Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data. Export

@article{boyer:graphs, abstract = {Motivation: Modern comparative genomics does not restrict to sequence but involves the comparison of metabolic pathways or protein-protein 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@inrialpes.fr.}, address = {INRIA Rh\^{o}ne-Alpes, HELIX Group 655 avenue de l'Europe, 38334 Montbonnot Cedex, France.}, author = {Boyer, F. and Morgat, A. and Labarre, L. and Pothier, J. and Viari, A.}, citeulike-article-id = {423833}, citeulike-linkout-0 = {http://view.ncbi.nlm.nih.gov/pubmed/16216829}, citeulike-linkout-1 = {http://www.hubmed.org/display.cgi?uids=16216829}, day = {1}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {graph, synteny, thesis}, month = {December}, number = {23}, pages = {4209--4215}, posted-at = {2008-11-12 16:53:00}, priority = {2}, title = {Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/16216829}, volume = {21}, year = {2005} }

TY - JOUR ID - boyer:graphs L3 - citeulike-article-id:423833 N2 - Motivation: Modern comparative genomics does not restrict to sequence but involves the comparison of metabolic pathways or protein-protein 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@inrialpes.fr. IS - 23 JF - Bioinformatics SN - 1367-4803 AD - INRIA Rhône-Alpes, HELIX Group 655 avenue de l'Europe, 38334 Montbonnot Cedex, France. EP - 4215 TI - Syntons, metabolons and interactons: an exact graph-theoretical approach for exploring neighbourhood between genomic and functional data. VL - 21 SP - 4209 KW - graph KW - synteny KW - thesis AU - Boyer, F AU - Morgat, A AU - Labarre, L AU - Pothier, J AU - Viari, A PY - 2005/12/01/ UR - http://view.ncbi.nlm.nih.gov/pubmed/16216829 ER -