Modeling of gene regulatory network dynamics using threshold logic

Tejaswi Gowda, Sarma Vrudhula, Seungchan Kim

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Scopus citations

Abstract

Gene regulation modeling is one of the most active research topics in systems biology. The aim of modeling gene regulation is to understand how individual genes function and interact with each other to create complex biological phenomena. In this paper we propose a novel gene regulatory model based on threshold logic. The approach is developed by a combination of threshold logic properties and perceptron learning techniques. This work does not focus on determination of the pair-wise interactions among genes. Instead, the objective of this work is to generate a model that will describe and predict phenomena associated with a biological system. The utility of the approach is demonstrated by modeling a cellular system of 50 genes. The model could effectively replicate both the steady state and the transient behavior of genes.

Original languageEnglish (US)
Title of host publicationThe Challenges of Systems Biology Community Efforts to Harness Biological Complexity
PublisherBlackwell Publishing Inc.
Pages71-81
Number of pages11
ISBN (Print)9781573317511
DOIs
StatePublished - Mar 2009

Publication series

NameAnnals of the New York Academy of Sciences
Volume1158
ISSN (Print)0077-8923
ISSN (Electronic)1749-6632

Keywords

  • Gene regulation networks
  • Modeling of biological systems
  • Threshold logic

ASJC Scopus subject areas

  • Neuroscience(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • History and Philosophy of Science

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