Computing attractors of multi-valued Gene Regulatory Networks using Fuzzy Answer Set Programming

Abstract

Fuzzy Answer Set Programming (FASP) extends the popular Answer Set Programming (ASP) paradigm to modeling and solving combinatorial search problems in continuous domains. The recent development of FASP solvers has turned FASP into a practical tool for solving real-world problems. In this paper, we propose the use of FASP for modeling the dynamics of Gene Regulatory Networks (GRNs), an important kind of biological network. A commonly used simplifying assumption to model the dynamics of GRNs is to assume only Boolean levels of activation of each node. ASP has been used to model such Boolean networks. Our work extends this Boolean network formalism by allowing multi-valued activation levels. We show how FASP can be used to model the dynamics of such networks. We also experimentally assess the plausibility of our method using real biological networks found in the literature.