BioM2: biologically informed multi-stage machine learning for phenotype prediction using omics data.

ABSTRACT: Navigating the complex landscape of high-dimensional omics data with machine learning models presents a significant challenge. The integration of biological domain knowledge into these models has shown promise in creating more meaningful stratifications of predictor variables, leading to algorithms that are both more accurate and generalizable. However, the wider availability of machine learning tools capable of incorporating such biological knowledge remains limited. Addressing this gap, we introduce BioM2, a novel R package designed for biologically informed multistage machine learning. BioM2 uniquely leverages biological information to effectively stratify and aggregate high-dimensional biological data in the context of machine learning. Demonstrating its utility with genome-wide DNA me

SUBMITTER: Zhang S 

PROVIDER: S-EPMC11316398 | biostudies-literature | 2024 Jul

REPOSITORIES: biostudies-literature