化学信息学中的数据策划:重要性和实施
Tsuyoshi Esaki1, Kazuyoshi Ikeda2,3
1Faculty of Data Science, Shiga University, 1-1-1 Banba, Hikone, Shiga, 522-8522, Japan. tsuyoshi-esaki@biwako.shiga-u.ac.jp.
Journal of cheminformatics
|March 2, 2026
概括
有效的数据策划对于化学信息学和计算药物发现至关重要. 本综述综合了结构和实验条件策划的最佳实践,导致更准确和可重复的预测模型.
科学领域:
- 化学信息学 化学信息学
- 计算机化药物发现技术
- 数据科学数据科学数据科学
背景情况:
- 有大量的化学和生物数据集可用,但包含不一致和错误.
- 这些数据问题限制了计算模型的性能和可重现性.
- 标准化数据策划对于可靠的化学信息学工作流程至关重要.
研究的目的:
- 为化学信息学中数据策划最佳实践提供叙述性审查.
- 在结构和实验条件方面围绕化学数据策划的框架.
- 为建立可靠的化学信息模型提供实用指导.
主要方法:
- 对数据不一致及其影响的综合证据.
- 修订了标准化和QSAR准备工作流程,用于结构策划.
- 概述了从文献和数据库中组装条件意识数据集的策略.
主要成果:
- 数据策划的双支柱框架:结构和实验条件.
- 案例研究表明,通过精选数据改善了模型的准确性和可重复性.
- 确定用于数据管理的工具,最佳实践和决策点.
结论:
- 严格的数据策划,包括结构和实验条件,对于准确和可重复的化学信息模型至关重要.
- 本综述巩固了最佳实践,为研究人员提供了实际指导.
- 未来的方向包括自动化策划和建立元数据社区标准.
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