CoNECo:一个命名实体认可和蛋白质复合物的规范化库
Katerina Nastou1, Mikaela Koutrouli1, Sampo Pyysalo2
1Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen 2200, Denmark.
Bioinformatics advances
|October 16, 2024
概括
本研究介绍了复杂命名实体体库 (CoNECo),用于在生物医学文本中识别和规范含蛋白质的复杂物. 开发的工具实现了强大的性能,使科学文献的全面分析.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 自然语言处理自然语言处理.
背景情况:
- 生物医学信息提取已经进步,但对含有蛋白质的复合体缺乏资源.
- 现有的资源无法充分识别各种各样的生物体的复杂名称.
研究的目的:
- 开发一个专门用于命名实体识别 (NER) 和命名实体规范化 (NEN) 的蛋白质含有复合物的集体.
- 创建和评估用于识别和标准化生物医学文献中复杂实体的计算工具.
主要方法:
- 复杂命名实体库 (CoNECo) 的构建,包含1621个文件和2052个注释的实体.
- 1976年实体对基因本体学 (GO) 的规范化.
- 培训和评估基于变压器和基于字典的标记器.
主要成果:
- CoNECo库在NER和NEN任务中表现出强的表现.
- 基于变压器的标记器获得了73.7%的F分,基于字典的标记器获得了61.2%.
- 开发的标记器用于对开放式生物医学文献进行全面的注释.
结论:
- CoNECo为推进含蛋白复合体识别提供了至关重要的资源.
- 开发的方法为该领域的NER和NEN提供了有效的解决方案.
- 所有资源都是公开可用的,以促进进一步的研究和开发.
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