Now showing items 1-4 of 4

    • Gene selection using iterative feature elimination random forests for survival outcomes. 

      George, Stephen L; Hui, K; Pang, H; Tong, T (IEEE/ACM Trans Comput Biol Bioinform, 2012-09)
      Although many feature selection methods for classification have been developed, there is a need to identify genes in high-dimensional data with censored survival outcomes. Traditional methods for gene selection in classification ...
    • On enrichment strategies for biomarker stratified clinical trials 

      George, Stephen L; Wang, T; Wang, Xiaofei; Zhou, J (Journal of Biopharmaceutical Statistics, 2017-09-07)
      In the era of precision medicine, drugs are increasingly developed to target subgroups of patients with certain biomarkers. In large all-comer trials using a biomarker strati ed design (BSD), the cost of treating and following ...
    • permGPU: Using graphics processing units in RNA microarray association studies. 

      George, Stephen L; Jung, SH; Owzar, Kouros; Shterev, ID (BMC Bioinformatics, 2010-06-16)
      BACKGROUND: Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses ...
    • Robust test method for time-course microarray experiments. 

      George, Stephen L; Jung, SH; Kim, S; Owzar, Kouros; Sohn, I (BMC Bioinformatics, 2010-07-22)
      BACKGROUND: In a time-course microarray experiment, the expression level for each gene is observed across a number of time-points in order to characterize the temporal trajectories of the gene-expression profiles. For many ...