食品科学2025，Vol.46Issue(14)：366-375,10.DOI:10.7506/spkx1002-6630-20241130-213
基于机器学习的抑菌活性物质筛选研究进展
Research Progress in the Screening of Antimicrobial Substances Based on Machine Learning
摘要
Abstract
The problem of bacterial resistance poses a significant threat to human and animal health as well as public safety,making the discovery of effective new antimicrobial compounds an urgent priority.Traditional methods for screening antimicrobial activity are often time-consuming and labor-intensive,with limited accuracy and objectivity.As a branch of artificial intelligence,machine learning algorithms have demonstrated exceptional capabilities in processing large-scale data,feature extraction,and model optimization,leading to their increasing application in the screening of antimicrobial substances.This paper reviews commonly used machine learning models,such as random forests,support vector machines,and deep learning,in antimicrobial activity screening.It provides an in-depth exploration of machine learning applications in the discovery of antimicrobial peptides,essential oils,and polyphenols,aiming to offer valuable insights into the application of machine learning techniques for identifying antimicrobial compounds.关键词
机器学习/抑菌活性物质/筛选Key words
machine learning/antimicrobial substances/screening分类
轻工业引用本文复制引用
侯江霞,曹锋,孙丽,周志,姜金辉,王琛鑫,汪兰,石柳,吴文锦,郭晓嘉,陈胜,陈朗..基于机器学习的抑菌活性物质筛选研究进展[J].食品科学,2025,46(14):366-375,10.基金项目
湖北省自然科学基金杰青项目(2022CFA095) （2022CFA095）
湖北省重点研发计划项目(2023BBB103) （2023BBB103）
