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Updated: Jun 29, 2025

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K1K2NN:基于邻居的新型多标签分类方法,用于预测COVID-19药物副作用

Pranab Das1, Dilwar Hussain Mazumder1

  • 1Department of Computer Science & Engineering, National Institute of Technology Nagaland, Chumukedima, Dimapur, Nagaland 797103, India.

Computational biology and chemistry
|April 5, 2024
PubMed
概括

预测COVID-19药物的副作用至关重要. 一个新的K1K2近邻 (K1K2NN) 模型使用分子描述符和化学结构准确预测药物SE,提高药物开发安全性.

关键词:
在 COVID-19 疫情中,化学性质 化学性质药物开发 药物开发机器学习 机器学习多个标签的多个标签副作用 副作用 副作用 副作用

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