A workflow to study mechanistic indicators for driver gene prediction with Moonlight.

ABSTRACT: Prediction of driver genes (tumor suppressors and oncogenes) is an essential step in understanding cancer development and discovering potential novel treatments. We recently proposed Moonlight as a bioinformatics framework to predict driver genes and analyze them in a system-biology-oriented manner based on -omics integration. Moonlight uses gene expression as a primary data source and combines it with patterns related to cancer hallmarks and regulatory networks to identify oncogenic mediators. Once the oncogenic mediators are identified, it is important to include extra levels of evidence, called mechanistic indicators, to identify driver genes and to link the observed gene expression changes to the underlying alteration that promotes them. Such a mechanistic indicator could be for exampl

SUBMITTER: Nourbakhsh M 

PROVIDER: S-EPMC10516357 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature