Learning functional properties of proteins with language models

• Published in: Nature machine intelligence Vol. 4; no. 3; pp. 227 - 245
• Main Authors: Unsal, Serbulent, Atas, Heval, Albayrak, Muammer, Turhan, Kemal, Acar, Aybar C., Doğan, Tunca
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.03.2022; Nature Publishing Group
• Subjects: 631/114/1305; 631/114/2403; 631/114/2410; 631/114/2784; 639/705/1042; Algorithms; Analysis; Annotations; Benchmarks; Biomarkers; Deep learning; Engineering; Gene expression; Immunoglobulins; Informatics; Kinases; Ligands; Localization; Machine learning; Mutation; Natural language processing; Neural networks; Performance prediction; Proteins; Proteomics; Representations; West Nile virus

Data-centric approaches have been used to develop predictive methods for elucidating uncharacterized properties of proteins; however, studies indicate that these methods should be further improved to effectively solve critical problems in biomedicine and biotechnology, which can be achieved by bette...