Title: Modelling gene and protein regulatory networks with Answer Set Programming

Authors: Timur Fayruzov, Jeroen Janssen, Dirk Vermeir, Chris Cornelis, Martine De Cock

Addresses: Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 (S9), 9000 Ghent, Belgium. ' Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. ' Department of Computer Science, Vrije Universiteit Brussel, Pleinlaan 2, 1050 Brussels, Belgium. ' Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 (S9), 9000 Ghent, Belgium. ' Department of Applied Mathematics and Computer Science, Ghent University, Krijgslaan 281 (S9), 9000 Ghent, Belgium; University of Washington, 1900 Commerce St., Tacoma, WA-98402, USA

Abstract: Recently, many approaches to model regulatory networks have been proposed in the systems biology domain. However, the task is far from being solved. In this paper, we propose an Answer Set Programming (ASP)-based approach to model interaction networks. We build a general ASP framework that describes the network semantics and allows modelling specific networks with little effort. ASP provides a rich and flexible toolbox that allows expanding the framework with desired features. In this paper, we tune our framework to mimic Boolean network behaviour and apply it to model the Budding Yeast and Fission Yeast cell cycle networks. The obtained steady states of these networks correspond to those of the Boolean networks.

Keywords: systems biology; ASP; answer set programming; network modelling; budding yeast; fission yeast; cell cycles; network steady state; steady cycles; gene regulatory networks; protein regulatory networks; bioinformatics; network semantics.

DOI: 10.1504/IJDMB.2011.039178

International Journal of Data Mining and Bioinformatics, 2011 Vol.5 No.2, pp.209 - 229

Published online: 24 Mar 2011 *

Full-text access for editors Access for subscribers Purchase this article Comment on this article