Literature DB >> 25487098

Chemical master equation closure for computer-aided synthetic biology.

Patrick Smadbeck1, Yiannis N Kaznessis.   

Abstract

With inexpensive DNA synthesis technologies, we can now construct biological systems by quickly piecing together DNA sequences. Synthetic biology is the promising discipline that focuses on the construction of these new biological systems. Synthetic biology is an engineering discipline, and as such, it can benefit from mathematical modeling. This chapter focuses on mathematical models of biological systems. These models take the form of chemical reaction networks. The importance of stochasticity is discussed and methods to simulate stochastic reaction networks are reviewed. A closure scheme solution is also presented for the master equation of chemical reaction networks. The master equation is a complete model of randomly evolving molecular populations. Because of its ambitious character, the master equation remained unsolved for all but the simplest of molecular interaction networks for over 70 years. With the first complete solution of chemical master equations, a wide range of experimental observations of biomolecular interactions may be mathematically conceptualized. We anticipate that models based on the closure scheme described herein may assist in rationally designing synthetic biological systems.

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Year:  2015        PMID: 25487098      PMCID: PMC4820257          DOI: 10.1007/978-1-4939-1878-2_9

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


  28 in total

1.  Construction of a genetic toggle switch in Escherichia coli.

Authors:  T S Gardner; C R Cantor; J J Collins
Journal:  Nature       Date:  2000-01-20       Impact factor: 49.962

2.  Binomial leap methods for simulating stochastic chemical kinetics.

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Journal:  J Chem Phys       Date:  2004-12-01       Impact factor: 3.488

3.  Antimicrobial peptides targeting Gram-negative pathogens, produced and delivered by lactic acid bacteria.

Authors:  Katherine Volzing; Juan Borrero; Michael J Sadowsky; Yiannis N Kaznessis
Journal:  ACS Synth Biol       Date:  2013-07-10       Impact factor: 5.110

4.  Time accelerated Monte Carlo simulations of biological networks using the binomial tau-leap method.

Authors:  Abhijit Chatterjee; Kapil Mayawala; Jeremy S Edwards; Dionisios G Vlachos
Journal:  Bioinformatics       Date:  2005-02-04       Impact factor: 6.937

5.  Nested stochastic simulation algorithm for chemical kinetic systems with disparate rates.

Authors:  Weinan E; Di Liu; Eric Vanden-Eijnden
Journal:  J Chem Phys       Date:  2005-11-15       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.  Moment-closure approximations for mass-action models.

Authors:  C S Gillespie
Journal:  IET Syst Biol       Date:  2009-01       Impact factor: 1.615

8.  proTeOn and proTeOff, new protein devices that inducibly activate bacterial gene expression.

Authors:  Katherine Volzing; Konstantinos Biliouris; Yiannis N Kaznessis
Journal:  ACS Chem Biol       Date:  2011-08-18       Impact factor: 5.100

9.  SynBioSS: the synthetic biology modeling suite.

Authors:  Anthony D Hill; Jonathan R Tomshine; Emma M B Weeding; Vassilios Sotiropoulos; Yiannis N Kaznessis
Journal:  Bioinformatics       Date:  2008-08-30       Impact factor: 6.937

Review 10.  Models for synthetic biology.

Authors:  Yiannis N Kaznessis
Journal:  BMC Syst Biol       Date:  2007-11-06
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