NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways

@article{citeulike:2863207, abstract = {The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources. 10.1093/nar/gkn336}, author = {Brohee, Sylvain and Faust, Karoline and Lima-Mendez, Gipsi and Sand, Olivier and Janky, Rekin's and Vanderstocken, Gilles and Deville, Yves and van Helden, Jacques }, citeulike-article-id = {2863207}, doi = {http://dx.doi.org/10.1093/nar/gkn336}, journal = {Nucl. Acids Res.}, keywords = {bioinformatics, cluster, network, pathways, software, webserver}, month = {June}, pages = {gkn336+}, posted-at = {2008-06-05 02:58:50}, priority = {2}, title = {NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways}, url = {http://dx.doi.org/10.1093/nar/gkn336}, year = {2008} }

TY - JOUR ID - citeulike:2863207 L3 - citeulike-article-id:2863207 TI - NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways JF - Nucl. Acids Res. SP - gkn336 N2 - The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources. 10.1093/nar/gkn336 KW - bioinformatics KW - cluster KW - network KW - pathways KW - software KW - webserver AU - Brohee, Sylvain AU - Faust, Karoline AU - Lima-Mendez, Gipsi AU - Sand, Olivier AU - Janky, Rekin's AU - Vanderstocken, Gilles AU - Deville, Yves AU - van Helden, Jacques PY - 2008/06/04/ UR - http://dx.doi.org/10.1093/nar/gkn336 ER -