Reconstruction of Gene Regulatory Networks Based on Two-Stage Bayesian Network Structure Learning Algorithm

Journal of Bionic Engineering

Volumn 6, Issue 1, 2009, Pages 86-92

  Liu, Gui xia ^a   Feng, Wei ^a   Wang, Han ^a   Liu, Lei ^a   Zhou, Chun guang ^a  

^a JILIN UNIVERSITY   (China)

Author keywords

Bayesian network; gene regulatory networks; immune evolutionary algorithm; two stage learning algorithm

Indexed keywords

BAYESIAN NETWORK MODELS; BAYESIAN NETWORK STRUCTURES; GENE REGULATORY NETWORKS; IMMUNE EVOLUTION ALGORITHMS; IMMUNE EVOLUTIONARY ALGORITHM; MICROARRAY GENE EXPRESSION DATUM; NETWORK STRUCTURES; POST-GENOMIC BIOLOGIES; REGULATORY RELATIONSHIPS; TWO-STAGE LEARNING ALGORITHM; YEAST CELL CYCLES;

BIOINFORMATICS; BIOLOGICAL SYSTEMS; DISTRIBUTED PARAMETER NETWORKS; EDUCATION; EVOLUTIONARY ALGORITHMS; GENE EXPRESSION; INFERENCE ENGINES; INTELLIGENT NETWORKS; LEARNING ALGORITHMS; LEARNING SYSTEMS; RESTORATION; SPEECH ANALYSIS;

BAYESIAN NETWORKS;

EID: 64049105056     PISSN: 16726529     EISSN: None     Source Type: Journal    
DOI: 10.1016/S1672-6529(08)60103-1     Document Type: Article

References (17)

1. Akutsu T., Miyano S., and Kuhara S. Identification of genetic networks from a small number of gene expression patterns under the Boolean network model. Pacific Symposium on Biocomputing (1999) 17-28
2. Chen K.C., Wang T.Y., Tseng H.H., Huang C., and Kao C.Y. A stochastic differential equation model for quantifying transcriptional regulatory network in Saccharomyces cerevisiae. Bioinformatics 21 (2005) 2883-2890
3. Van Someren E.P., Wessels L.F., and Reinders M.J. Linear modeling of genetic networks from experimental data. Intelligent Systems for Molecular Biology 8 (2000) 355-366
4. Friedman N., Linial M., Nachman I., and Pe'er D. Using Bayesian networks to analyze expression data. Journal of Computational Biology 7 (2000) 601-620
5. Maraziotis I., Dragomir A., and Bezerianos A. Recurrent neuro-fuzzy network models for reverse engineering gene regulatory interactions. Lecture Notes in Computer Science 3695 (2005) 24-34
6. De Jong H. Modeling and simulation of genetic regulatory systems: A literature review. Journal of Computational Biology 9 (2002) 67-103
7. Cheng J, Bell D A, Liu W. An algorithm for Bayesian belief network construction from data. Proceedings of AI&STAT'97, Ft. Lauderdale, Florida, 1997, 83-90.
8. Zhang Q., Xu X., and Liang Y.C. An improved artificial immune algorithm with a dynamic threshold. Journal of Bionic Engineering 3 (2006) 93-97
9. Jiao L.C., and Wang L. A novel genetic algorithm based on immunity. IEEE Transactions on System, Man and Cybernetics, Part A 30 (2000) 552-561
10. Farmer J.D., Packard N.H., and Perelson A.S. The immune system adaptation and machine learning. Physica D 2 (1986) 187-204
11. Barron A., Rissanen J., and Yu B. The minimum description length principle in coding and modeling. IEEE Transactions on Information Theory 44 (1998) 2743-2760
12. Norsys, [2008-06-03]. http://www.norsys.com
13. Banjo, [2008-06-20]. http://www.cs.duke.edu/amink/software/banjo/
14. Yang J.H., Sun L., Lee H.P., Qian Y., and Liang Y.C. Clonal selection based memetic algorithm for job shop scheduling problems. Journal of Bionic Engineering 5 (2008) 111-119
15. Spellman P., Sherlock G., Zhang M., Iyer V., Anders K., Eisen M., Brown P., Botstein D., and Futcher B. Comprehensive identification of cell cycle-regulated genes of the yeast sacccharomyces cerevisiae by microarray hybridization. Molecular Biology of the Cell 9 (1998) 3273-3297
16. Chen J.C., and Yuan B. Detecting functional modules in the yeast protein -protein interaction network. Bioinformatics 22 (2006) 2283-2290
17. Cannon R.L., Dave J.V., and Bezdek J.C. Efficient implementation of the fuzzy C-means clustering algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 8 (1986) 248-255