Computational Techniques for Analysis of Genetic Network Dynamics
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Copyright Sage Publications. Postprint version. Published in International Journal of Robotics Research, Volume 24, Issue 2-3, February 2005, pages 219-235.
Abstract
In this paper we propose modeling and analysis techniques for genetic networks that provide biologists with insight into the dynamics of such systems. Central to our modeling approach is the framework of hybrid systems and our analysis tools are derived from formal analysis of such systems. Given a set of states characterizing a property of biological interest P, we present the Multi-Affine Rectangular Partition (MARP) algorithm for the construction of a set of infeasible states I that will never reach P and the Rapidly Exploring Random Forest of Trees (RRFT) algorithm for the construction of a set of feasible states F that will reach P. These techniques are scalable to high dimensions and can incorporate uncertainty (partial knowledge of kinetic parameters and state uncertainty). We apply these methods to understand the genetic interactions involved in the phenomenon of luminescence production in the marine bacterium V. fischeri.
Suggested Citation
Calin Belta, Joel M. Esposito, Jongwoo Kim, and R. Vijay Kumar. "Computational Techniques for Analysis of Genetic Network Dynamics" Departmental Papers (MEAM) (2005).
Available at: http://works.bepress.com/vijay_kumar/31
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