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Inference of Protein Function from the Structure of Interaction Networks

  • Oliver Mason
  • Mark Verwoerd
  • Peter Clifford
Chapter

Abstract

We consider the problem of using graph-theoretical techniques to predict the function of unannotated proteins in an organism’s proteome. Specifically, we present an overview of the major methods for predicting protein function based on interaction network structure and describe an abstract framework within which these methods can be treated in a unified fashion. We also present a comparison of the proposed methods and highlight some open theoretical and practical questions in the area.

Keywords

Protein function prediction Graph algorithms Graph multicuts Markov random fields 

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Notes

Acknowledgements

This work was partially supported by Science Foundation Ireland (SFI) grant 03/RP1/I382 and the Irish Higher Education Authority (HEA) PRTLI Network Mathematics grant. Neither Science Foundation Ireland nor the Higher Education Authority is responsible for any use of data appearing in this publication.

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  1. 1.Hamilton InstituteNUI MaynoothMaynoothIreland

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