M.1 aTerol, J.1 aTalon, M.1 aRobles, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1608147401648nas a2200241 4500008004100000245010900041210006900150300001100219490000700230520055300237653010300790653018900893653008001082100001601162700001401178700001601192700001501208700001701223700002201240700002101262700001701283856010601300 2002 eng d00aBioinformatics methods for the analysis of expression arrays: data clustering and information extraction0 aBioinformatics methods for the analysis of expression arrays dat a269-830 v983 aExpression 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.10aAbstracting and Indexing as Topic/methods *Cluster Analysis *Database Management Systems Databases10aComputer-Assisted/methods Information Storage and Retrieval/*methods Internet Medline National Library of Medicine (U.S.) Oligonucleotide Array Sequence Analysis/*methods United States10aGenetic Gene Expression Gene Expression Profiling/*methods Image Processing1 aTamames, J.1 aClark, D.1 aHerrero, J.1 aDopazo, J.1 aBlaschke, C.1 aFernandez, J., M.1 aOliveros, J., C.1 aValencia, A. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12141992