Robust filtering circuit design for stochastic gene networks under intrinsic and extrinsic molecular noises

Bor Sen Chen, Wei-Sheng Wu

Research output: Contribution to journalArticle

25 Citations (Scopus)

Abstract

How to design a robust gene network to tolerate more intrinsic kinetic parameter variations and to attenuate more extrinsic environmental noises to achieve a desired filtering level will be an important topic for systems biology and synthetic biology. At present, there is no good systematic design method to achieve robust gene network design. In this study, a gene network suffering from intrinsic kinetic parameter fluctuations and extrinsic environmental noises is modeled as a Langevin equation with state-dependent stochastic noises. Based on the nonlinear stochastic filtering theory, a systematic gene circuit design method is proposed to make gene networks improve their robustness to tolerate more intrinsic noises and to attenuate extrinsic noises to a prescribed filtering level. The robust gene network design principles have not only yielded a comprehensive design theory of robust gene networks, but also gained valuable insights into the molecular noise filtering of gene networks from the systematic perspective.

Original languageEnglish
Pages (from-to)342-355
Number of pages14
JournalMathematical Biosciences
Volume211
Issue number2
DOIs
Publication statusPublished - 2008 Feb 1

Fingerprint

Robust Filtering
Stochastic Networks
Gene Networks
Circuit Design
Gene Regulatory Networks
Noise
Genes
Networks (circuits)
Filtering
Network Design
Design Method
Kinetic parameters
Kinetics
Synthetic Biology
Noise Filtering
synthetic biology
kinetics
Langevin Equation
Systems Biology
gene regulatory networks

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Medicine(all)
  • Modelling and Simulation
  • Immunology and Microbiology(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

Cite this

@article{88a51cc6b45c4437a360709cdaa769f9,
title = "Robust filtering circuit design for stochastic gene networks under intrinsic and extrinsic molecular noises",
abstract = "How to design a robust gene network to tolerate more intrinsic kinetic parameter variations and to attenuate more extrinsic environmental noises to achieve a desired filtering level will be an important topic for systems biology and synthetic biology. At present, there is no good systematic design method to achieve robust gene network design. In this study, a gene network suffering from intrinsic kinetic parameter fluctuations and extrinsic environmental noises is modeled as a Langevin equation with state-dependent stochastic noises. Based on the nonlinear stochastic filtering theory, a systematic gene circuit design method is proposed to make gene networks improve their robustness to tolerate more intrinsic noises and to attenuate extrinsic noises to a prescribed filtering level. The robust gene network design principles have not only yielded a comprehensive design theory of robust gene networks, but also gained valuable insights into the molecular noise filtering of gene networks from the systematic perspective.",
author = "Chen, {Bor Sen} and Wei-Sheng Wu",
year = "2008",
month = "2",
day = "1",
doi = "10.1016/j.mbs.2007.11.002",
language = "English",
volume = "211",
pages = "342--355",
journal = "Mathematical Biosciences",
issn = "0025-5564",
publisher = "Elsevier Inc.",
number = "2",

}

Robust filtering circuit design for stochastic gene networks under intrinsic and extrinsic molecular noises. / Chen, Bor Sen; Wu, Wei-Sheng.

In: Mathematical Biosciences, Vol. 211, No. 2, 01.02.2008, p. 342-355.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Robust filtering circuit design for stochastic gene networks under intrinsic and extrinsic molecular noises

AU - Chen, Bor Sen

AU - Wu, Wei-Sheng

PY - 2008/2/1

Y1 - 2008/2/1

N2 - How to design a robust gene network to tolerate more intrinsic kinetic parameter variations and to attenuate more extrinsic environmental noises to achieve a desired filtering level will be an important topic for systems biology and synthetic biology. At present, there is no good systematic design method to achieve robust gene network design. In this study, a gene network suffering from intrinsic kinetic parameter fluctuations and extrinsic environmental noises is modeled as a Langevin equation with state-dependent stochastic noises. Based on the nonlinear stochastic filtering theory, a systematic gene circuit design method is proposed to make gene networks improve their robustness to tolerate more intrinsic noises and to attenuate extrinsic noises to a prescribed filtering level. The robust gene network design principles have not only yielded a comprehensive design theory of robust gene networks, but also gained valuable insights into the molecular noise filtering of gene networks from the systematic perspective.

AB - How to design a robust gene network to tolerate more intrinsic kinetic parameter variations and to attenuate more extrinsic environmental noises to achieve a desired filtering level will be an important topic for systems biology and synthetic biology. At present, there is no good systematic design method to achieve robust gene network design. In this study, a gene network suffering from intrinsic kinetic parameter fluctuations and extrinsic environmental noises is modeled as a Langevin equation with state-dependent stochastic noises. Based on the nonlinear stochastic filtering theory, a systematic gene circuit design method is proposed to make gene networks improve their robustness to tolerate more intrinsic noises and to attenuate extrinsic noises to a prescribed filtering level. The robust gene network design principles have not only yielded a comprehensive design theory of robust gene networks, but also gained valuable insights into the molecular noise filtering of gene networks from the systematic perspective.

UR - http://www.scopus.com/inward/record.url?scp=38349082134&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=38349082134&partnerID=8YFLogxK

U2 - 10.1016/j.mbs.2007.11.002

DO - 10.1016/j.mbs.2007.11.002

M3 - Article

C2 - 18191422

AN - SCOPUS:38349082134

VL - 211

SP - 342

EP - 355

JO - Mathematical Biosciences

JF - Mathematical Biosciences

SN - 0025-5564

IS - 2

ER -