Validation of gene regulatory networks from protein-protein interaction data: Application to cell-cycle regulation

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

Volumn 4774 LNBI, Issue , 2007, Pages 300-310

  Chaturvedi, Iti ^a,b   Sakharkar, Meena Kishore ^b   Rajapakse, Jagath C ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Dynamic bayesian networks; Gene regulatory networks; Genetic algorithms; Protein protein interactions

Indexed keywords

BAYESIAN NETWORKS; DATA ACQUISITION; GENE ENCODING; GENE EXPRESSION; GENETIC ALGORITHMS;

DYNAMIC BAYESIAN NETWORKS; GENE REGULATORY NETWORKS; PROTEIN-PROTEIN INTERACTIONS;

PROTEINS;

EID: 38349066315     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75286-8_29     Document Type: Conference Paper

References (24)

1. Nikolsky, Y.: Biological networks and analysis of experimental data in drug discovery. Drug discovery today 10(9), 653 (2005)
2. Wyrick, J.J., Young, R.A.: Deciphering gene expression regulatory networks. Curr. Opin. Genet. Dev. 12(2), 130-136 (2002)
3. Fromont-Racine, M., Rain, J.C., Legrain, P.: Toward a functional analysis of the yeast genome through exhaustive two-hybrid screens. Nature Genetics 16, 277-282 (1997)
4. Duda, R.O.: Pattern classification [Book]
5. Friedman, N., Linial, M., Nachman, I., Pe'er, D.: Using bayesian networks to analyze expression data. J. Computational Biology 7(3), 601-620 (2000) 6. Lauritzen, S.: Graphical Models. Oxford University Press, Oxford (1996)
6. Luo, F., Tang, K., Khan, L.: Hierarchical clustering of gene expression data. Bioinformatics and Bioengineering, 2003. In: Proceedings. Third IEEE Symposium, 10-12 March, pp. 328-335 (2003)
7. Wei, W., Xin, L., Min, X., Jinrong, P., Setiono, R.: A hybrid SOM-SVM method for analyzing zebra fish gene expression. Pattern Recognition, 2004. In: ICPR 2004. Proceedings of the 17th International Conference, vol. 2, pp. 323-326 (2004)
8. Alter, O., Brown, P.O., Botstein, D.: Singular value decomposition for genome-wide expression data processing and modeling. Proc. Natl. Acad. Sci. USA 97, 10101-10106 (2000)
9. Lee, S., Batzoglou, S.: Application of Independent component analysis to microarrays. Genome Biology 4, R76 (2003)
10. Bar-Joseph, Z.: Analyzing Time Series Gene Expression Data. Bioinformatics 20(16), 2493-2503 (2004)
11. Fang-Xiang, et al.: A Genetic Algorithm for Inferring Time Delays in Gene Regulatory Networks, CSB (2004)
12. Wu, C.C., Huang, H., Juan, H., Chen, S.: Gene Networks: an interactive tool for reconstruction of genetic networks from microarray data. Bioinformatics advanced access (2004)
13. Liang, S., Fuhrman, S., Somogyi, R.: REVEAL: a general reverse engineering algorithm for inference of genetic network architectures. In: Pacific Symposium on Biocomputing, vol. 3, pp. 18-29 (1998)
14. Friedmann, N., Linial, M., Nachman, I., Pe'er, D.: Using Bayesian Networks to Analyze expression data. Journal of Computational Biology 7, 601-620 (2000)
15. Heckerman, D., Geiger, D., Chickering, D.M.: Learning Bayesian networks: The combination of knowledge and statistical data. Machine Learning 9, 309-347 (1999)
16. Friedman, N., Murphy, K., Russell, S.: Learning the structure of dynamic probabilistic networks. In: Proc. Fourteenth Conference on Uncertainty in Artificial Intelligence (UAI '98), pp. 139-147 (1998)
17. Troyanskaya, O., et al.: Missing value estimation methods for DNA microarray. Bioinformatics 17(6), 520-525 (2001)
18. Davierwala, A.P., et al.: Synthetic genetic interaction spectrum of essential genes. Nature Genetics 37(10), 1147-1152 (2005)
19. Krogan, N.J., et al.: High-definition macromolecular composition of yeast RNAprocessing complexes. Mol. Cell 13(2), 225-239 (2004)
20. Young, K.H.: Yeast Two-Hybrid: So Many Interactions (in) So Little Time. Biology of reproduction 58, 302-311 (1998)
21. Page, D., Ong, I.M.: Experimental design of time series data for learning from dynamic Bayesian networks. PSB 11, 267-278 (2006)
22. Bahler, J.: Cell-Cycle Control of Gene Expression in Budding and Fission Yeast. Annu. Rev. Genet. 39, 69-94 (2005)
23. Spellman, et al.: Comprehensive Identification of Cell Cycle-regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization. Molecular Biology of the Cell 9, 3273-3297 (1998)
24. Stark, C., Breitkreutz, B.J., Reguly, T., Boucher, L., Breitkreutz, A., Tyers, M.: BioGRID: a general repository for interaction datasets. Nucleic Acids Res. 34, D535-D539 (2006)