Theory and Practice of Logic Programming

Table of Contents - July 2011 - Volume 11, Special Issue 4-5 (27th International Conference on Logic Programming)  

Regular Papers

Automatic network reconstruction using ASP

MARKUS DURZINSKYa1, WOLFGANG MARWANa1, MAX OSTROWSKIa2, TORSTEN SCHAUBa2* and ANNEGRET WAGLERa3

a1 Magdeburg Centre for Systems Biology, Universität Magdeburg, Germany

a2 Universität Potsdam, Germany

a3 Université Blaise Pascal, Clermont-Ferrand, France

Abstract

Building biological models by inferring functional dependencies from experimental data is an important issue in Molecular Biology. To relieve the biologist from this traditionally manual process, various approaches have been proposed to increase the degree of automation. However, available approaches often yield a single model only, rely on specific assumptions, and/or use dedicated, heuristic algorithms that are intolerant to changing circumstances or requirements in the view of the rapid progress made in Biotechnology. Our aim is to provide a declarative solution to the problem by appeal to Answer Set Programming (ASP) overcoming these difficulties. We build upon an existing approach to Automatic Network Reconstruction proposed by part of the authors. This approach has firm mathematical foundations and is well suited for ASP due to its combinatorial flavor providing a characterization of all models explaining a set of experiments. The usage of ASP has several benefits over the existing heuristic algorithms. First, it is declarative and thus transparent for biological experts. Second, it is elaboration tolerant and thus allows for an easy exploration and incorporation of biological constraints. Third, it allows for exploring the entire space of possible models. Finally, our approach offers an excellent performance, matching existing, special-purpose systems.

(Online publication July 06 2011)

* Affiliated with Simon Fraser University, Canada, and Griffith University, Australia.