Protein functional annotation of simultaneously improved stability, accuracy and false discovery rate achieved by a sequence-based deep learning

• Published in: Briefings in bioinformatics Vol. 21; no. 4; pp. 1437 - 1447
• Main Authors: Hong, Jiajun, Luo, Yongchao, Zhang, Yang, Ying, Junbiao, Xue, Weiwei, Xie, Tian, Tao, Lin, Zhu, Feng
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 02.08.2019; Oxford Publishing Limited (England)
• Subjects: Accuracy; Algorithms; Amino acid sequence; Annotations; Computer applications; Deep learning; Machine learning; Problem Solving Protocol; Proteins; Stability; Strategy; annotation accuracy; deep learning; prediction stability; protein function prediction; false discovery rate
• ISSN: 1477-4054; 1467-5463; 1477-4054
• DOI: 10.1093/bib/bbz081

Abstract Functional annotation of protein sequence with high accuracy has become one of the most important issues in modern biomedical studies, and computational approaches of significantly accelerated analysis process and enhanced accuracy are greatly desired. Although a variety of methods have bee...