Abstract
In this chapter, we present and interpret some operations on biological networks that can easily performed with NeAT, a set of Web tools aimed at studying biological networks (or graphs) and classifications. These approaches are of particular interest for biologists and scientists who need to assess the reliability of new datasets (either experimental or predicted) by comparing them to established references. Firstly, we describe the steps that will allow a nonspecialist user to compare two networks to compute their union and the statistical significance of their intersection. Next, we show how to map functional classes (e.g., GO categories, sets of regulons or complexes) onto a biological network. A third protocol explains how to compare two sets of functional classes, e.g., to assess statistically the biological relevance of some computationally returned groups of genes (clustering). The metrics as well as the results obtained by following the different protocols are extensively described and explained. NeAT is available at the following URL: http://rsat.bigre.ulb.ac.be/rsat/index_neat.html.
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Acknowledgments
KULeuven SCD-SISTA lab is funded by the Research Council KUL (GOA MaNet, GOA AMBioRICS, CoE EF/05/007 SymBioSys, PROMETA, START 1, several PhD/postdoc and fellow grants, GOA 2006/12), FWO [PhD/postdoc grants, projects G.0241.04 (Functional Genomics), G.0499.04 (Statistics), G.0232.05 (Cardiovascular), G.0318.05 (subfunctionalization), G.0553.06 (VitamineD), G.0302.07 (SVM/Kernel), research communities (ICCoS, ANMMM, MLDM)], G.0733.09 3UTR; G. 082409 (EGFR), G.0254.05 (Genetics of human heart develoment), IWT (PhD Grants, GBOU-McKnow-E (Knowledge management algorithms), GBOU-ANA (biosensors), TAD-BioScope-IT, Silicos; SBO-BioFrame, SBO-MoKa, TBM Endometriosis), the Belgian Federal Science Policy Office [IUAP P6/25 (BioMaGNet, Bioinformatics and Modeling: from Genomes to Networks, 2007–2011), IUAP P5/25 (Molecular Pathology of Genetic Diseases) and the EU-RTD (ERNSI: European Research Network on System Identification; FP6-NoE Biopattern; FP6-IP e-Tumours, FP6-MC-EST Bioptrain, FP6-STREP Strokemap). Sylvain BrohÕe is ChargÕ de Recherches at the Fonds National de la Recherche Scientifique (FNRS) de la CommunautÕ FranÓaise de Belgique and was supported by a post-doc grant of the CheartED project (in the SISTA lab).
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Brohée, S. (2012). Using the NeAT Toolbox to Compare Networks to Networks, Clusters to Clusters, and Network to Clusters. In: van Helden, J., Toussaint, A., Thieffry, D. (eds) Bacterial Molecular Networks. Methods in Molecular Biology, vol 804. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-361-5_18
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DOI: https://doi.org/10.1007/978-1-61779-361-5_18
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