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The International Journal of Robotics Research
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Computational Techniques for Analysis of Genetic Network Dynamics

Calin Belta

Drexel University, Philadelphia, PA, USA, calin{at}drexel.edu

Joel M. Esposito

US Naval Academy, Annapolis, MD, USA

Jongwoo Kim

University of Pennsylvania, Philadelphia, PA, USA

Vijay Kumar

University of Pennsylvania, Philadelphia, PA, USA

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.

Key Words: genetic networks • hybrid systems • formal analysis • rapidly-exploring random trees

The International Journal of Robotics Research, Vol. 24, No. 2-3, 219-235 (2005)
DOI: 10.1177/0278364905050359
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J. Kim, J. M. Esposito, and V. Kumar
Sampling-based Algorithm for Testing and Validating Robot Controllers
The International Journal of Robotics Research, December 1, 2006; 25(12): 1257 - 1272.
[Abstract] [PDF]