Approximating Continuous Systems by Timed Automata
FMSB '08 Proceedings of the 1st international workshop on Formal Methods in Systems Biology
CMSB '08 Proceedings of the 6th International Conference on Computational Methods in Systems Biology
Hybrid dynamics of stochastic programs
Theoretical Computer Science
From model-checking to temporal logic constraint solving
CP'09 Proceedings of the 15th international conference on Principles and practice of constraint programming
Multistability of genetic regulatory networks
International Journal of Systems Science - Dynamics Analysis of Gene Regulatory Networks
IEEE Transactions on Fuzzy Systems
Biocircuit design through engineering bacterial logic gates
Natural Computing: an international journal
Theoretical Computer Science
On Parameter Synthesis by Parallel Model Checking
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Multiple verification in complex biological systems: the bone remodelling case study
Transactions on Computational Systems Biology XIV
Synthetic Biology and Microdevices: A Powerful Combination
ACM Journal on Emerging Technologies in Computing Systems (JETC) - Special Issue on Bioinformatics
Analytical Solution of Steady-State Equations for Chemical Reaction Networks with Bilinear Rate Laws
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
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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 Escherichia coli. Availability: RoVerGeNe and the transcriptional cascade model are available at http://iasi.bu.edu/%7Ebatt/rovergene/rovergene.htm Contact: gregory.batt@imag.fr