Designing Genetic Regulatory Networks Using Fuzzy Petri Nets Approach

International Journal of Automation and Computing

Volumn 7, Issue 3, 2010, Pages 403-412

  Hamed, Raed I ^a   Ahson, Syed I ^b   Parveen, Rafat ^a  

^a JAMIA MILLIA ISLAMIA CENTRAL UNIVERSITY   (India)

^b PATNA UNIVERSITY   (India)

Author keywords

fuzzy Petri net (FPN); fuzzy reasoning; fuzzy transition; Genetic regulatory networks; modeling

Indexed keywords

FUZZY PETRI NETS; FUZZY REASONING; FUZZY TRANSITION; GENETIC REGULATORY NETWORKS; MODELING;

ALGORITHMS; DESIGN; FUZZY SYSTEMS; GRAPH THEORY; PETRI NETS;

FUZZY LOGIC;

EID: 77955790181     PISSN: 14768186     EISSN: 17518520     Source Type: Journal    
DOI: 10.1007/s11633-010-0521-9     Document Type: Article

References (27)

1. M. L. Garg, S. I. Ahson, P. V. Gupta. A fuzzy Petri net for knowledge representation and reasoning. Information Processing Letters, vol. 39, no. 3, pp. 165-171, 1991.
2. H. H. McAdams, L. Shapiro. Circuit simulation of genetic networks. Science, vol. 269, no. 5224, pp. 650-656, 1995.
3. T. Akutsu, S. Miyano, S. Kuhara. Identification of genetic networks from a small number of gene expression patterns under the Boolean network model. In Proceedings of Pacific Symposium on Biocomputing, World Scientific, Singapore, vol. 4, pp. 17-28, 1999.
4. G. Batt, D. Ropers, H. De Jong, J. Geiselmann, R. Mateescu, M. Page, D. Schneider. Validation of qualitative models of genetic regulatory networks by model checking: Analysis of the nutritional stress response in Escherichia coli. Bioinformatics, vol. 21, no. 1 (Suppl.), pp. 19-28, 2005.
5. R. Hengge-Aronis. The general stress response in Escherichia coli, Bacterial Stress Responses, G. Storz, R. Hengge-Aronis, Eds., ASM Press, pp. 161-177, 2000.
6. D. Ropers, H. De Jong, M. Page, D. Schneider, J. Geiselmann. Qualitative Simulation of the Nutritional Stress Response in Escherichia Coli, Research Report No. 5412, INRIA, France, 2004.
7. I. Nachman, A. Regev, N. Friedman. Inferring quantitative models of regulatory networks from expression data. Bioinformatics, vol. 20, no. 1 (suppl.), pp. 248-256, 2004.
8. M. J. Beal, F. Falciani, Z. Ghahramani, C. Rangel, D. Wild. A Bayesian approach to reconstructing genetic regulatory networks with hidden factors. Bioinformatics, vol. 21, no. 3, pp. 349-356, 2005.
9. J. Vohradsky. Neural networks model of gene expression. The FASEB Journal, vol. 15, no. 3, pp. 846-854, 2001.
10. J. Khan, J. S. Wei, M. Ringnér, L. H. Saal, M. Ladanyi, F. Westermann, F. Berthold, M. Schwab, C. R. Antonescu, C. Peterson, P. S. Meltzer. Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nature Medicine, vol. 7, no. 6, pp. 673-679, 2001.
11. H. Matsuno, A. Doi, M. Nagasaki, S. Miyano. Hybrid Petri net representation of gene regulatory network. In Proceedings of Pacific Symposium on Biocomputing, pp. 341-52, 2000.
12. H. Matsuno, S. Fujita, A. Doi, M. Nagasaki, S. Miyano. Towards biopathway modeling and simulation. In Proceedings of International Conference on Applications and Theory Petri Nets, Lecture Notes in Computer Science, Springer, vol. 2679, pp. 3-22, 2003.
13. S. Fujita, M. Matsui, H. Matsuno, S. Miyano. Modeling and simulation of fission yeast cell cycle on hybrid functional Petri net. IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, vol. 87, no. 8, pp. 2919-2928, 2004.
14. H. Matsuno, S. I. T. Inouye, Y. Okitsu, Y. Fujita, S. Miyano. A new regulatory interactions suggested by simulations for circadian genetic control mechanism in mammals. Journal of Bioinformatics and Computational Biology, vol. 4, no. 1, pp. 139-153, 2006.
15. J. Shen, Y. Wang, Z. Liu. Designing genetic regulatory network with fuzzy logic. Advanced Intelligent Computing Theories and Applications, with Aspects of Artificial Intelligence, Lecture Notes in Computer Science, Springer, vol. 5227, pp. 990-995, 2008.
16. T. Maeshiro, S. I. Nakayama, H. Hemmi, K. Shimohara. An evolutionary system for the prediction of gene regulatory networks in biological cells. In Proceedings of SICE Annual Conference, Takamatsu, Japan, pp. 1577-1581, 2007.
17. H. Ressom, D. Wang, R. S. Varghese, R. Reynolds. Fuzzy logic based gene regulatory network. In Proceedings of IEEE International Conference on Fuzzy Systems, IEEE, Canada, vol. 2, pp. 1210-1215, 2003.
18. B. R. Gaines, M. L. G. Shaw. From fuzzy logic to expert systems. Information Sciences, vol. 36, no. 1-2, pp. 5-16, 1985.
19. S. I. Ahson. Petri net models of fuzzy neural networks. IEEE Transactions on Systems, Man, and Cybernetics, vo1. 25, no. 6, pp. 926-932, 1995.
20. J. L. Peterson. Petri Net Theory and the Modeling of Systems, Englewood Cliffs, NJ, USA: Prentice-Hall, 1981.
21. T. Murata. Petri nets: Properties, analysis and applications. Proceedings of the IEEE, vol. 77, no. 4, pp. 541-580, 1989.
22. S. M. Chen, J. S. Ke, J. F. Chang. Knowledge representation using fuzzy Petri nets. IEEE Transactions on Knowledge Data Engineering, vol. 2, no. 3, pp. 311-319, 1990.
23. J. Yuan, H. Shi, C. Liu, W. Shang. Improved basic inference models of fuzzy Petri nets. In Proceedings of the 7th World Conference on Intelligent Control and Automation, pp. 1488-1493, 2008.
24. C. Hu, P. Li, H. Wang. Improved modeling algorithm of fuzzy Petri net for fuzzy reasoning. In IEEE International Conference on Systems, Man and Cybarnetics, IEEE, Washington D. C., USA, vol. 5, pp. 4992-4997, 2003.
25. M. Gao, M. C. Zhou, X. Huang, Z. Wu. Fuzzy reasoning Petri nets. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, vol. 33, no. 3, pp. 314-324, 2003.
26. J. Sun, S. Y. Qin, Y. H. Song. Fault diagnosis of electric power systems based on fuzzy Petri nets. IEEE Transactions on Power Systems, vol. 19, no. 4, pp. 2053-2059, 2004.
27. J. Ye, J. Li, H. Shi, X. Gu, Z. Zhu. A fuzzy Petri net model towards context-awareness based personalized recommendation. In Proceedings of the 5th International Conference on Fuzzy Systems and Knowledge Discovery, IEEE, vol. 3, pp. 325-330, 2008.