Comprehensive evaluation of composite gene features in cancer outcome prediction.

ABSTRACT: Owing to the heterogeneous and continuously evolving nature of cancers, classifiers based on the expression of individual genes usually do not result in robust prediction of cancer outcome. As an alternative, composite gene features that combine functionally related genes have been proposed. It is expected that such features can be more robust and reproducible since they can capture the alterations in relevant biological processes as a whole and may be less sensitive to fluctuations in the expression of individual genes. Various algorithms have been developed for the identification of composite features and inference of composite gene feature activity, which all claim to improve the prediction accuracy. However, because of the limitations of test datasets incorporated by each individual st

SUBMITTER: Hou D 

PROVIDER: S-EPMC4345828 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature