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图形和多层次序列融合学习用于预测BACE-1抑制剂的分子活性

Shaohua Zheng1, Changwang Zhang1, Youjia Chen1

  • 1College of Physics and Information Engineering, Fuzhou University, Fuzhou 350108, China.

International journal of molecular sciences
|February 26, 2025
PubMed
概括

这项研究引入了一种新的图形和多层次序列融合学习 (GSFL) 模型,以提高对阿尔茨海默病治疗的BACE-1抑制剂的预测. 该模型整合了图形和序列数据,显著提高了分子活动预测的准确性.

关键词:
阿尔茨海默氏症是阿尔茨海默氏症的一种疾病.这是一种BACE-1抑制剂.融合学习 融合学习图表神经网络的神经网络分子活动预测分子活动预测.

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