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Updated: Jul 12, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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基于分子图的适用性领域对比学习使图注意力网络模型能够准确预测15个环境终点

Haobo Wang1, Wenjia Liu1, Jingwen Chen1

  • 1Key Laboratory of Industrial Ecology and Environmental Engineering (Ministry of Education), Dalian Key Laboratory on Chemicals Risk Control and Pollution Prevention Technology, School of Environmental Science and Technology, Dalian University of Technology, Dalian 116024, China.

Environmental science & technology
|October 28, 2023
PubMed
概括

新的图表注意力网络 (GAT) 模型准确地预测化学特性和环境命运,优于以前的方法. 这些模型通过一种新的适用性领域方法来增强,实现化学安全评估的基准性能.

关键词:
的QSAR模型模型.适用性领域 (applicability domain) 是一个应用领域.环境命运 环境命运 环境命运图表注意力网络 图表注意力网络分子图对比学习学习物理化学特性 物理化学特性

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