02349nas a2200181 4500008004100000022001400041245015400055210006900209260001500278300000700293490000600300520173800306100001502044700002402059700002102083700001502104856004802119 2011 eng d a1755-879400aA large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression0 alarge scale survey reveals that chromosomal copynumber alteratio c06/05/2011 a370 v43 a

Background

Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as cancer, harboring DNA copy number alterations (CNAs), will have a symptomatology strongly dependent on modules of functionally-related genes rather than on a unique "important" gene.

Methods

We carried out a systematic analysis of more than 140,000 observations of CNAs in cancers and searched by enrichments in gene functional modules associated to high frequencies of loss or gains.

Results

The analysis of CNAs in cancers clearly demonstrates the existence of a significant pattern of loss of gene modules functionally related to cancer initiation and progression along with the amplification of modules of genes related to unspecific defense against xenobiotics (probably chemotherapeutical agents). With the extension of this analysis to an Array-CGH dataset (glioblastomas) from The Cancer Genome Atlas we demonstrate the validity of this approach to investigate the functional impact of CNAs.

Conclusions

The presented results indicate promising clinical and therapeutic implications. Our findings also directly point out to the necessity of adopting a function-centric, rather a gene-centric, view in the understanding of phenotypes or diseases harboring CNAs.

1 aAlloza, E.1 aAl-Shahrour, Fatima1 aCigudosa, J., C.1 aDopazo, J. uhttp://www.biomedcentral.com/1755-8794/4/3702142nas 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.long02205nas a2200301 4500008004100000245007600041210006900117300001200186490000700198520130100205653001001506653002901516100001601545700002001561700001801581700002101599700001601620700001501636700002401651700002301675700001401698700001601712700002201728700001501750700001701765700001501782856010601797 2008 eng d00aGEPAS, a web-based tool for microarray data analysis and interpretation0 aGEPAS a webbased tool for microarray data analysis and interpret aW308-140 v363 a

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.

10agepas10amicroarray data analysis1 aTarraga, J.1 aMedina, Ignacio1 aCarbonell, J.1 aHuerta-Cepas, J.1 aMinguez, P.1 aAlloza, E.1 aAl-Shahrour, Fatima1 aVegas-Azcarate, S.1 aGoetz, S.1 aEscobar, P.1 aGarcia-Garcia, F.1 aConesa, A.1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1850880602196nas a2200217 4500008004100000245016500041210006900206300001000275490000700285520140700292653001501699653003501714100002401749700001601773700001601789700002001805700001501825700001701840700001501857856010601872 2007 eng d00aFatiGO +: a functional profiling tool for genomic data. Integration of functional annotation, regulatory motifs and interaction data with microarray experiments0 aFatiGO a functional profiling tool for genomic data Integration  aW91-60 v353 a

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.

10ababelomics10afunctional enrichment analysys1 aAl-Shahrour, Fatima1 aMinguez, P.1 aTarraga, J.1 aMedina, Ignacio1 aAlloza, E.1 aMontaner, D.1 aDopazo, J. uhttp://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=1747850401445nas 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.long01882nas 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=16845056