Network and data integration for biomarker signature discovery via network smoothed T-statistics.

ABSTRACT: Predictive, stable and interpretable gene signatures are generally seen as an important step towards a better personalized medicine. During the last decade various methods have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinics is the typical low reproducibility of signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. We here propose a technique that integrates network information as well as different kinds of experimental data (here exemplified by mRNA and miRNA expression) into one classifier. This is done by smoothing t-statistics of indi

SUBMITTER: Cun Y 

PROVIDER: S-EPMC3760887 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature