Advances in machine learning for predicting protein functions / 生物工程学报
Chinese Journal of Biotechnology
;
(12): 2141-2157, 2023.
Article
in Chinese
| WPRIM
| ID: wpr-981195
ABSTRACT
Proteins play a variety of functional roles in cellular activities and are indispensable for life. Understanding the functions of proteins is crucial in many fields such as medicine and drug development. In addition, the application of enzymes in green synthesis has been of great interest, but the high cost of obtaining specific functional enzymes as well as the variety of enzyme types and functions hamper their application. At present, the specific functions of proteins are mainly determined through tedious and time-consuming experimental characterization. With the rapid development of bioinformatics and sequencing technologies, the number of protein sequences that have been sequenced is much larger than those can be annotated, thus developing efficient methods for predicting protein functions becomes crucial. With the rapid development of computer technology, data-driven machine learning methods have become a promising solution to these challenges. This review provides an overview of protein function and its annotation methods as well as the development history and operation process of machine learning. In combination with the application of machine learning in the field of enzyme function prediction, we present an outlook on the future direction of efficient artificial intelligence-assisted protein function research.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Artificial Intelligence
/
Proteins
/
Computational Biology
/
Machine Learning
/
Drug Development
Language:
Chinese
Journal:
Chinese Journal of Biotechnology
Year:
2023
Type:
Article
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