02142nas 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=1909423001445nas 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=1679039302090nas 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.long01648nas 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