Towards Inferring Protein Interactions: Challenges and Solutions

Publication Type

Journal Article

Publication Date

2006

Abstract

Discovering interacting proteins has been an essential part of functional genomics. However, existing experimental techniques only uncover a small portion of any interactome. Furthermore, these data often have a very high false rate. By conceptualizing the interactions at domain level, we provide a more abstract representation of interactome, which also facilitates the discovery of unobserved protein-protein interactions. Although several domain-based approaches have been proposed to predict protein-protein interactions, they usually assume that domain interactions are independent on each other for the convenience of computational modeling. A new framework to predict protein interactions is proposed in this paper, where no assumption is made about domain interactions. Protein interactions may be the result of multiple domain interactions which are dependent on each other. A conjunctive norm form representation is used to capture the relationships between protein interactions and domain interactions. The problem of interaction inference is then modeled as a constraint satisfiability problem and solved via linear programing. Experimental results on a combined yeast data set have demonstrated the robustness and the accuracy of the proposed algorithm. Moreover, we also map some predicted interacting domains to three-dimensional structures of protein complexes to show the validity of our predictions.

Discipline

Bioinformatics | Computer Sciences

Research Areas

Information Systems and Management

Publication

EURASIP Journal on Applied Signal Processing

Volume

2006

First Page

1

Last Page

14

ISSN

1687-6180

Identifier

10.1155/ASP/2006/37349

Publisher

Springer Verlag

Comments

Special Issue in Advanced Signal Processing Techniques in Bioinformatics

Additional URL

http://dx.doi.org/10.1155/ASP/2006/37349

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