Modeling multi-valued biological interaction networks using fuzzy answer set programming. (English) Zbl 1397.68027

Summary: Fuzzy answer set programming (FASP) is an extension of the popular answer set programming (ASP) paradigm that allows for modeling and solving combinatorial search problems in continuous domains. The recent development of practical solvers for FASP has enabled its applicability to real-world problems. In this paper, we investigate the application of FASP in modeling the dynamics of gene regulatory networks (GRNs). A commonly used simplifying assumption to model the dynamics of GRNs is to assume only Boolean levels of activation of each node. 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 experimentally assess the efficiency of our method using real biological networks found in the literature, as well as on randomly-generated synthetic networks. The experiments demonstrate the applicability and usefulness of our proposed method to find network attractors.


68N17 Logic programming
68T37 Reasoning under uncertainty in the context of artificial intelligence
92C42 Systems biology, networks


ASP-G; Potassco
Full Text: DOI Link


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