A general recurrent neural network approach to model genetic regulatory networks

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

Volumn 7 VOLS, Issue , 2005, Pages 4735-4738

  Hu, Xiao ^a   Maglia, Ann ^b   Wunsch II, Donald C ^a  

^a Architectural and Environmental Engineering   (United States)

^b MISSOURI UNIVERSITY OF SCIENCE AND TECHNOLOGY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ESCHERICHIA COLI; GENES; GENETIC ENGINEERING; MATHEMATICAL MODELS; TIME SERIES ANALYSIS;

COMPLEX INTERACTIONS; DNA REPAIR NETWORK; NEGATIVE REGULATIONS;

NEURAL NETWORKS;

EID: 33846925048     PISSN: 05891019     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (18)

1. B. R. Jasny, L. Roberts, Building on the DNA Revolution. Science 300:277, 2003.
2. L. F. A. Wessels, E. P. Van Someren, M.J.T. Reinders, "A comparison of genetic network models," Pac Symp Biocomput, 508-519, 2001.
3. T. Akutsu, S. Miyano, S. Kuhara, "Identification of genetic networks from a small number of gene expression patterns under the Boolean network model," Pac Symp Biocomput, 17-28, 1999.
4. S. Liang, S. Fuhrman, R. Somogyi, "Reveal, a general reverse engineering algorithm for inference of genetic network architectures," Pac Symp Biocomput, 18-29, 1998.
5. J. L. Michael De Hoon, S. Imota, K. Kobayashi, N. Ogasawara, S. Miyano, "Inferring gene regulatory networks from time-ordered gene expression data of Bacillus subtills using differential equations," Pac Symp Biocomput, 17-28, 2003.
6. T. Chen, H. L. He, G. M. Church, "Modeling gene expression with differential equations," Pac Symp Biocomput, 4:2940, 1999.
7. N. Friedman, M. Linial, T. Nachman, D. Pe'er, "Using Bayesian net work to analyze expression data," J. Comp. Biol., 7, 601-620, 2000.
8. S. Imoto, T. Gota, S. Miyano, "Estimation of genetic networks and functional structures between genes by using Bayesian networks and nonparametric regression," Pac Symp Biocomput, 175-186, 2002.
9. R. Xu, X. Hu, D. Wunsch, "Inference of genetic regulatory networks with recurrent neural network models," Engineering in Medicine and Biology Society, 2004. EMBC 2004. Conference Proceedings. 26th Annual International Conference of the Volume 2, 1-5 Sept. 2004 Page(s):2905-2908 Vol.4.
10. J. F. Kolen, S. C. Kremer, A Field Guide to Dynamic Recurrent Networks, Wiley-IEEE Press, New York, March 2001.
11. F. J. Pineda. Generalization of back-propagation to recurrent neural networks. Physical Review Letters 59, 19, 2229-2232, 1987.
12. B. A. Pearlmutter, "Learning state space trajectories in recurrent neural networks," Neural Computation 1, 2, 263-269, 1989.
13. P. D'haeseleer, Reconstructing gene networks from large scale gene expression data. Ph.D. Thesis, 2000.
14. E. Mjolsness, D. H. Sharp, J. Reinitz, "A Connectionist Model of Development." J. Theoretical Biology 152, 429-453, 1991.
15. Jiří Vohradský, "Neural network model," J Biol Chem 276, 39, 36168-36173, 2001.
16. B. A. Pearlmutter, "Gradient calculations for dynamic recurrent neural networks: a survey," IEEE Transactions on Neural Networks 6(5), 1212-1218, 1995.
17. P. J. Werbos, "Backpropagation through time: what it does and how to do it," Proceedings of IEEE, 78(10), 1550-1560, 1990.
18. M. Ronen, R. Rosenberg, B. I. Shraiman, U. Alon, "Assigning numbers to the arrows: parameterizing a gene regulation network by using accurate expression kinetics," Proc. Natl Acad. Sci. USA, 99, 10555-10560.