相关实验视频

Updated: Sep 13, 2025

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

584

基于图形卷积自编码器的药物向相互作用预测,使用动态加权剩余GCN

Ming Zeng1, Min Wang2,3, Fuqiang Xie1

  • 1School of Mathematics and Computer Science, Gannan Normal University, Shida South Rd. Rongjiang New District, Ganzhou, 341000, Jiangxi, China.

BMC bioinformatics
|July 30, 2025
PubMed
概括

这项研究介绍了DDGAE,这是一种用于药物向相互作用 (DTI) 预测的新型图形卷积自编码器. DDGAE增强了表示学习和模型稳定性,在DTI预测准确性方面表现优于现有的方法.

关键词:
药物-标药物相互作用双重自我监督的联合培训机制.动态加权卷积残留连接的剩余连接.生成性的对抗性网络.图形卷积自编码器的自编码器

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