农药学学报2024，Vol.26Issue(3)：472-481,10.DOI:10.16801/j.issn.1008-7303.2024.0038
基于机器学习的多类别气味模型研究
Research on multi-category odor model based on machine learning
摘要
Abstract
Olfaction plays a key role in the perception of external chemical signals by organisms,and odor assessment is an important means for humans to understand the olfactory world of organisms.However,the diversity of odor descriptors caused by evaluator subjectivity presents a significant challenge to the prediction of molecular odor attributes using computational methods.Based on single-label data,this study utilizes six machine learning algorithms and soft voting model integration strategies to construct a multi-category odor attribute prediction model for five high-frequency odor categories.The Macro F1 score of the model on the test set and the external test set are all above 0.7,showing good predictive ability and generalization performance.The model also shows some ability to detect counter-intuitive structure-odor relationship,presenting a new possibility for the effective prediction of molecular odor attributes.Simultaneously,this study also predicted the possible odor categories of molecules with mosquito-trapping effect,providing vital clues for elucidating the relationship between mosquito behavior and odor preference.关键词
嗅觉感知/机器学习/特征筛选/气味预测/蚊虫引诱剂Key words
olfactory perception/machine learning/feature screening/odor prediction/mosquito attractants分类
化学工程引用本文复制引用
靳彬艳,李秀珍,时薪媛,韩菲宇,张莉..基于机器学习的多类别气味模型研究[J].农药学学报,2024,26(3):472-481,10.基金项目
国家自然科学基金(22177132). Supported by the National Natural Science Foundation of China(No.22177132). （22177132）
