大数据和人工智能驱动技术在CADD (计算机辅助药物设计) 的应用
1Department of Mechanical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
Methods in molecular biology (Clifton, N.J.)
|September 7, 2023
概括
计算机辅助药物设计 (CADD) 利用大数据和人工智能 (AI) 加快药物开发. 数据预处理和人工智能方法增强了复杂的生物医学数据的分析,以有效地发现药物.
科学领域:
- 计算化学和药理学计算化学和药理学
- 生物信息学和计算生物学
- 人工智能在药物发现中的作用
背景情况:
- 药物设计是复杂的,昂贵的,耗时的.
- 大数据和人工智能的进步为CADD提供了新的解决方案.
- 生物医学数据的复杂性需要先进的分析方法.
研究的目的:
- 突出大数据和人工智能在现代药物设计中的作用.
- 强调数据预处理对于CADD中的AI应用的重要性.
- 探索AI和大数据如何克服药物开发挑战.
主要方法:
- 大数据分析和人工智能方法的应用.
- 对生物医学原始数据的数据预处理技术的实施.
- 利用人工智能预测ADMET属性,识别绑定站点和虚拟选.
主要成果:
- 人工智能和大数据使大规模生物医学数据集的准确分析成为可能.
- 数据预处理确保了AI驱动的药物设计的一致性和可重复性.
- 这些技术有助于有效预测药物特性和目标相互作用.
结论:
- 大数据和人工智能对于推进计算机辅助药物设计至关重要.
- 有效的数据预处理对于在CADD中成功实施AI至关重要.
- 人工智能驱动的方法正在改变新药开发的格局.
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