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Bioinformatics Advance Access published online on July 27, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm362
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Robustness Analysis and Tuning of Synthetic Gene Networks

Grégory Batt a, Boyan Yordanov b, Ron Weiss c and Calin Belta a

aCenters for Information and Systems Engineering and for BioDynamics, Boston University, Boston, MA, USA,
bDepartment of Biomedical Engineering, Boston University, Boston, MA, USA,
cDepartments of Electrical Engineering and Molecular Biology, Princeton University, Princeton, NJ, USA

*To whom correspondence should be addressed. Dr. Grégory Batt, E-mail: gregory.batt{at}imag.fr


  Abstract

Motivation: The goal of synthetic biology is to design and construct biological systems that present a desired behavior. The construction of synthetic gene networks implementing simple functions has demonstrated the feasibility of this approach. However, the design of these networks is difficult, notably because existing techniques and tools are not adapted to deal with uncertainties on molecular concentrations and parameter values.

Results: We propose an approach for the analysis of a class of uncertain piecewise-multiaffine differential equation models. This modeling framework is well-adapted to the experimental data currently-available. Moreover, these models present interesting mathematical properties that allow the development of efficient algorithms for solving robustness analyses and tuning problems. These algorithms are implemented in the tool RoVerGeNe, and their practical applicability and biological relevance are demonstrated on the analysis of the tuning of a synthetic transcriptional cascade built in E. coli.

Availability: RoVerGeNe and the transcriptional cascade model are available at http://iasi.bu.edu/%7Ebatt/rovergene/rovergene.htm

Contact: gregory.batt{at}imag.fr

Associate Editor: Dr. Chris Stoeckert

Received on March 17, 2007; revised on June 8, 2007; accepted on July 8, 2007

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