DocumentCode
1845912
Title
Analysing Gene Regulatory Networks by both Constraint Programming and Model-Checking
Author
Fromentin, J. ; Comet, J.-P. ; Le Gall, P. ; Roux, O.
fYear
2007
fDate
22-26 Aug. 2007
Firstpage
4595
Lastpage
4598
Abstract
In this article, we propose a formal method to analyse gene regulatory networks (GRN). The dynamics of such systems is often described by an ordinary differential equation system, but has also been abstracted into a discrete transition system. This modeling depends on parameters for which different values are possible. Each instantiation of these parameters defines a possible dynamics and verification tools can be used to select the tuples of values which lead to dynamics consistent with known behaviours. GRN are so complex that their discrete modeling gives a number of possible dynamics exponential in function of the GRN´s size (number of genes and interactions). In this paper, we propose to use constraint programming and CTL formal language to determine the set of all dynamics consistent with the known behavioral properties without enumerating all of them. This approach allows us therefore to minimize the computation time necessary for the research of these parameters.
Keywords
biology computing; constraint handling; formal specification; genetics; CTL formal language; constraint programming; discrete transition system; formal method; gene regulatory networks; model checking; ordinary differential equation; Biological system modeling; Biology computing; Cost accounting; Differential equations; Dynamic programming; Formal languages; Genetics; Logic programming; Piecewise linear techniques; Proteins; Animals; Gene Expression Regulation; Humans; Models, Genetic; Programming Languages; Software;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location
Lyon
ISSN
1557-170X
Print_ISBN
978-1-4244-0787-3
Type
conf
DOI
10.1109/IEMBS.2007.4353363
Filename
4353363
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