Gesellschaft für Informatik e.V.

Lecture Notes in Informatics


German Conference on Bioinformatics 2004, GCB 2004, October 4-6, 2004, Bielefeld, Germany P-53, 159-168 (2004).

GI, Gesellschaft für Informatik, Bonn
2004


Editors

Robert Giegerich (ed.), Jens Stoye (ed.)


Copyright © GI, Gesellschaft für Informatik, Bonn

Contents

Probabilistic methods for predicting protein functions in protein-protein interaction networks

Christoph Best , Ralf Zimmer and Joannis Apostolakis

Abstract


We discuss probabilistic methods for predicting protein functions from protein-protein interaction networks. Previous work based on Markov Randon Fields is extended and compared to a general machine-learning theoretic approach. Using actual protein interaction networks for yeast from the MIPS database and GO-SLIM function assignments, we compare the predictions of the different probabilistic methods and of a standard support vector machine. It turns out that, with the currently available networks, the simple methods based on counting frequencies perform as well as the more sophisticated approaches.


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GI, Gesellschaft für Informatik, Bonn
ISBN 3-88579-382-2


Last changed 04.10.2013 18:03:58