Literature DB >> 23083149

Specification, construction, and exact reduction of state transition system models of biochemical processes.

Scott M Bugenhagen1, Daniel A Beard.   

Abstract

Biochemical reaction systems may be viewed as discrete event processes characterized by a number of states and state transitions. These systems may be modeled as state transition systems with transitions representing individual reaction events. Since they often involve a large number of interactions, it can be difficult to construct such a model for a system, and since the resulting state-level model can involve a huge number of states, model analysis can be difficult or impossible. Here, we describe methods for the high-level specification of a system using hypergraphs, for the automated generation of a state-level model from a high-level model, and for the exact reduction of a state-level model using information from the high-level model. Exact reduction is achieved through the automated application to the high-level model of the symmetry reduction technique and reduction by decomposition by independent subsystems, allowing potentially significant reductions without the need to generate a full model. The application of the method to biochemical reaction systems is illustrated by models describing a hypothetical ion-channel at several levels of complexity. The method allows for the reduction of the otherwise intractable example models to a manageable size.

Mesh:

Substances:

Year:  2012        PMID: 23083149      PMCID: PMC3487925          DOI: 10.1063/1.4758074

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  11 in total

1.  STOCHSIM: modelling of stochastic biomolecular processes.

Authors:  N Le Novère; T S Shimizu
Journal:  Bioinformatics       Date:  2001-06       Impact factor: 6.937

2.  BioNetGen: software for rule-based modeling of signal transduction based on the interactions of molecular domains.

Authors:  Michael L Blinov; James R Faeder; Byron Goldstein; William S Hlavacek
Journal:  Bioinformatics       Date:  2004-06-24       Impact factor: 6.937

3.  Automatic generation of cellular reaction networks with Moleculizer 1.0.

Authors:  Larry Lok; Roger Brent
Journal:  Nat Biotechnol       Date:  2005-01       Impact factor: 54.908

4.  A stochastic automata network descriptor for Markov chain models of instantaneously coupled intracellular Ca2+ channels.

Authors:  Vien Nguyen; Roy Mathias; Gregory D Smith
Journal:  Bull Math Biol       Date:  2005-05       Impact factor: 1.758

5.  Reduction and solution of the chemical master equation using time scale separation and finite state projection.

Authors:  Slaven Peles; Brian Munsky; Mustafa Khammash
Journal:  J Chem Phys       Date:  2006-11-28       Impact factor: 3.488

6.  The finite state projection algorithm for the solution of the chemical master equation.

Authors:  Brian Munsky; Mustafa Khammash
Journal:  J Chem Phys       Date:  2006-01-28       Impact factor: 3.488

7.  Internal coarse-graining of molecular systems.

Authors:  Jérôme Feret; Vincent Danos; Jean Krivine; Russ Harmer; Walter Fontana
Journal:  Proc Natl Acad Sci U S A       Date:  2009-04-03       Impact factor: 11.205

8.  Enhanced identification and exploitation of time scales for model reduction in stochastic chemical kinetics.

Authors:  Carlos A Gómez-Uribe; George C Verghese; Abraham R Tzafriri
Journal:  J Chem Phys       Date:  2008-12-28       Impact factor: 3.488

9.  Invariant manifold reductions for Markovian ion channel dynamics.

Authors:  James P Keener
Journal:  J Math Biol       Date:  2008-07-01       Impact factor: 2.259

10.  Quantitative modeling of stochastic systems in molecular biology by using stochastic Petri nets.

Authors:  P J Goss; J Peccoud
Journal:  Proc Natl Acad Sci U S A       Date:  1998-06-09       Impact factor: 11.205

View more
  2 in total

Review 1.  Modeling for (physical) biologists: an introduction to the rule-based approach.

Authors:  Lily A Chylek; Leonard A Harris; James R Faeder; William S Hlavacek
Journal:  Phys Biol       Date:  2015-07-16       Impact factor: 2.583

Review 2.  Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Authors:  Lily A Chylek; Leonard A Harris; Chang-Shung Tung; James R Faeder; Carlos F Lopez; William S Hlavacek
Journal:  Wiley Interdiscip Rev Syst Biol Med       Date:  2013-09-30
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.