GraphWeb: mining heterogeneous biological networks for gene modules with functional significance.

@article{citeulike:2773255, abstract = {Deciphering heterogeneous cellular networks with embedded modules is a great challenge of current systems biology. Experimental and computational studies construct complex networks of molecules that describe various aspects of the cell such as transcriptional regulation, protein interactions and metabolism. Groups of interacting genes and proteins reflect network modules that potentially share regulatory mechanisms and relate to common function. Here, we present GraphWeb, a public web server for biological network analysis and module discovery. GraphWeb provides methods to: (1) integrate heterogeneous and multispecies data for constructing directed and undirected, weighted and unweighted networks; (ii) discover network modules using a variety of algorithms and topological filters and (iii) interpret modules using functional knowledge of the Gene Ontology and pathways, as well as regulatory features such as binding motifs and microRNA targets. GraphWeb is designed to analyse individual or multiple merged networks, search for conserved features across multiple species, mine large biological networks for smaller modules, discover novel candidates and connections for known pathways and compare results of high-throughput datasets. The GraphWeb is available at http://biit.cs.ut.ee/graphweb/.}, address = {University of Tartu, Institute of Computer Science, Liivi 2, Tartu, Estonia, EMBL Outstation, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK, University of Tartu, Institute of Molecular and Cell Biology, Riia 23a and QureTec Ltd. \"{U}likooli 6a, Tartu, Estonia.}, author = {Reimand, J\"{u}ri and Tooming, Laur and Peterson, Hedi and Adler, Priit and Vilo, Jaak }, citeulike-article-id = {2773255}, issn = {1362-4962}, journal = {Nucleic acids research}, keywords = {modularity}, month = {May}, posted-at = {2008-05-08 18:05:45}, priority = {3}, title = {GraphWeb: mining heterogeneous biological networks for gene modules with functional significance.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/18460544}, year = {2008} }

TY - JOUR ID - citeulike:2773255 L3 - citeulike-article-id:2773255 TI - GraphWeb: mining heterogeneous biological networks for gene modules with functional significance. JF - Nucleic acids research AD - University of Tartu, Institute of Computer Science, Liivi 2, Tartu, Estonia, EMBL Outstation, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, UK, University of Tartu, Institute of Molecular and Cell Biology, Riia 23a and QureTec Ltd. Ülikooli 6a, Tartu, Estonia. SN - 1362-4962 N2 - Deciphering heterogeneous cellular networks with embedded modules is a great challenge of current systems biology. Experimental and computational studies construct complex networks of molecules that describe various aspects of the cell such as transcriptional regulation, protein interactions and metabolism. Groups of interacting genes and proteins reflect network modules that potentially share regulatory mechanisms and relate to common function. Here, we present GraphWeb, a public web server for biological network analysis and module discovery. GraphWeb provides methods to: (1) integrate heterogeneous and multispecies data for constructing directed and undirected, weighted and unweighted networks; (ii) discover network modules using a variety of algorithms and topological filters and (iii) interpret modules using functional knowledge of the Gene Ontology and pathways, as well as regulatory features such as binding motifs and microRNA targets. GraphWeb is designed to analyse individual or multiple merged networks, search for conserved features across multiple species, mine large biological networks for smaller modules, discover novel candidates and connections for known pathways and compare results of high-throughput datasets. The GraphWeb is available at http://biit.cs.ut.ee/graphweb/. KW - modularity AU - Reimand, Jüri AU - Tooming, Laur AU - Peterson, Hedi AU - Adler, Priit AU - Vilo, Jaak PY - 2008/05/06/ UR - http://view.ncbi.nlm.nih.gov/pubmed/18460544 ER -