Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.

Self-supervised models generate implicit labels from unstructured data rather than relying on labeled datasets for supervisory signals. Self-supervised learning (SSL), a transformative subset of ...