Author:

Keywords:

Science & Technology, Life Sciences & Biomedicine, Biochemistry & Molecular Biology, FUNCTIONAL MODULES, PROTEIN COMPLEXES, PREDICTION, REPRESENTATION, ALGORITHMS, Cluster Analysis, Computer Graphics, Gene Expression Regulation, Internet, Metabolic Networks and Pathways, Oligonucleotide Array Sequence Analysis, Protein Interaction Mapping, Signal Transduction, Software, 05 Environmental Sciences, 06 Biological Sciences, 08 Information and Computing Sciences, Developmental Biology, 31 Biological sciences, 34 Chemical sciences, 41 Environmental sciences

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.