Protein interaction inference using particle swarm optimization algorithm

Authors:
Mudassar Iqbal;Alex A. Freitas;Colin G. Johnson
Affiliations:
Centre for Biomedical Informatics and Computing Lab., University of Kent, Canterbury, UK;Centre for Biomedical Informatics and Computing Lab., University of Kent, Canterbury, UK;Centre for Biomedical Informatics and Computing Lab., University of Kent, Canterbury, UK
Venue:
EvoBIO'08 Proceedings of the 6th European conference on Evolutionary computation, machine learning and data mining in bioinformatics
Year:
2008

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Abstract

Many processes in the cell involve interaction among the proteins and determination of the networks of such interactions is of immense importance towards the complete understanding of cellular functions. As the experimental techniques for this purpose are expensive and potentially erroneous, there are many computational methods being put forward for prediction of protein-protein interactions. These methods use different genomic features for indirect inference of protein- protein interactions. As the interaction among two proteins is facilitated by domains, there are many methods being put forward for inference of such interactions using the specificity of assignment of domains to proteins. We present here an heuristic optimization method, particle swarm optimization, which predicts protein-protein interaction by using the domain assignments information. Results are compared with another known method which predicts domain interactions by casting the problem of interactions inference as a maximum satisfiability (MAX-SAT) problem.