使用人工智能和机器学习开发疫苗:一篇综述
Varun S Asediya1, Pranav A Anjaria1, Rafiyuddin A Mathakiya1
1Kamdhenu University, Anand, Gujarat, India.
International journal of biological macromolecules
|October 19, 2024
概括
人工智能 (AI) 通过分析数据来识别候选药物并优化设计,可以加速疫苗开发. 对数据质量和伦理考虑的仔细关注对于其在未来的流行病中成功应用至关重要.
科学领域:
- 疫苗学 疫苗学 疫苗学
- 计算生物学 计算生物学
- 生物信息学是一种生物信息学.
背景情况:
- 疫苗开发是复杂的,需要识别抗原,辅助剂和有效的输送系统.
- 随着COVID-19的爆发,人们越来越需要快速有效的疫苗研发.
- 人工智能 (AI) 为生物研究中分析大型数据集提供了强大的工具.
研究的目的:
- 探索AI在疫苗开发的各个阶段的应用.
- 审查机器学习方法如何提高疫苗设计和预测性能.
- 解决与人工智能在疫苗学中的挑战和伦理考虑.
主要方法:
- 审查当前关于AI在疫苗开发中的应用文献.
- 分析机器学习技术,以预测免疫反应,发现辅助剂和优化疫苗参数.
- 讨论AI在蛋白质结构预测和供应链建模中的作用.
主要成果:
- 人工智能可以从蛋白质序列预测免疫反应,并有助于新型疫苗候选人的发现.
- 机器学习有助于辅助剂选择,剂量优化和疫苗供应链管理.
- 人工智能工具可以预测蛋白质结构,这对于抗原设计至关重要.
结论:
- 人工智能具有显著的潜力,可以加速疫苗开发和为未来的流行病做好准备.
- 仔细考虑数据质量,算法偏见和数据隐私对于负责任的AI实施至关重要.
- 将人工智能整合到疫苗研究中需要对方法和数据完整性的强有力的验证.
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