Browse by author
Lookup NU author(s): Dr Jason Steggles, Dr Oliver Shaw, Professor Anil Wipat
Full text for this publication is not currently held within this repository. Alternative links are provided below where available.
Motivation: New developments in post-genomic technology now provide researchers with the data necessary to study regulatory processes in a holistic fashion at multiple levels of biological organization. One of the major challenges for the biologist is to integrate and interpret these vast data resources to gain a greater understanding of the structure and function of the molecular processes that mediate adaptive and cell cycle driven changes in gene expression. In order to achieve this biologists require new tools and techniques to allow pathway related data to be modelled and analysed as network structures, providing valuable insights which can then be validated and investigated in the laboratory. Results: We propose a new technique for constructing and analysing qualitative models of genetic regulatory networks based on the Petri net formalism. We take as our starting point the Boolean network approach of treating genes as binary switches and develop a new Petri net model which uses logic minimization to automate the construction of compact qualitative models. Our approach addresses the shortcomings of Boolean networks by providing access to the wide range of existing Petri net analysis techniques and by using non-determinism to cope with incomplete and inconsistent data. The ideas we present are illustrated by a case study in which the genetic regulatory network controlling sporulation in the bacterium Bacillus subtilis is modelled and analysed. © 2007 Oxford University Press.
Author(s): Steggles LJ, Banks R, Shaw O, Wipat A
Publication type: Article
Publication status: Published
Journal: Bioinformatics
Year: 2007
Volume: 23
Issue: 3
Pages: 336-343
ISSN (print): 1367-4803
ISSN (electronic): 1367-4811
Publisher: Oxford University Press
URL: http://dx.doi.org/10.1093/bioinformatics/btl596
DOI: 10.1093/bioinformatics/btl596
PubMed id: 17121774
Altmetrics provided by Altmetric
