Target Discovery and Validation Reviews and Protocols

54 Imoto et al.
5. De Hoon, M. J. L., Imoto, S., Kobayashi, K., Ogasawara, N., and Miyano, S.
(2003) Inferring gene regulatory networks from time-ordered gene expression data
of Bacillus subtilis using differential equations. Pac. Symp. Biocomput. 8, 17–28.
6. Friedman, N., Linial, M., Nachman, I., and Pe’er, D. (2000) Using Bayesian
network to analyze expression data. J. Comp. Biol. 7, 601–620.
7. Hartemink, A. J., Gifford, D. K., Jaakkola, T. S., and Young, R. A. (2001) Using
graphical models and genomic expression data to statistically validate models of
genetic regulatory networks. Pac. Symp. Biocomput. 6, 422–433.
8. Pe’er, D., Regev, A., Elidan, G., and Friedman, N. (2001) Inferring subnetworks
from perturbed expression profiles. Bioinformatics 17 (Suppl. 1), S215–S224.
9. Imoto, S., Goto, T., and Miyano, S. (2002) Estimation of genetic networks and
functional structures between genes by using Bayesian networks and nonparametric
regression. Pac. Symp. Biocomput. 7, 175–186.
10. Imoto, S., Kim, S., Goto, T., et al. (2003) Bayesian network and nonparametric
heteroscedastic regression for non-linear modeling of genetic network. J.
Bioinform. Comp. Biol. 1, 231–252.
11. Imoto, S., Savoie, C. J., Aburatani, S., et al. (2003) Use of gene networks for identifying
and validating drug targets. J. Bioinform. Comput. Biol. 1, 459–474.
12. Savoie, C. J., Aburatani, S., Watanabe, S., et al. (2003) Use of gene networks from
full genome microarray libraries to identify functionally relevant drug-affected
genes and gene regulation cascades. DNA Res. 10, 19–25.
13. Tamada, Y., Imoto, S., Tashiro, K., Kuhara, S., and Miyano, S. (2005) Identifying
drug active pathways from gene networks estimated by gene expression data.
Genome Inform Ser Workshop Genome Inform 16, 182–191.
14. Aburatani, S., Tashiro, K., Savoie, C. J., et al. (2003) Discovery of novel transcription
control relationships with gene regulatory networks generated from multiple-disruption
full genome expression libraries. DNA Res. 10, 1–8.
15. Quackenbush, J. (2002) Microarray data normalization and transformation. Nat.
Genet. 32 (Suppl.), 496–501.
16. Maki, Y., Tominaga, D., Okamoto, M., Watanabe, S., and Eguchi, Y. (2001)
Development of a system for the inference of large scale genetic networks. Pac.
Symp. Biocomput. 6, 446–458.
17. Konishi, S. (1999) Statistical model evaluation and information criteria, in
Multivariate Analysis, Design of Experiments and Survey Sampling (Ghosh, S.,
ed.), Marcel Dekker, New York, pp. 369–399.
18. Cooper, G. and Herskovits, E. (1992) A Bayesian method for the induction of
probabilistic networks from data. Mach. Learn. 9, 309–347.
19. Hastie, T. and Tibshirani, R. J. (1990) Generalized Additive Models. Chapman &
Hall, London.
20. De Boor, C. (1978) A Practical Guide to Splines. Springer-Verlag, Berlin.
21. Imoto, S. and Konishi, S. (2003) Selection of smoothing parameters in B-spline
nonparametric regression models using information criteria. Ann. Inst. Stat. Math.
55, 671–687.
22. Davison, A. C. (1986) Approximate predictive likelihood. Biometrika 73, 323–332.