Literature DB >> 19399430

Rule-based modeling of biochemical systems with BioNetGen.

James R Faeder1, Michael L Blinov, William S Hlavacek.   

Abstract

Rule-based modeling involves the representation of molecules as structured objects and molecular interactions as rules for transforming the attributes of these objects. The approach is notable in that it allows one to systematically incorporate site-specific details about protein-protein interactions into a model for the dynamics of a signal-transduction system, but the method has other applications as well, such as following the fates of individual carbon atoms in metabolic reactions. The consequences of protein-protein interactions are difficult to specify and track with a conventional modeling approach because of the large number of protein phosphoforms and protein complexes that these interactions potentially generate. Here, we focus on how a rule-based model is specified in the BioNetGen language (BNGL) and how a model specification is analyzed using the BioNetGen software tool. We also discuss new developments in rule-based modeling that should enable the construction and analyses of comprehensive models for signal transduction pathways and similarly large-scale models for other biochemical systems.

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Year:  2009        PMID: 19399430     DOI: 10.1007/978-1-59745-525-1_5

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  173 in total

Review 1.  Mathematical simulation of membrane protein clustering for efficient signal transduction.

Authors:  Krishnan Radhakrishnan; Ádám Halász; Meghan M McCabe; Jeremy S Edwards; Bridget S Wilson
Journal:  Ann Biomed Eng       Date:  2012-06-06       Impact factor: 3.934

2.  Leveraging modeling approaches: reaction networks and rules.

Authors:  Michael L Blinov; Ion I Moraru
Journal:  Adv Exp Med Biol       Date:  2012       Impact factor: 2.622

3.  Modeling cellular signaling: taking space into the computation.

Authors:  Michael W Sneddon; Thierry Emonet
Journal:  Nat Methods       Date:  2012-02-28       Impact factor: 28.547

4.  Proteus: a web-based, context-specific modelling tool for molecular networks.

Authors:  Florian Gnad; Javier Estrada; Jeremy Gunawardena
Journal:  Bioinformatics       Date:  2012-03-15       Impact factor: 6.937

Review 5.  Use of virtual cell in studies of cellular dynamics.

Authors:  Boris M Slepchenko; Leslie M Loew
Journal:  Int Rev Cell Mol Biol       Date:  2010       Impact factor: 6.813

Review 6.  Classic and contemporary approaches to modeling biochemical reactions.

Authors:  William W Chen; Mario Niepel; Peter K Sorger
Journal:  Genes Dev       Date:  2010-09-01       Impact factor: 11.361

Review 7.  Using views of Systems Biology Cloud: application for model building.

Authors:  Oliver Ruebenacker; Michael Blinov
Journal:  Theory Biosci       Date:  2010-08-21       Impact factor: 1.919

8.  Efficient modeling, simulation and coarse-graining of biological complexity with NFsim.

Authors:  Michael W Sneddon; James R Faeder; Thierry Emonet
Journal:  Nat Methods       Date:  2010-12-26       Impact factor: 28.547

9.  Timescale analysis of rule-based biochemical reaction networks.

Authors:  David J Klinke; Stacey D Finley
Journal:  Biotechnol Prog       Date:  2011-09-26

10.  Computational analysis of an autophagy/translation switch based on mutual inhibition of MTORC1 and ULK1.

Authors:  Paulina Szymańska; Katie R Martin; Jeffrey P MacKeigan; William S Hlavacek; Tomasz Lipniacki
Journal:  PLoS One       Date:  2015-03-11       Impact factor: 3.240

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