从生物医学文献中识别基因组数据来源
Xu Zuo1, Ashley Gilliam1, Yan Hu1
1University of Texas Health Science Center at Houston, Houston, TX, USA.
概括
在研究中准确引用基因组数据对于可复制性和归属性至关重要. 本研究引入了一个新的库和基于BERT的模型,以改善基因组数据源的识别和引用,增强数据共享和重复使用.
科学领域:
- 基因组学就是基因组学.
- 生物信息学是一种生物信息学.
- 数据科学数据科学数据科学
背景情况:
- 基因组研究产生了大量的数据,需要强大的数据引用实践.
- 目前的数据引用方法往往不够,阻碍了基因组研究中的可复制性和适当的归因.
- 标准化数据引用对于推动基因组研究和数据共享至关重要.
研究的目的:
- 为识别基因组数据源及其属性开发一个黄金标准库.
- 创建和评估基因组数据提及和关系的信息提取模型.
- 提高基因组研究出版物中数据引用的准确性和完整性.
主要方法:
- 创建一个有实体 (数据集,存储库,贡献者) 和属性 (加入号码,URL,DOI) 的分类库.
- 数据源实体和属性之间的关系的注释.
- 实施基于BERT的信息提取管道,以识别提及和关系.
- 评估使用F1分数的注释者间协议和模型性能.
主要成果:
- 开发的数据库有助于识别基因组数据源和相关元数据.
- 基于BERT的模型在识别数据源提及时获得了0.94的F1评分.
- 这些模型在提取数据提及和属性之间的关系方面获得了0.76的F1得分.
- 这项研究证明了拟议方法在应对数据引用挑战方面的有效性.
结论:
- 引入的数据库和模型代表了基因组数据源自动识别的重大进步.
- 改进的数据引用实践将促进更大的数据共享和重用在基因组学.
- 这项工作为开发更复杂的工具管理和引用研究数据提供了基础.
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