Gesellschaft für Informatik e.V.

Lecture Notes in Informatics

German Conference on Bioinformatics 2005 (GCB 2005), 5.-7. October 2005, Hamburg, Germany P-71, 193-202 (2005).



Andrew Torda, Stefan Kurtz, Matthias Rarey (eds.)


Inferring regulatory systems with noisy pathway information

Christian Spieth , Felix Streichertn , Nora Speern and Andreas Zell


With increasing number of pathways available in public databases, the process of inferring gene regulatory networks becomes more and more feasible. The major problem of most of these pathways is that they are very often faulty or describe only parts of a regulatory system due to limitations of the experimental techniques or due to a focus specifically only on a subnetwork of a larger process. To address this issue, we propose a new multi-objective evolutionary algorithm in this paper, which infers gene regulatory systems from experimental microarray data by incorporating known pathways from publicly available databases. These pathways are used as an initial template for creating suitable models of the regulatory network and are then refined by the algorithm. With this approach, we were able to infer regulatory systems with incorporation of pathway information that is incomplete or even faulty.

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ISBN 3-88579-400-4

Last changed 24.01.2012 21:51:56