Regularized Classification and Survival Analysis for Expression Profiling of Cancer

• Acknowledgements: This study has been supported by RO1 CA120988 from NCI, NIH (P.I.: Dr. Jian Huang, Department of Statistics and Actuarial Science, University of Iowa). We would like to thank members of Yale Cancer Center and University of Iowa Holden Comprehensive Cancer Center for insightful discussions.
  
  
• Study Period: 01/01/2008 -- 12/31/2011
  
  
• Goal: The objectives of this project are to develop novel statistical methods and computer packages for cancer classification and survival analysis using high-dimensional gene expression data and clinical measurements. The development of the proposed statistical methods that can deal with high-dimensional problems in estimating the relationship between cancer clinical outcomes and genomic data will contribute to better understanding of the genetic basis of cancer, better diagnoses, and better survival prediction, which in turn, can potentially have important impact on public health.
  
  
• Please email shuangge.ma AT yale.edu OR jian AT divms.uiowa.edu for a list of publications generated in this study.