Synchronous versus asynchronous modeling of gene regulatory networks

Bioinformatics

Volumn 24, Issue 17, 2008, Pages 1917-1925

  Garg, Abhishek ^a   Di Cara, Alessandro ^b   Xenarios, Ioannis ^c   Mendoza, Luis ^d   De Micheli, Giovanni ^a  

^a EPFL   (Switzerland)

^b MERCK SERONO S A   (Switzerland)

^c SWISS INSTITUTE OF BIOINFORMATICS   (Switzerland)

^d UNIVERSIDAD NACIONAL AUTÓNOMA DE MÉXICO   (Mexico)

Author keywords

[No Author keywords available]

Indexed keywords

ANIMAL CELL; ARTICLE; CELL DIFFERENTIATION; COMPUTER MODEL; COMPUTER PROGRAM; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; GENE REGULATORY NETWORK; GENETIC ALGORITHM; GENETIC IDENTIFICATION; HUMAN; HUMAN CELL; INTERMETHOD COMPARISON; MOLECULAR DYNAMICS; NONHUMAN; PRIORITY JOURNAL; SYSTEMS BIOLOGY; TH1 CELL; TH2 CELL;

EID: 50549088838     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btn336     Document Type: Article

References (23)

1. Albert,R. and Othmer, H.G. (2003) The topology of the regulatory interactions predicts the expression pattern of the Drosophila segment polarity genes. J. Theor. Biol., 223, 1-18.
2. Agnello,D. et al. (2003) Cytokines and transcription factors that regulate T helper cell differentiation: New players and new insights. J. Clin. Immunol., 23, 147-162.
3. Baldamus,M. and Schneider,K. (2001) Tbe BDD Space Complexity of Different Forms of Concurrency. In Proceedings of ICACSD '01. Newcastle upon Tyne, UK, pp. 231-242.
4. Bergmann,C. and van Hemmen,J.L. (2001) Th1 or Th2: How an appropriate T helper response can be made. Bull. Math. Biol., 63, 405-430.
5. Bernot,G. et al. (2004) Application of formal methods to biological regulatory networks: Extending Thomas' asynchronous logical approach with temporal logic. J. Theor. Biol., 229, 339-347.
6. Bryant,R.E. (1986) Graph-based algorithms for Boolean function manipulation. IEEE Trans. Comput., 35, 677-691.
7. Burch,J.R. et al. (1991) Symbolic model checking with partitioned transition relations. In Proceedings of International Conference on VLSI'91. Edinburgh, Scotland, pp. 49-58.
8. Burch,J.R. et al. (1994) Symbolic model checking for sequential circuit verification. IEEE Comput-Aid D, 13.
9. Chabrier,N. et al. (2004) BIOCHAM. In Proceeding of Computational Method of Systems Biology. Paris, France, pp. 172-191.
10. Devloo,V. et al. (2003) Identification of all steady states in large biological systems by logical analysis. Bull. Math. Biol., 65, 1025-1051.
11. Di Cara, et al. (2007) Dynamic simulation of regulatory networks using SQUAD. BMC Bioinformatics, 8, 462.
12. Fauré,A. et al. (2006) Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle. Bioinformatics, 22, e124-e131.
13. Garg,A. et al. (2007) An efficient method for dynamic analysis of gene regulatory networks. Springer LNBI, 4453, 62-76.
14. Kauffman,S.A. (1969) Metabolic stability and epigenesis in randomly constructed genetic nets. J. Theor. Biol., 22, 437-467.
15. Klamt,S. et al. (2006) A methodology for the structural and functional analysis of signaling and regulatory networks. BMC Bioinformatics, 7, 56.
16. Murphy,K.M. and Reiner,S.L. (2002) The lineage decisions on helper T cells. Nat. Rev. Immunol., 2, 933-944.
17. Mendoza,L. and Xenarios,I. (2006) A method for the generation of standardized qualitative dynamical systems of regulatory networks. Theor. Biol. Med. Model., 3, 13.
18. Mendoza,L. (2006) A network model for the control of the differentiation process in Th cells. BioSystems, 84, 101-114.
19. Naldi,A. et al. (2007) Decision diagrams for the representation and analysis of logical models of genetic networks. LNCS/LNBI, 4695, 233-247.
20. Remy,E. et al. (2006) From logical regulatory graphs to standard petri nets: Dynamical roles and functionality of feedback circuits. Springer LNCS, 4230, 56-72.
21. Thomas,R. (1991) Regulatory networks seen as asynchronous automata: A logical description. J. Theor. Biol., 153, 1-23.
22. Thomas,R. and Kaufman,M. (1995) Dynamical behaviour of biological regulatory networks-I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state. Bull. Math. Biol., 57, 247-276.
23. Xie,A. and Beerel,P.A. (1998) Efficient state classification of Finite State Markov Chains. In Proceedings of DAC. San Francisco, CA, USA, pp. 605-610.