Stepwise group sparse regression (SGSR): Gene-set-based pharmacogenomic predictive models with stepwise selection of functional priors

Pacific Symposium on Biocomputing

Volumn , Issue , 2015, Pages 32-43

  Jang, In Sock ^a   Dienstmann, Rodrigo ^a   Margolin, Adam A ^b   Guinney, Justin ^a  

^a SAGE BIONETWORKS   (United States)

^b OREGON HEALTH AND SCIENCE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOINFORMATICS; CELL CULTURE; GENES; LINEAR REGRESSION; PATIENT TREATMENT;

DOMAIN-SPECIFIC KNOWLEDGE; IMPROVED PREDICTABILITY; INTERPRETABILITY AND ACCURACY; LINEAR REGRESSION MODELS; PREDICTIVE PERFORMANCE; REGULARIZATION METHODS; STATE-OF-THE-ART METHODS; STATISTICAL LEARNING;

DISEASES;

ALGORITHM; BIOLOGICAL MODEL; BIOLOGY; DRUG SCREENING; GENETIC DATABASE; GENETICS; HUMAN; NEOPLASMS; PHARMACOGENETICS; STATISTICAL MODEL; STATISTICS AND NUMERICAL DATA; TUMOR CELL LINE;

ALGORITHMS; CELL LINE, TUMOR; COMPUTATIONAL BIOLOGY; DATABASES, GENETIC; DRUG SCREENING ASSAYS, ANTITUMOR; HUMANS; LINEAR MODELS; MODELS, GENETIC; NEOPLASMS; PHARMACOGENETICS;

EID: 84971350079     PISSN: 23356928     EISSN: 23356936     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (39)

1. Ferte, C., F. Andre, and J.C. Soria, Nat Rev Clin Oncol, 7(7)(2010).
2. Peggs, K. and S. Mackinnon, N Engl J Med, 348(11) (2003).
3. Roche-Lestienne, C., et al., N Engl J Med, 348(22) (2003).
4. Savage, D.G. and K.H. Antman, N Engl J Med, 2002. 346(9) (2002).
5. Barretina, J., et al., Nature, 483(7391) (2012).
6. Marum, L., Future Med Chem, 4(8) (2012).
7. Garnett, M.J., et al., Nature, 483(7391) (2012).
8. Yang, W., et al., Nucleic Acids Res, 41(Database issue) (2013).
9. Forbes, S.A., et al., Nucleic Acids Res, 39(Database issue) (2011).
10. Kanehisa, M., et al., Nucleic Acids Res, 40(Database issue) (2012).
11. Cerami, E.G., et al., Nucleic Acids Res, 39(Database issue) (2011).
12. Draghici, S., et al., Genome Res, 17(10) (2007).
13. Jang, I.S., et al., Pac Symp Biocomput, (2014).
14. Neto, E.C., et al., Pac Symp Biocomput, (2014).
15. Chen, L., et al., BMC Syst Biol, 5 (2011).
16. Li, C. and H. Li, Bioinformatics, 24(9) (2008).
17. Tai, F. and W. Pan, Bioinformatics, 23(23) (2007).
18. Tai, F. and W. Pan, 23(14) (2007).
19. Wang, Z., et al., Bioinformatics, 29(20) (2013).
20. Wei, P. and W. Pan, Bioinformatics, 24(3) (2008).
21. Jang, I.S., A. Margolin, and A. Califano, Interface Focus, 3(4) (2013).
22. Li, X., et al., Proteomics, 11(19) (2011).
23. Wei, Z. and H. Li, Bioinformatics, 23(12) (2007).
24. Yuan, M., et al. Journal of the Royal Statistical Society Series B-Statistical Methodology, 68 (2006)
25. Friedman, J., et al. arXiv:1001.0736 (2010).
26. Jacob, L., et al. In Proceedings of the 26th Annual International Conference on Machine Learning (2009)
27. Sales, G., et al., Bmc Bioinformatics, 13 (2012).
28. Liberzon, A., et al., Bioinformatics, 27(12) (2011).
29. Hoerl, A.E., R.W. Kennard, and R.W. Hoerl, Applied Statistics-Journal of the Royal Statistical Society Series C, 34(2) (1985).
30. Tibshirani, R., Journal of the Royal Statistical Society Series B-Methodological, 58(1) (1996).
31. Tibshirani, R., Journal of the Royal Statistical Society Series B-Statistical Methodology, 73 (2011).
32. Zou, H. and T. Hastie, Journal of the Royal Statistical Society Series B-Statistical Methodology, 67 (2005).
33. Fu, W.J.J., Journal of Computational and Graphical Statistics, 7(3) (1998).
34. Vilal, E., et al. Cancer Cell, 4(1) (2003).
35. Bonet, C., et al. J Biol Chem, 287(35) (2012).
36. Kim, L.C., et al. Nat Rev Clin Oncol, 6(10) (2009).
37. Yadav, V., et al. Mol Carcinog, 50(5) (2011).
38. Sun, J.C,. et al. World J Gastroenterol, 16(36) (2010).
39. Damhofer, H., et al. Mol Oncol, 7(6) (2013).