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Message-passing algorithms for the prediction of protein domain interactions from proteinprotein interaction data
Mudassar Iqbal, Alex A. Freitas, Colin G. Johnson, and Massimo Vergassola
Bioinformatics, 24(18):182-196, September 2008 [doi].Abstract
Motivation: Cellular processes often hinge upon specific interactions among proteins, and knowledge of these processes at a system level constitutes a major goal of proteomics. In particular, a greater understanding of protein-protein interactions can be gained via a more detailed investigation of the protein domain interactions that mediate the interactions of proteins. Existing high-throughput experimental techniques assay protein-protein interactions, yet they do not provide any direct information on the interactions among domains. Inferences concerning the latter can be made by analysis of the domain composition of a set of proteins and their interaction map. This inference problem is non-trivial, however, due to the high level of noise generally present in experimental data concerning protein-protein interactions. This noise leads to contradictions, i.e. the impossibility of having a pattern of domain interactions compatible with the protein-protein interaction map.
Results: We formulate the problem of prediction of protein domain interactions in a form that lends itself to the application of belief propagation, a powerful algorithm for such inference problems, which is based on message passing. The input to our algorithm is an interaction map among a set of proteins, and a set of domain assignments to the relevant proteins. The output is a list of probabilities of interaction between each pair of domains. Our method is able to effectively cope with errors in the protein-protein interaction dataset and systematically resolve contradictions. We applied the method to a dataset concerning the budding yeast Saccharomyces cerevisiae and tested the quality of our predictions by cross-validation on this dataset, by comparison with existing computational predictions, and finally with experimentally available domain interactions. Results compare favourably to those by existing algorithms.
Availability: A C language implementation of the algorithm is available upon request.
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@article{2808, author = {Mudassar Iqbal and Alex A. Freitas and Colin G. Johnson and Massimo Vergassola}, title = {Message-passing algorithms for the prediction of protein domain interactions from proteinprotein interaction data}, month = {September}, year = {2008}, pages = {182-196}, keywords = {determinacy analysis, Craig interpolants}, note = {}, doi = {10.1093/bioinformatics/btn366 }, url = {http://www.cs.kent.ac.uk/pubs/2008/2808}, publication_type = {article}, submission_id = {12753_1220878394}, ISSN = {1460-2059}, journal = {Bioinformatics}, volume = {24}, number = {18}, publisher = {Oxford University Press}, }