Computational Techniques for Analysis of Genetic Network Dynamics

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.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2005
Accession Number
ADA575039

Entities

People

  • Calin Belta
  • Joel M. Esposito
  • Jongwoo Kim
  • Vijay Kumar

Organizations

  • United States Naval Academy

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Chemical Kinetics
  • Chemical Reactions
  • Computational Science
  • Computations
  • Computer Science
  • Differential Equations
  • Dynamics
  • Equations
  • Hybrid Systems
  • Linear Differential Equations
  • Luminescence
  • Motion Planning
  • Production
  • Robotics
  • Simulations
  • United States Naval Academy

Fields of Study

  • Biology
  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Forest Ecology

Technology Areas

  • Biotechnology