Prediction of combinatorial protein-protein interaction networks from expression data using statistics on conditional probability

Authors:
Takatoshi Fujiki;Etsuko Inoue;Takuya Yoshihiro;Masaru Nakagawa
Affiliations:
Faculty of Systems Engineering, Wakayama University, Wakayama, Japan;Faculty of Systems Engineering, Wakayama University, Wakayama, Japan;Faculty of Systems Engineering, Wakayama University, Wakayama, Japan;Faculty of Systems Engineering, Wakayama University, Wakayama, Japan
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Year:
2010

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Abstract

In this paper we propose a method to retrieve combinatorial protein-protein interaction to predict the interaction networks from protein expression data based on statistics on conditional probability. Our method retrieves the combinations of three proteins A, B and C which include combinatorial effects among them. The combinatorial effect considered in this paper does not include the "sole effect" between two proteins A-C or B-C, so that we can retrieve the combinatorial effect which appears only when proteins A, B and C get together. We evaluate our method with a real protein expression data set and obtain several combinations of three proteins in which protein-protein interactions are prediced.