Bioinformatics Advance Access originally published online on October 10, 2005
Bioinformatics 2005 21(23):4209-4215; doi:10.1093/bioinformatics/bti711
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Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data
1INRIA Rhône-Alpes, HELIX Group 655 avenue de l'Europe, 38334 Montbonnot Cedex, France
2Swiss Institute of Bioinformatics, Swiss-Prot Group 1 rue Michel Servet, CH-1211 Geneva, Switzerland
3UMR 8030, Genoscope, Centre National de Séquençage 2 rue Gaston Crémieux, CP570691057 Evry cedex, France
4Atelier de BioInformatique, Université Paris VI 12 rue Cuvier, 75005 Paris, France
*To whom correspondence should be addressed.
Motivation: Modern comparative genomics does not restrict to sequence but involves the comparison of metabolic pathways or proteinprotein interactions as well. Central in this approach is the concept of neighbourhood between entities (genes, proteins, chemical compounds). Therefore there is a growing need for new methods aiming at merging the connectivity information from different biological sources in order to infer functional coupling.
Results: We present a generic approach to merge the information from two or more graphs representing biological data. The method is based on two concepts. The first one, the correspondence multigraph, precisely defines how correspondence is performed between the primary data-graphs. The second one, the common connected components, defines which property of the multigraph is searched for. Although this problem has already been informally stated in the past few years, we give here a formal and general statement together with an exact algorithm to solve it.
Availability: The algorithm presented in this paper has been implemented in C. Source code is freely available for download at: http://www.inrialpes.fr/helix/people/viari/cccpart
Contact: Alain.Viari{at}inrialpes.fr
Received on June 1, 2005; revised on July 22, 2005; accepted on October 6, 2005
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