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Updated: Jun 24, 2025

Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions
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Author Spotlight: A Computational Approach to Decipher Amino Acid Preferences in Multispecific Protein-Protein Interactions

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一种端到端的方法,用于预测化合物-蛋白质相互作用,基于简化的同质图形卷积网络和预训练的语言模型

Yufang Zhang1,2,3, Jiayi Li4, Shenggeng Lin4

  • 1School of Mathematical Sciences and SJTU-Yale Joint Center for Biostatistics and Data Science, Shanghai Jiao Tong University, Shanghai, 200240, China.

Journal of cheminformatics
|June 7, 2024
PubMed
概括

我们开发了SPVec-SGCN-CPI,这是一种用于预测化合物-蛋白质相互作用的新型深度学习方法. 这种方法优于不平衡的数据,加速药物发现和目标识别.

关键词:
化合物-蛋白质相互作用终端到终端的学习.图表 卷积网络 卷积网络在 word2vec 中使用.

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