NMRExtractor:利用大型语言模型,从开源科学出版物中构建一个实验性NMR数据库
Qinggong Wang1,2, Wei Zhang2,3, Mingan Chen2,4,5
1Nanjing University of Chinese Medicine 138 Xianlin Road Nanjing 210023 China myzheng@simm.ac.cn.
Chemical science
|May 30, 2025
概括
NMRExtractor自动从科学文献中提取核磁共振 (NMR) 数据. 这个工具创建了NMRBank,这是一个大型的,开放式访问的NMR信息数据集,以加速化学研究.
科学领域:
- 化学 化学 化学
- 计算化学计算化学
- 数据科学数据科学数据科学
背景情况:
- 核磁共振 (NMR) 光谱对于确定分子结构至关重要.
- 从出版物中手动提取NMR数据是化学研究中的一个重大瓶.
研究的目的:
- 开发一个自动化工具,NMRExtractor,用于高效的NMR数据提取.
- 从科学文献中创建一个全面的,开放的NMR数据集,NMRBank.
主要方法:
- 一个微调的大型语言模型被用于数据提取.
- 处理了超过570万个开源科学出版物.
- 构建了NMRBank,拥有225,809条条目,包括化合物IUPAC名称,NMR条件,1H和13CNMR化学转移,置信级别和引用.
主要成果:
- NMRBank的化学空间比现有的公共NMR数据集大得多.
- 该NMRExtractor工具显示了处理和更新NMRBank数据集的高可扩展性.
- 成功自动提取关键的NMR数据点.
结论:
- NMRExtractor和NMRBank解决了可访问的实验性NMR数据的稀缺问题.
- 这项工作为人工智能驱动的NMR预测提供了基础,并推进了化学研究.
- 自动数据提取和不断更新的数据库加速了化学的进步.
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