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Updated: Jun 2, 2025

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox

Published on: August 28, 2019

一个尺寸不适合所有人:修改传统范式,以评估用于虚拟查的QSAR模型的准确性

James Wellnitz¹, Sankalp Jain², Joshua E Hochuli¹

¹Division of Chemical Biology and Medicinal Chemistry, Laboratory for Molecular Modeling,, UNC Eshelman School of Pharmacy, University of North Carolina, Chapel Hill, NC, 27599, USA.

Journal of cheminformatics

|January 17, 2025

概括

对于虚拟选,优先考虑基于不平衡数据集的定量结构-活动关系 (QSAR) 模型,重点关注正预测值 (PPV). 与传统的平衡精度方法相比,这种方法在早期药物发现中提高了命中率.

科学领域:

计算化学和化学信息学
药物的发现和开发.
在化学科学中的机器学习.

背景情况:

传统的定量结构-活动关系 (QSAR) 建模强调数据集平衡和平衡准确性 (BA).
现代药物发现越来越多地利用QSAR进行大型化学图书馆的虚拟选.

关键词:

计算机辅助的药物发现.击中率击中率击中率没有平衡的数据集.积极的预测值是积极的.在QSAR建模中使用QSAR模型.虚拟选是一个虚拟的选.

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