[Advances in machine learning for predicting protein functions].
Sheng Wu Gong Cheng Xue Bao
; 39(6): 2141-2157, 2023 Jun 25.
Article
in Zh
| MEDLINE
| ID: mdl-37401587
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.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Artificial Intelligence
/
Machine Learning
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
Zh
Journal:
Sheng Wu Gong Cheng Xue Bao
Journal subject:
BIOTECNOLOGIA
Year:
2023
Document type:
Article
Affiliation country: