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Updated: Jan 29, 2026

Dual-Color Fluorescence Cross-Correlation Spectroscopy to Study Protein-Protein Interaction and Protein Dynamics in Live Cells
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Published on: December 11, 2021

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混合双语境促成交叉注意力框架与语言模型指导,用于多标签预测人类非目标干-蛋白相互作用

Abdullah1,2, Zulaikha Fatima3, Muhammad Ateeb Ather1,2

  • 1Center for Computing Research, Instituto Politécnico Nacional, Mexico City 07320, Mexico.

International journal of molecular sciences
|January 28, 2026
PubMed
概括

本研究介绍了HDPC-LGT,这是一个深度学习框架,用于预测药物异常目标和降低毒性. 它准确地识别了联体蛋白相互作用,改善了药物发现和安全概况.

关键词:
相互注意的注意力交叉.深度学习是一种深度学习.发现药物的发现.图形变压器 图形变压器模型的解释性可解释性多式联络方式的代表性.在目标之外的预测预测多种药理学 多种药理学蛋白联体相互作用脚手架的一般化概括

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