PatCID:专利文件中的化学结构的开放访问数据集
Lucas Morin1,2, Valéry Weber3, Gerhard Ingmar Meijer3
1IBM Research, Säumerstrasse 4, 8803, Rüschlikon, Switzerland. lum@zurich.ibm.com.
Nature communications
|August 2, 2024
概括
从专利中检索出化学结构的数据库PatCID比其他数据库检索出更多的分子. 这加快了药物发现和材料科学研究的速度,并提供了可以自由访问的数据.
科学领域:
- 化学 化学 化学
- 生物技术是生物技术.
- 材料科学 是一种材料科学.
- 知识产权知识产权知识产权
背景情况:
- 专利出版物包含有价值的化学结构信息,对于药物发现和材料科学至关重要.
- 在大规模的专利中访问和分析这些化学结构是具有挑战性的.
- 现有的化学专利数据库在全面的分子检索方面存在局限性.
研究的目的:
- 引入PatCID (专利提取的化学结构图像数据库用于发现),这是从专利文件中提取的化学结构的大规模数据库.
- 与现有的最先进的数据库相比,评估PatCID在检索化学结构方面的表现.
- 突显PatCID在加速研发方面的实用性.
主要方法:
- 开发PatCID,一个包含8100万化学结构图像和1400万从专利中提取的独特化学结构的数据库.
- 将PatCID的检索性能与自动创建的 (谷歌专利,SureChEMBL) 和手动创建的 (Reaxys,SciFinder) 化学专利数据库进行比较.
- 使用最先进的文档理解方法来提取高质量的数据.
主要成果:
- 在一个随机数据集上,PatCID实现了56.0%的分子检索率.
- 在自动检索方面,PatCID的表现优于谷歌专利 (41.5%) 和SureChEMBL (23.5%).
- PatCID的性能与手动策划的数据库竞争,如Reaxys (53.5%) 和SciFinder (49.5%).
结论:
- PatCID提供来自专利的高质量的化学结构数据,超过现有的自动生成数据库.
- PatCID显示了与专有,手动策划的化学专利数据库相比的竞争性表现.
- 免费访问的PatCID数据集有助于应用自动文献审查和分子生成.
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