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推动药物发现分子性质预测的边界,使用多任务学习BERT增强SMILES计数

Xiao-Chen Zhang1,2,3, Cheng-Kun Wu3, Jia-Cai Yi3

  • 1Xiangya School of Pharmaceutical Sciences, Central South University, Changsha 410013, Hunan, P. R. China.

Research (Washington, D.C.)
|September 17, 2024
PubMed
概括

本研究介绍了MTL-BERT,这是一种深度学习模型,通过使用大型未标记数据集和多任务学习来改善分子性质预测. 它克服了数据稀缺性,以便更好地预测药物发现.

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