Transparent Exploration of Machine Learning for Biomarker Discovery from Proteomics and Omics Data.

ABSTRACT: Biomarkers are of central importance for assessing the health state and to guide medical interventions and their efficacy; still, they are lacking for most diseases. Mass spectrometry (MS)-based proteomics is a powerful technology for biomarker discovery but requires sophisticated bioinformatics to identify robust patterns. Machine learning (ML) has become a promising tool for this purpose. However, it is sometimes applied in an opaque manner and generally requires specialized knowledge. To enable easy access to ML for biomarker discovery without any programming or bioinformatics skills, we developed "OmicLearn" (http://OmicLearn.org), an open-source browser-based ML tool using the latest advances in the Python ML ecosystem. Data matrices from omics experiments are easily uploaded to an on

SUBMITTER: Torun FM 

PROVIDER: S-EPMC9903317 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature