Detecting inconsistencies in large biological networks with answer set programming

Authors:
Martin Gebser;Torsten Schaub;Sven Thiele;Philippe Veber
Affiliations:
Institute for informatics, university of potsdam, potsdam, germany (e-mail: gebser@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de, sthiele@cs.uni-potsdam.de);Institute for informatics, university of potsdam, potsdam, germany (e-mail: gebser@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de, sthiele@cs.uni-potsdam.de);Institute for informatics, university of potsdam, potsdam, germany (e-mail: gebser@cs.uni-potsdam.de, torsten@cs.uni-potsdam.de, sthiele@cs.uni-potsdam.de);Institut cochin, paris, france (e-mail: philippe.veber@googlemail.com)
Venue:
Theory and Practice of Logic Programming
Year:
2011

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Abstract

We introduce an approach to detecting inconsistencies in large biological networks by using answer set programming. To this end, we build upon a recently proposed notion of consistency between biochemical/genetic reactions and high-throughput profiles of cell activity. We then present an approach based on answer set programming to check the consistency of large-scale data sets. Moreover, we extend this methodology to provide explanations for inconsistencies by determining minimal representations of conflicts. In practice, this can be used to identify unreliable data or to indicate missing reactions.