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针对神经退行:使用PubChem和scikit-learn发现G9a抑制剂的三种机器学习方法

Mariya L Ivanova1, Nicola Russo2, Konstantin Nikolic2

  • 1School of Computing and Engineering, University of West London, London, UK. mariya.ivanova@uwl.ac.uk.

Journal of computer-aided molecular design
|August 6, 2025
PubMed
概括

开发了三种机器学习模型来预测G9a抑制剂的有效性和活性,为神经科学研究提供了时间和成本有效的工具. 这些模型利用PubChem数据和scikit学习算法,以提供高效的药物发现支持.

关键词:
在CID_SID ML模型中,作为G9a抑制剂的有效性.基于IUPAC的ML模型

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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...