URC Fuzzy Modeling and Simulation of Gene Regulation

Abstract

Recent technological advances in high-throughput data collection give biologists the ability to study increasingly complex systems. A new methodology is needed to develop and test biological models based on experimental observations and predict the effect of perturbations of the network (e.g. genetic engineering, pharmaceuticals, gene therapy). Diverse modeling approaches have been proposed, in two general categories: modeling a biological pathway as (a) a logical circuit or (b) a chemical reaction network. Boolean logic models can not represent necessary biological details. Chemical kinetics simulations require large numbers of parameters that are very difficult to accurately measure. Based on the way biologists have traditionally thought about systems, we propose that fuzzy logic is a natural language for modeling biology. The Union Rule Configuration (URC) avoids combinatorial explosion in the fuzzy rule base, allowing complex system models. We demonstrate the fuzzy modeling method on the commonly studied lac operon of E. coli. Our goal is to develop a modeling and simulation approach that can be understood and applied by biologists without the need for experts in other fields or "black-box" software.

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Document Details

Document Type
Technical Report
Publication Date
Oct 25, 2001
Accession Number
ADA411144

Entities

People

  • B. A. Sokhansanj
  • J. P. Fitch

Organizations

  • University of California, Davis

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Biology
  • Biotechnology
  • Cells
  • Chemical Kinetics
  • Chemical Reactions
  • Complex Systems
  • Computer Simulations
  • Control Systems
  • Engineering
  • Enzyme Kinetics
  • Enzymes
  • Fuzzy Logic
  • Fuzzy Sets
  • Gene Therapy
  • Molecular Biology
  • Set Theory
  • Simulations

Readers

  • Computational Modeling and Simulation
  • Criminal Law
  • Neural Network Machine Learning.

Technology Areas

  • Biotechnology