title: Algorithms for inferring qualitative models of biological networks.
abstract: Modeling genetic networks and metabolic networks is an important topic in bioinformatics. We propose a qualitative network model which is a combination of the Boolean network and qualitative reasoning, where qualitative reasoning is a kind of reasoning method well-studied in Artificial Intelligence. We also present algorithms for inferring qualitative networks from time series data and an algorithm for inferring S-systems (synergistic and saturable systems) from time series data, where S-systems are based on a particular kind of nonlinear differential equation and have been applied to the analysis of various biological systems.
authors.affiliation: Human Genome Center, University of Tokyo, Japan. takutsu@ims.u-tokyo.ac.jp
authors.forename: T
authors.initials: T
authors.lastname: Akutsu
authors.forename: S
authors.initials: S
authors.lastname: Miyano
authors.forename: S
authors.initials: S
authors.lastname: Kuhara
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D015870:Gene Expression; D008660:Metabolism; D008954:Models, Biological; D008957:Models, Genetic; D017711:Nonlinear Dynamics