References

1. E. S. Lander,The new genomics: global views of biology, Science 274, 536-539 (1996).

2. K. V. Chin, and A. N. Kong, Application of DNA microarrays in pharmacoge-nomics and toxicogenomics, Pharm Res 19, 1773-1778 (2002).

3. E.S.Lander, Array of hope, Nat Genet Suppl 21,3-4(1999).

4. H. K. Hamadeh et al., An overview of toxicogenomics, Curr Issues Mol Biol 4, 45-56 (2002).

5. R. Ulrich and S. H. Friend,Toxicogenomics and drug discovery: will new technologies help us produce better drugs ? Nat Rev Drug Discov 1, 84-88 (2002).

6. J. F. Waring, J. F. and D. N. Halbert, The promise of toxicogenomics, Curr Opin Mol Ther 4, 229-235 (2002).

7. G. A. Churchill, Fundamentals of experimental design for cDNA microarrays, Nat Genet 32 (Suppl 2), 490-495 (2002).

8. J. Quackenbush, Microarray data normalization and transformation, Nat Genet 32 (Suppl 2), 496-501 (2002).

9. T. R. Hughes et al., Functional discovery via a compendium ofexpression profiles, Cell 102, 109-126 (2000).

10. H. K. Hamadeh et al., Gene expression analysis reveals chemical-specific profiles, Toxicol Sci 67, 219-231 (2002).

11. H. K. Hamadeh et al., Prediction of compound signature using high density gene expression profiling, Toxicol Sci 67, 232-240(2002).

12. K.Johnson and S.Lin, QA/QCasa pressing need for microarray analysis: meeting report from CAMDA'02, BioTechniques 34, S62-S63 (2003).

13. D. V. Nguyen, A. B. Arpat, N. Wang, and R. J. Carroll, DNA microarray experiments: biological and technological aspects, Biometrics, 58, 701-717 (2002).

A. M. Edwards, Unfolding of microarray data, JComput Biol, 8:4, 443-461 (2001).

15. S. Dudoit, J. Fridlyand, and T. Speed, Comparison of discrimination methods for the classification oftumors using gene expression data, J Am Stat Assoc 97, 77-87 (2002).

16. N. Cristianini and J. Shawe-Taylor, An Introduction to Support Vector Machines and other Kernel-based Learning Methods, Cambridge University Press, 2000.

17. S. Ramaswamy, et al., Multiclass cancer diagnosis using tumor gene expression signatures, Proc Natl Acad Sci USA 98, 15149-15154(2001).

18. J. Cox, Sparse linear discriminant analysis for microarray data, in preparation.

19. D. K. Slonim, From patterns to pathways: gene expression data analysis comes of age, Nat Genet 32 (Suppl 2), 502-508 (2002).

20. E. F. Petricoin et al., Medical applications of microarray technologies: a regulatory science perspective, Nat Genet 32 (Suppl 2), 474-479 (2002).

0 0

Post a comment