title: Efficient parameter search for qualitative models of regulatory networks using symbolic model checking.
abstract: BACKGROUND
  Investigating the relation between the structure and behavior of complex biological networks often involves posing the question if the hypothesized structure of a regulatory network is consistent with the observed behavior, or if a proposed structure can generate a desired behavior.
  
  
  RESULTS
  The above questions can be cast into a parameter search problem for qualitative models of regulatory networks. We develop a method based on symbolic model checking that avoids enumerating all possible parametrizations, and show that this method performs well on real biological problems, using the IRMA synthetic network and benchmark datasets. We test the consistency between IRMA and time-series expression profiles, and search for parameter modifications that would make the external control of the system behavior more robust.
  
  
  BACKGROUND
  GNA and the IRMA model are available at http://ibis.inrialpes.fr/.
authors.affiliation: INRIA Paris-Rocquencourt, Le Chesnay, France. gregory.batt@inria.fr
authors.forename: Gregory
authors.initials: G
authors.lastname: Batt
authors.forename: Michel
authors.initials: M
authors.lastname: Page
authors.forename: Irene
authors.initials: I
authors.lastname: Cantone
authors.forename: Gregor
authors.initials: G
authors.lastname: Goessler
authors.forename: Pedro
authors.initials: P
authors.lastname: Monteiro
authors.forename: Hidde
authors.initials: H
authors.lastname: de Jong
mesh_terms: D019985:Benchmarking; D003198:Computer Simulation; D001330:Electronic Data Processing; D015966:Gene Expression Regulation, Fungal; D053263:Gene Regulatory Networks; D008957:Models, Genetic; D012984:Software; D013561:Symbolism; D049490:Systems Biology; D015003:Yeasts / Q000235:genetics
references.citation: J Theor Biol. 2004 Aug 7;229(3):339-47
references.pmid: 15234201
references.citation: J Math Biol. 2009 Sep;59(3):315-58
references.pmid: 18987858
references.citation: Nat Biotechnol. 2007 Nov;25(11):1239-49
references.pmid: 17989686
references.citation: Science. 2008 Jul 4;321(5885):126-9
references.pmid: 18599789
references.citation: J Theor Biol. 2008 Dec 7;255(3):269-77
references.pmid: 18692073
references.citation: Bioinformatics. 2007 Apr 1;23(7):866-74
references.pmid: 17267426
references.citation: J Theor Biol. 2004 Oct 7;230(3):289-99
references.pmid: 15302539
references.citation: Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:4595-8
references.pmid: 18003029
references.citation: Bioinformatics. 2006 Jul 15;22(14):e124-31
references.pmid: 16873462
references.citation: J Theor Biol. 2009 Dec 21;261(4):511-30
references.pmid: 19665034
references.citation: Cell. 2009 Apr 3;137(1):172-81
references.pmid: 19327819
references.citation: Bioinformatics. 2005 Jun;21 Suppl 1:i19-28
references.pmid: 15961457
references.citation: J Theor Biol. 1973 Apr;39(1):103-29
references.pmid: 4741704
references.citation: Bioinformatics. 2008 Aug 15;24(16):i227-33
references.pmid: 18689830
references.citation: Mol Syst Biol. 2009;5:331
references.pmid: 19953085
references.citation: Biosystems. 2009 Nov;98(2):91-104
references.pmid: 19664681