Abstraction methods for analysis of gene regulatory networks

Hiroyuki Kuwahara, Chris J. Myers

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

Abstract

With advances in high throughput methods of data collection for gene regulatory networks, we are now in a position to face the challenge of elucidating how these genes coupled with environmental stimuli orchestrate the regulation of cell-level behaviors. Understanding the behavior of such complex systems is likely impossible to achieve with wet-lab experiments alone due to the amount and complexity of the data being collected. Therefore, it is essential to integrate the experimental work with efficient and ac-curate computational methods for analysis. Unfortunately, such analysis is complicated not only by the sheer size of the models of interest but also by the fact that gene regulatory networks often involve small molecular counts making discrete and stochastic analysis necessary. To address this problem, this chapter presents a model abstraction methodology which systematically performs various model abstractions to reduce the complexity of computational biochemical models resulting in substantial improvements in analysis time with limited loss in accuracy.

Original languageEnglish (US)
Title of host publicationHandbook of Research on Computational Methodologies in Gene Regulatory Networks
PublisherIGI Global
Pages352-385
Number of pages34
ISBN (Print)9781605666853
DOIs
StatePublished - 2009
Externally publishedYes

ASJC Scopus subject areas

  • Health Professions(all)

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