抗菌肽
抗菌剂
计算机科学
人工智能
计算生物学
数据库
生物
微生物学
作者
Xiangrun Zhou,Guixia Liu,Shuyuan Cao,Ji Lv
标识
DOI:10.1021/acs.jcim.5c00006
摘要
Antimicrobial peptides are a promising strategy to combat antimicrobial resistance. However, the experimental discovery of antimicrobial peptides is both time-consuming and laborious. In recent years, the development of computational technologies (especially deep learning) has provided new opportunities for antimicrobial peptide prediction. Various computational models have been proposed to predict antimicrobial peptide. In this review, we focus on deep learning models for antimicrobial peptide prediction. We first collected and summarized available data resources for antimicrobial peptides. Subsequently, we summarized existing deep learning models for antimicrobial peptides and discussed their limitations and challenges. This study aims to help computational biologists design better deep learning models for antimicrobial peptide prediction.
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