基于极限梯度提升算法和特征筛选方法的羊角月牙藻(Selenastrum capricornutum)急性毒性定量构效关系(QSAR)模型的建立与应用

CORC > 烟台海岸带研究所 > 中国科学院烟台海岸带研究所 > 中科院海岸带环境过程与生态修复重点实验室

	基于极限梯度提升算法和特征筛选方法的羊角月牙藻(Selenastrum capricornutum)急性毒性定量构效关系(QSAR)模型的建立与应用
	滕跃发 1,2,3; 王晓晴 1,2,3; 李斐 2,3; 吉成龙 2,3; 吴惠丰 2,3
刊名	生态毒理学报
	2023
卷号	18 期号:3 页码:33-46
关键词	多环芳烃羊角月牙藻定量构效关系机器学习极限梯度提升特征筛选
ISSN号	1673-5897
其他题名	Development and Application of Quantitative Structure-activity Relationship (QSAR) Model for Acute Toxicity of Selenastrum capricornutum Based on Extreme Gradient Boosting Algorithm and Feature Selection Method
文献子类	期刊论文
英文摘要	Algae as the main primary producers in aquatic food webs play an important role in ensuring the sustainability of aquatic ecosystems.However,a large number of chemicals have been released into the aquatic environment with the development of industrial production and countless other human activities,posing a great threat to algae.If algae are endangered,they will inevitably affect other aquatic organisms.Therefore,it is imperative to assess environmental toxicity on algae.The assessment requires a large amount of toxicity data through experimental measurements,which is costly and time consuming.Quantitative structure activity relationships (QSAR) is a good alternative method to solve these problems.In this study,QSAR models for the acute toxicity of Selenastrum capricornutum were constructed by using the extreme gradient boosting (XGB) algorithm and feature selection method.53 acute toxicity data were gathered from Web of Science and China National Knowledge Infrastructure.The optimal model achieved a coefficient of determination (R_(TR)~2) of 0.97 for training set,a coefficient of determination(Q_(EXT)~2) of 0.78 for validation set,and a leave-one-out cross-validation coefficient (Q_(LOO)~2) of 0.51,respectively.In addition,the results showed that the topological charge number,total atomic number and electronegativity of the compounds were the key factors affecting the acute toxicity of Selenastrum capricornutum.On this basis,the established QSAR model and EPI Suite were used to predict the acute toxicity of 16 typical polycyclic aromatic hydrocarbons(PAHs) to algae,respectively.This study provides an efficient predictive tool for obtaining acute toxicity data of algae and helps to accelerate environmental risk assessment of algae.
语种	中文
CSCD记录号	CSCD:7523173
内容类型	期刊论文
源URL	[http://ir.yic.ac.cn/handle/133337/34196]
专题	烟台海岸带研究所_中科院海岸带环境过程与生态修复重点实验室
作者单位	1.中国科学院大学,北京100049; 2.中国科学院海岸带环境过程与生态修复重点实验室(烟台海岸带研究所),山东省海岸带环境过程重点实验室,中国科学院烟台海岸带研究所,烟台264003; 3.中国科学院海洋大科学中心,青岛266071
推荐引用方式 GB/T 7714	滕跃发,王晓晴,李斐,等. 基于极限梯度提升算法和特征筛选方法的羊角月牙藻(Selenastrum capricornutum)急性毒性定量构效关系(QSAR)模型的建立与应用[J]. 生态毒理学报,2023,18(3):33-46.
APA	滕跃发,王晓晴,李斐,吉成龙,&吴惠丰.(2023).基于极限梯度提升算法和特征筛选方法的羊角月牙藻(Selenastrum capricornutum)急性毒性定量构效关系(QSAR)模型的建立与应用.生态毒理学报,18(3),33-46.
MLA	滕跃发,et al."基于极限梯度提升算法和特征筛选方法的羊角月牙藻(Selenastrum capricornutum)急性毒性定量构效关系(QSAR)模型的建立与应用".生态毒理学报 18.3(2023):33-46.