The identification of dynamic gene-protein networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4366 LNBI, Issue , 2007, Pages 157-170

  Westra, Ronald L ^a   Hollanders, Goele ^b   Bex, Geert Jan ^b   Gyssens, Marc ^b   Tuyls, Karl ^a  

^a MAASTRICHT UNIVERSITY   (Netherlands)

^b HASSELT UNIVERSITY   (Belgium)

Author keywords

Gene regulatory networks; Hierarchical networks; Microarrays; Piecewise linear model; Robust identification

Indexed keywords

BIOINFORMATICS; DYNAMICAL SYSTEMS; HIERARCHICAL SYSTEMS; MICROARRAYS; MOLECULAR INTERACTIONS; PROTEINS;

GENE REGULATORY NETWORKS; HIERARCHICAL NETWORKS; PIECEWISE LINEAR MODELS; ROBUST IDENTIFICATION;

GENE EXPRESSION;

EID: 36048997121     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71037-0_11     Document Type: Conference Paper

References (24)

1. Bower J.M., Bolouri H.(Editors), Computational Modeling of Genetic and Biochemical Networks, MIT Press, 2001.
2. de Jong H., Modeling and Simulation of Genetic RegulatorySystems: A Literature Review, Journal of Computational Biology, 2002, Volume 9, Number 1, pp. 67-103
3. de Jong H., Gouze J.L., Hernandez C., Page M., Sari T., Geiselmann J., Qualitative simulation of genetic regulatory networks usingpiecewise-linear models, Bull Math Biol. 2004 Mar;66(2): pp 301-40.
4. Elowitz M.B., Levine A.J., Siggia E.D., Swain P.S., Stochastic gene expression in a single cell, Science, vol.297, August 16, 2002, pp.1183-1186.
5. Endy, D, Brent, R. (2001) Modeling Cellular Behavior, Nature 2001 Jan 18; 409(6818):391-5.
6. Fuchs J.J. (2003), More on sparse representations in arbitrary bases, in: Proc. 13th IFAC Symp. on System Identification, Sysid 2003, Rotterdam, The Netherlands, August 27-29, 2003, pp. 1357-1362.
7. Fuchs J.J. (2004), On sparse representations in arbitrary redundant bases, IEEE Trans. on IT, June 2004.
8. Glass L., Kauffman S.A. (1973), The Logical Analysis of Continuous Non-linear Biochemical Control Networks, J.Theor.Biol., 1973 Vol. 39(1), pp. 103-129
9. Goldbeter A (2002) Computational approaches to cellular rhythms. Nature 420, 238-45
10. Gonze D, Halloy J, and Goldbeter A (2004) Stochastic models for circadian oscillations: Emergence of a biological rhythm. Int J Quantum Chem 98, pp 228-238.
11. Hasty J., McMillen D., Isaacs F., Collins J. J., (2001), Computational studies of gene regulatory networks: in numero molecular biology,Narure Reviews Genetics, vol. 2, no. 4, pp. 268-279, 2001.
12. Novak B, Tyson JJ (1997) Modeling the control of DNA replication in fission yeast, PNAS, USA, Vol. 94, pp. 9147-9152, August 1997.
13. Leiv Øyehaug, Erik Plahte, Stig W. Omholt, Targeted reduction of complex models with time scale hierarchy-a case study, Mathematical Biosciences, 185, 123-152, 2003.
14. Peeters R.L.M., Westra R.L., On the identification of sparse gene regulatory networks, Proc. of the 16th Intern. Symp. on Mathematical Theory of Networks and Systems (MTNS2004) Leuven, Belgium July 5-9, 2004
15. Plahte E, Mestl T, Omholt SW, A methodological basis for description and analysis of systems with complex switch-like interactions, Journal of Mathematical Biology, 36, 321-348, 1998.
16. Rosenfeld N, Young JW, Alon U, Swain PS, Elowitz MB, Gene regulation at the single-cell level, Science 307 (2005) pp 1962.
17. Somogyi R., Fuhrman S., Askenazi M., Wuensche A. (1997). The Gene Expression Matrix: Towards the Extraction of Genetic Network Architectures. Nonlinear Analysis, Proc. of Second World Cong, of Nonlinear Analysis (WCNA96) 30(3) pp 1815-1824.
18. Swain P.S., Efficient attenuation of stochasticity in gene expression through post-transcriptional control, J Mol Biol 344 (2004) pp 965.
19. Swain P.S., Elowitz MB, Siggia ED, Intrinsic and extrinsic contributions to stochasticity in gene expression, PNAS 99 (2002) pp 12795.
20. Steuer R. (2004), Effects of stochasticity in models of the cell cycle:from quantized cycle times to noise-induced oscillations, Journal of Theoretical Biology 228 (2004) 293-301.
21. van Schuppen J.H. (2004), System theory of rational positive systems for cell reaction networks, CWI Report MAS-E0421, December 2004, ISSN 1386-3703
22. Verdult V., Verhaegen M., Subspace Identification of Piecewise Linear Systems, In Proc. 43rd IEEE Conference on Decision and Control (CDC), pp 3838-3843, Atlantis, Paradise Island, Bahamas, December 2004.
23. Westra R.L.,(2005a), Piecewise Linear Dynamic Modeling and Identification of Gene-Protein Interaction Networks, Nisis/JCB Workshop reverse engineering, Jena, June 10, 2005.
24. Yeung M.K.S., Tegnér J., Collins J.J., Reverse engineering gene networks using singular value decomposition and robust regression, Proc. Nat. Acad. Science, vol. 99, no. 9, 2002, pp. 6163-6168.