title: Rule-based modelling and simulation of biochemical systems with molecular finite automata.
abstract: The authors propose a theoretical formalism, molecular finite automata (MFA), to describe individual proteins as rule-based computing machines. The MFA formalism provides a framework for modelling individual protein behaviours and systems-level dynamics via construction of programmable and executable machines. Models specified within this formalism explicitly represent the context-sensitive dynamics of individual proteins driven by external inputs and represent protein-protein interactions as synchronised machine reconfigurations. Both deterministic and stochastic simulations can be applied to quantitatively compute the dynamics of MFA models. They apply the MFA formalism to model and simulate a simple example of a signal-transduction system that involves an MAP kinase cascade and a scaffold protein.
authors.affiliation: Chinese Academy of Sciences, Max Plank Society Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Shanghai, People's Republic of China. jinyang2004@gmail.com
authors.forename: J
authors.initials: J
authors.lastname: Yang
authors.forename: X
authors.initials: X
authors.lastname: Meng
authors.forename: W S
authors.initials: WS
authors.lastname: Hlavacek
mesh_terms: D000465:Algorithms; D019295:Computational Biology / Q000379:methods*; D003198:Computer Simulation; D020935:MAP Kinase Signaling System; D008954:Models, Biological; D008956:Models, Chemical; D008958:Models, Molecular; D009010:Monte Carlo Method; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D013269:Stochastic Processes
chemical_list: D011506:Proteins