Modeling multi-valued biological interaction networks using Fuzzy Answer Set Programming

Mushthofa, Mushthofa, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881, Ling-Hong, Hung, Kathleen, Marchal and Martine, De Cock 2018. Modeling multi-valued biological interaction networks using Fuzzy Answer Set Programming. Fuzzy Sets and Systems 345 , pp. 63-82. 10.1016/j.fss.2018.01.003

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Abstract

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.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Elsevier
ISSN:	0165-0114
Date of First Compliant Deposit:	20 February 2018
Date of Acceptance:	1 January 2018
Last Modified:	07 Nov 2023 03:45
URI:	https://orca.cardiff.ac.uk/id/eprint/109311

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