A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

ABSTRACT: Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single gen

SUBMITTER: Seok J 

PROVIDER: S-EPMC4416884 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature