Gene regulatory networks simplified by nonlinear balanced truncation

Anke Meyer-Bäse, Fabian Theis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

Abstract

The complexity of gene regulatory networks described by coupled nonlinear differential equations is often an obstacle for analysis purposes. Therefore, the development of effective model reduction techniques is of paramount importance in the field of systems biology. In this paper, we apply the theory of nonlinear balanced truncation for model reduction for gene regulatory networks based only on standard matrix computations. The method is based on finding a controllability and observability function of the nonlinear system and thus obtain a balanced representation that produces singular value functions which are functions of the state. As a result, we obtain a ranked contribution of the states from an input-output perspective.

Original languageEnglish
Title of host publicationIndependent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI
DOIs
StatePublished - 2008
Externally publishedYes
EventIndependent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI - Orlando, FL, United States
Duration: 17 Mar 200819 Mar 2008

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume6979
ISSN (Print)0277-786X

Conference

ConferenceIndependent Component Analyses, Wavelets, Unsupervised Nano-Biomimetic Sensors, and Neural Networks VI
Country/TerritoryUnited States
CityOrlando, FL
Period17/03/0819/03/08

Keywords

  • Gene regulatory network
  • Hankel operator
  • Nonlinear balanced truncation

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