Biomarker discovery is the process of identifying measurable biological indicators, such as gene expression patterns, proteins or metabolites, that correlate with a disease state, treatment response or physiological process. Machine learning methods applied to genomic, proteomic and clinical datasets accelerate this process by detecting patterns across high-dimensional biological data that would be impractical to find manually. Validated biomarkers underpin precision medicine and inform drug discovery by identifying targets and patient stratification criteria.