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复杂QA:用于蛋白质复杂结构评估的深度图形学习方法

Lei Zhang1, Sheng Wang1, Jie Hou2

  • 1Department of Computer Science and Technology, AnHui University, Hefei, 230601, Anhui, China.

Briefings in bioinformatics
|November 6, 2023
PubMed
概括

复杂QA是一种新的深度图神经网络方法,用于评估残留物级别的蛋白质复合体接口质量. 该工具通过评估结构准确性,有助于蛋白质功能分析和药物设计.

关键词:
深度图形学习 (deep graph learning) 是一种深度图形学习.机器学习是机器学习.蛋白质复合体评估 蛋白质复合体评估蛋白质接口 蛋白质接口

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