02732nas a2200205 4500008004100000245017300041210006900214300000800283490000600291520176400297653006302061653002302124653005002147653015802197100001302355700002302368700001502391700001402406856010602420 2007 eng d00aIdentification of conserved domains in the promoter regions of nitric oxide synthase 2: implications for the species-specific transcription and evolutionary differences0 aIdentification of conserved domains in the promoter regions of n a2710 v83 aBACKGROUND: The majority of the genes involved in the inflammatory response are highly conserved in mammals. These genes are not significantly expressed under normal conditions and are mainly regulated at the transcription and prost-transcriptional level. Transcription from the promoters of these genes is very dependent on NF-kappaB activation, which integrates the response to diverse extracellular stresses. However, in spite of the high conservation of the pattern of promoter regulation in kappaB-regulated genes, there is inter-species diversity in some genes. One example is nitric oxide synthase 2 (NOS-2), which exhibits a species-specific pattern of expression in response to infection or pro-inflammatory challenge. RESULTS: We have conducted a comparative genomic analysis of NOS-2 with different bioinformatic approaches. This analysis shows that in the NOS-2 gene promoter the position and the evolutionary divergence of some conserved regions are different in rodents and non-rodent mammals, and in particular in primates. Two not previously described distal regions in rodents that are similar to the unique upstream region responsible of the NF-kappaB activation of NOS-2 in humans are fragmented and translocated to different locations in the rodent promoters. The rodent sequences moreover lack the functional kappaB sites and IFN-gamma response sites present in the homologous human, rhesus monkey and chimpanzee regions. The absence of kappaB binding in these regions was confirmed by electrophoretic mobility shift assays. CONCLUSION: The data presented reveal divergence between rodents and other mammals in the location and functionality of conserved regions of the NOS-2 promoter containing NF-kappaB and IFN-gamma response elements.10aAnimals Base Sequence Conserved Sequence Enhancer Elements10aGenetic *Evolution10aGenetic Response Elements Species Specificity10aMolecular Humans Inflammation/metabolism Interferon-gamma/metabolism Mice NF-kappa B/metabolism Nitric Oxide Synthase Type II/*genetics *Promoter Regions1 aRico, D.1 aVaquerizas, J., M.1 aDopazo, H.1 aBosca, L. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1768618201445nas 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.long01522nas a2200205 4500008004100000245013200041210006900173300000700242490000600249520054800255653009100803653004200894653014400936653006001080100001701140700002301157700001501180700001501195856010601210 2006 eng d00aExploring the reasons for the large density of triplex-forming oligonucleotide target sequences in the human regulatory regions0 aExploring the reasons for the large density of triplexforming ol a630 v73 aBACKGROUND: DNA duplex sequences that can be targets for triplex formation are highly over-represented in the human genome, especially in regulatory regions. RESULTS: Here we studied using bioinformatics tools several properties of triplex target sequences in an attempt to determine those that make these sequences so special in the genome. CONCLUSION: Our results strongly suggest that the unique physical properties of these sequences make them particularly suitable as "separators" between protein-recognition sites in the promoter region.10aAnimals Base Sequence Computational Biology DNA/chemistry/*genetics/*metabolism Genome10aGenetic/genetics Regulatory Sequences10aHuman/genetics Humans Mice Nucleic Acid Conformation Nucleotides/genetics Oligonucleotides/chemistry/*genetics/*metabolism Promoter Regions10aNucleic Acid/*genetics Transcription Factors/metabolism1 aGoni, J., R.1 aVaquerizas, J., M.1 aDopazo, J.1 aOrozco, M. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1656681701882nas a2200313 4500008004100000245005200041210005100093300001200144490000700156520100300163653001001166653002901176100001701205700001601222700002101238700001601259700002301275700001401298700001601312700001301328700001801341700001401359700001901373700001501392700001601407700002401423700001501447856010601462 2006 eng d00aNext station in microarray data analysis: GEPAS0 aNext station in microarray data analysis GEPAS aW486-910 v343 a

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

10agepas10amicroarray data analysis1 aMontaner, D.1 aTarraga, J.1 aHuerta-Cepas, J.1 aBurguet, J.1 aVaquerizas, J., M.1 aConde, L.1 aMinguez, P.1 aVera, J.1 aMukherjee, S.1 aValls, J.1 aPujana, M., A.1 aAlloza, E.1 aHerrero, J.1 aAl-Shahrour, Fatima1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1684505601783nas a2200253 4500008004100000245010200041210006900143300001100212490000700223520089100230653004301121653008001164653002701244653005601271100001401327700002301341700001501364700001501379700001601394700001701410700002001427700001501447856006701462 2006 eng d00aPupaSuite: finding functional single nucleotide polymorphisms for large-scale genotyping purposes0 aPupaSuite finding functional single nucleotide polymorphisms for aW621-50 v343 a

We have developed a web tool, PupaSuite, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect, specifically oriented to help in the design of large-scale genotyping projects. PupaSuite uses a collection of data on SNPs from heterogeneous sources and a large number of pre-calculated predictions to offer a flexible and intuitive interface for selecting an optimal set of SNPs. It improves the functionality of PupaSNP and PupasView programs and implements new facilities such as the analysis of user’s data to derive haplotypes with functional information. A new estimator of putative effect of polymorphisms has been included that uses evolutionary information. Also SNPeffect database predictions have been included. The PupaSuite web interface is accessible through http://pupasuite.bioinfo.cipf.es and through http://www.pupasnp.org.

10aAlgorithms Computer Graphics Databases10aMolecular Genotype Haplotypes Internet Linkage Disequilibrium *Polymorphism10aNucleic Acid Evolution10aSingle Nucleotide *Software User-Computer Interface1 aConde, L.1 aVaquerizas, J., M.1 aDopazo, H.1 aArbiza, L.1 aReumers, J.1 aRousseau, F.1 aSchymkowitz, J.1 aDopazo, J. uhttp://nar.oxfordjournals.org/cgi/content/full/34/suppl_2/W62102090nas 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.long02188nas a2200241 4500008004100000245009500041210006900136300001200205490000700217520141200224653001001636653002901646100002301675700001401698700002001712700001601732700001601748700002101764700002401785700001601809700001501825856010601840 2005 eng d00aGEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data0 aGEPAS an experimentoriented pipeline for the analysis of microar aW616-200 v333 a

The Gene Expression Profile Analysis Suite, GEPAS, has been running for more than three years. With >76,000 experiments analysed during the last year and a daily average of almost 300 analyses, GEPAS can be considered a well-established and widely used platform for gene expression microarray data analysis. GEPAS is oriented to the analysis of whole series of experiments. Its design and development have been driven by the demands of the biomedical community, probably the most active collective in the field of microarray users. Although clustering methods have obviously been implemented in GEPAS, our interest has focused more on methods for finding genes differentially expressed among distinct classes of experiments or correlated to diverse clinical outcomes, as well as on building predictors. There is also a great interest in CGH-arrays which fostered the development of the corresponding tool in GEPAS: InSilicoCGH. Much effort has been invested in GEPAS for developing and implementing efficient methods for functional annotation of experiments in the proper statistical framework. Thus, the popular FatiGO has expanded to a suite of programs for functional annotation of experiments, including information on transcription factor binding sites, chromosomal location and tissues. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://www.gepas.org.

10agepas10amicroarray data analysis1 aVaquerizas, J., M.1 aConde, L.1 aYankilevich, P.1 aCabezon, A.1 aMinguez, P.1 aDiaz-Uriarte, R.1 aAl-Shahrour, Fatima1 aHerrero, J.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1598054802607nas a2200181 4500008004100000245009100041210006900132300001200201490000700213520184100220653007402061653005202135653007802187100001602265700002302281700001502304856010602319 2005 eng d00aHighly specific and accurate selection of siRNAs for high-throughput functional assays0 aHighly specific and accurate selection of siRNAs for highthrough a1376-820 v213 aMOTIVATION: Small interfering RNA (siRNA) is widely used in functional genomics to silence genes by decreasing their expression to study the resulting phenotypes. The possibility of performing large-scale functional assays by gene silencing accentuates the necessity of a software capable of the high-throughput design of highly specific siRNA. The main objective sought was the design of a large number of siRNAs with appropriate thermodynamic properties and, especially, high specificity. Since all the available procedures require, to some extent, manual processing of the results to guarantee specific results, specificity constitutes to date, the major obstacle to the complete automation of all the steps necessary for the selection of optimal candidate siRNAs. RESULT: Here, we present a program that for the first time completely automates the search for siRNAs. In SiDE, the most complete set of rules for the selection of siRNA candidates (including G+C content, nucleotides at determined positions, thermodynamic properties, propensity to form internal hairpins, etc.) is implemented and moreover, specificity is achieved by a conceptually new method. After selecting possible siRNA candidates with the optimal functional properties, putative unspecific matches, which can cause cross-hybridization, are checked in databases containing a unique entry for each gene. These truly non-redundant databases are constructed from the genome annotations (Ensembl). Also intron/exon boundaries, presence of polymorphisms (single nucleotide polymorphisms) specificity for either gene or transcript, and other features can be selected to be considered in the design of siRNAs. AVAILABILITY: The program is available as a web server at http://side.bioinfo.cnio.es. The program was written under the GPL license. CONTACT: jdopazo@cnio.es.10a*Algorithms Base Sequence *Gene Silencing Molecular Sequence Data RNA10aRNA/*methods *Software *User-Computer Interface10aSmall Interfering/*genetics Sequence Alignment/*methods Sequence Analysis1 aSantoyo, J.1 aVaquerizas, J., M.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1559135702075nas a2200205 4500008004100000245012600041210006900167300001100236490000700247520124100254653010501495653005601600100001401656700002301670700002101693700001901714700001501733700001501748856010601763 2005 eng d00aPupasView: a visual tool for selecting suitable SNPs, with putative pathological effect in genes, for genotyping purposes0 aPupasView a visual tool for selecting suitable SNPs with putativ aW501-50 v333 aWe have developed a web tool, PupasView, for the selection of single nucleotide polymorphisms (SNPs) with potential phenotypic effect. PupasView constitutes an interactive environment in which functional information and population frequency data can be used as sequential filters over linkage disequilibrium parameters to obtain a final list of SNPs optimal for genotyping purposes. PupasView is the first resource that integrates phenotypic effects caused by SNPs at both the translational and the transcriptional level. PupasView retrieves SNPs that could affect conserved regions that the cellular machinery uses for the correct processing of genes (intron/exon boundaries or exonic splicing enhancers), predicted transcription factor binding sites and changes in amino acids in the proteins for which a putative pathological effect is calculated. The program uses the mapping of SNPs in the genome provided by Ensembl. PupasView will be of much help in studies of multifactorial disorders, where the use of functional SNPs will increase the sensitivity of the identification of the genes responsible for the disease. The PupasView web interface is accessible through http://pupasview.ochoa.fib.es and through http://www.pupasnp.org.10aComputer Graphics Genes *Genetic Predisposition to Disease Genotype Internet Phenotype *Polymorphism10aSingle Nucleotide *Software User-Computer Interface1 aConde, L.1 aVaquerizas, J., M.1 aFerrer-Costa, C.1 ade la Cruz, X.1 aOrozco, M.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1598052201390nas a2200169 4500008004100000245006900041210006700110300001100177490000700188520056300195653024500758653005201003100002301055700001501078700002101093856010601114 2004 eng d00aDNMAD: web-based diagnosis and normalization for microarray data0 aDNMAD webbased diagnosis and normalization for microarray data a3656-80 v203 aSUMMARY: We present a web server for Diagnosis and Normalization of MicroArray Data (DNMAD). DNMAD includes several common data transformations such as spatial and global robust local regression or multiple slide normalization, and allows for detecting several kinds of errors that result from the manipulation and the image analysis of the arrays. This tool offers a user-friendly interface, and is completely integrated within the Gene Expression Pattern Analysis Suite (GEPAS). AVAILABILITY: The tool is accessible on-line at http://dnmad.bioinfo.cnio.es.10aAlgorithms Database Management Systems Gene Expression Profiling/*methods/standards Information Storage and Retrieval/*methods *Internet Oligonucleotide Array Sequence Analysis/*methods/standards Sequence Alignment/methods Sequence Analysis10aDNA/*methods *Software *User-Computer Interface1 aVaquerizas, J., M.1 aDopazo, J.1 aDiaz-Uriarte, R. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1524709402102nas a2200217 4500008004100000245007500041210006900116300001200185490000700197520140300204653001001607653002901617100001601646700002301662700002401685700001401709700001501723700002501738700001501763856010601778 2004 eng d00aNew challenges in gene expression data analysis and the extended GEPAS0 aNew challenges in gene expression data analysis and the extended aW485-910 v323 a

Since the first papers published in the late nineties, including, for the first time, a comprehensive analysis of microarray data, the number of questions that have been addressed through this technique have both increased and diversified. Initially, interest focussed on genes coexpressing across sets of experimental conditions, implying, essentially, the use of clustering techniques. Recently, however, interest has focussed more on finding genes differentially expressed among distinct classes of experiments, or correlated to diverse clinical outcomes, as well as in building predictors. In addition to this, the availability of accurate genomic data and the recent implementation of CGH arrays has made mapping expression and genomic data on the chromosomes possible. There is also a clear demand for methods that allow the automatic transfer of biological information to the results of microarray experiments. Different initiatives, such as the Gene Ontology (GO) consortium, pathways databases, protein functional motifs, etc., provide curated annotations for genes. Whereas many resources on the web focus mainly on clustering methods, GEPAS has evolved to cope with the aforementioned new challenges that have recently arisen in the field of microarray data analysis. The web-based pipeline for microarray gene expression data, GEPAS, is available at http://gepas.bioinfo.cnio.es.

10agepas10amicroarray data analysis1 aHerrero, J.1 aVaquerizas, J., M.1 aAl-Shahrour, Fatima1 aConde, L.1 aMateos, A.1 aDiaz-Uriarte, J., S.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1521543402164nas a2200229 4500008004100000245009400041210006900135300001100204490000700215520128900222653008201511653001201593653009301605100001401698700002301712700001601735700002401751700002201775700001601797700001501813856010601828 2004 eng d00aPupaSNP Finder: a web tool for finding SNPs with putative effect at transcriptional level0 aPupaSNP Finder a web tool for finding SNPs with putative effect  aW242-80 v323 aWe have developed a web tool, PupaSNP Finder (PupaSNP for short), for high-throughput searching for single nucleotide polymorphisms (SNPs) with potential phenotypic effect. PupaSNP takes as its input lists of genes (or generates them from chromosomal coordinates) and retrieves SNPs that could affect the conserved regions that the cellular machinery uses for the correct processing of genes (intron/exon boundaries or exonic splicing enhancers), predicted transcription factor binding sites (TFBS) and changes in amino acids in the proteins. The program uses the mapping of SNPs in the genome provided by Ensembl. Additionally, user-defined SNPs (not yet mapped in the genome) can be easily provided to the program. Also, additional functional information from Gene Ontology, OMIM and homologies in other model organisms is provided. In contrast to other programs already available, which focus only on SNPs with possible effect in the protein, PupaSNP includes SNPs with possible transcriptional effect. PupaSNP will be of significant help in studies of multifactorial disorders, where the use of functional SNPs will increase the sensitivity of identification of the genes responsible for the disease. The PupaSNP web interface is accessible through http://pupasnp.bioinfo.cnio.es.10aAmino Acid Substitution Binding Sites Humans Internet Phenotype *Polymorphism10aGenetic10aSingle Nucleotide RNA Splicing *Software Transcription Factors/metabolism *Transcription1 aConde, L.1 aVaquerizas, J., M.1 aSantoyo, J.1 aAl-Shahrour, Fatima1 aRuiz-Llorente, S.1 aRobledo, M.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1521538801500nas a2200217 4500008004100000245007700041210006900118300001100187490000700198520080200205653001001007653002901017100001601046700002401062700002101086700001501107700002301122700001601145700001501161856010601176 2003 eng d00aGEPAS: A web-based resource for microarray gene expression data analysis0 aGEPAS A webbased resource for microarray gene expression data an a3461-70 v313 a

We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).

10agepas10amicroarray data analysis1 aHerrero, J.1 aAl-Shahrour, Fatima1 aDiaz-Uriarte, R.1 aMateos, A.1 aVaquerizas, J., M.1 aSantoyo, J.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=12824345