GediNET for discovering gene associations across diseases using knowledge based machine learning approach.

ABSTRACT: The most common approaches to discovering genes associated with specific diseases are based on machine learning and use a variety of feature selection techniques to identify significant genes that can serve as biomarkers for a given disease. More recently, the integration in this process of prior knowledge-based approaches has shown significant promise in the discovery of new biomarkers with potential translational applications. In this study, we developed a novel approach, GediNET, that integrates prior biological knowledge to gene Groups that are shown to be associated with a specific disease such as a cancer. The novelty of GediNET is that it then also allows the discovery of significant associations between that specific disease and other diseases. The initial step in this process invo

SUBMITTER: Qumsiyeh E 

PROVIDER: S-EPMC9675776 | biostudies-literature | 2022 Nov

REPOSITORIES: biostudies-literature