Gesellschaft für Informatik e.V.

Lecture Notes in Informatics

German Conference on Bioinformatics P-136, 54-63 (2008).

Gesellschaft für Informatik, Bonn


Andreas Beyer (ed.), Michael Schroeder (ed.)

Copyright © Gesellschaft für Informatik, Bonn


A propagation-based algorithm for inferring gene-disease assocations

Oron Vanunu and Roded Sharan


A fundamental challenge in human health is the identification of diseasecausing genes. Recently, several studies have tackled this challenge via a two-step approach: first, a linkage interval is inferred from population studies; second, a computational approach is used to prioritize genes within this interval. State-of-the-art methods for the latter task are based on the observation that genes causing the same or similar diseases tend to lie close to one another in a network of protein-protein or functional interactions. However, most of these approaches use only local network information in the inference process. Here we provide a global, network-based method for prioritizing disease genes. The method is based on formulating constraints on the prioritization function that relate to its smoothness over the network and usage of prior information. A propagation-based method is used to compute a function satisfying the constraints. We test our method on gene-disease association data in a cross-validation setting, and compare it to extant prioritization approaches. We show that our method provides the best overall performance, ranking the true causal gene first for 29\% of the 1,369 diseases with a known gene in the OMIM knowledgebase.

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Gesellschaft für Informatik, Bonn
ISBN 978-3-88579-226-0

Last changed 04.10.2013 18:19:01