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Updated: May 21, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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一种可解释的深度几何学习模型,用于预测突变对蛋白质-蛋白质相互作用的影响,使用大规模蛋白质语言模型

Caiya Zhang1, Yan Sun1,2,3, Pingzhao Hu4,5,6,7,8,9

  • 1Department of Computer Science, Western University, London, ON, Canada.

Journal of cheminformatics
|March 22, 2025
PubMed
概括

这项研究引入了一种基于变压器的新型图形神经网络,以准确预测蛋白质-蛋白质相互作用 (PPI) 的变化. 该模型整合了本地和全球特征,优于理解疾病病因的现有方法.

关键词:
结合性亲缘关系是一种结合性亲缘关系.图形神经网络 (GNN) 是一个神经网络.图形变压器 图形变压器突变改变了突变的变化.蛋白蛋白相互作用 (PPI) 是一种蛋白蛋白相互作用.

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