Stochastic modeling for the expression of a gene regulated by competing transcription factors

Hsih Te Yang, Minoru S.H. Ko

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


It is widely accepted that gene expression regulation is a stochastic event. The common approach for its computer simulation requires detailed information on the interactions of individual molecules, which is often not available for the analyses of biological experiments. As an alternative approach, we employed a more intuitive model to simulate the experimental result, the Markov-chain model, in which a gene is regulated by activators and repressors, which bind the same site in a mutually exclusive manner. Our stochastic simulation in the presence of both activators and repressors predicted a Hill-coefficient of the dose-response curve closer to the experimentally observed value than the calculated value based on the simple additive effects of activators alone and repressors alone. The simulation also reproduced the heterogeneity of gene expression levels among individual cells observed by Fluorescence Activated Cell Sorting analysis. Therefore, our approach may help to apply stochastic simulations to broader experimental data.

Original languageEnglish
Article numbere32376
JournalPloS one
Issue number3
Publication statusPublished - 2012 Mar 14
Externally publishedYes

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General


Dive into the research topics of 'Stochastic modeling for the expression of a gene regulated by competing transcription factors'. Together they form a unique fingerprint.

Cite this