使用Thera-Py对药物和治疗概念的规范化
Matthew Cannon1, James Stevenson1, Kori Kuzma1
1The Steve and Cindy Rasmussen Institute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, United States.
JAMIA open
|November 13, 2023
概括
由于命名的多样性,治疗术语具有挑战性. Thera-Py是一个新的Python包,从多个来源协调药物和治疗概念,改进数据集成和概念重叠.
科学领域:
- 生物医学信息学 生物医学信息学
- 药理学 药理学是指药理学的学科.
- 计算生物学 计算生物学
背景情况:
- 治疗术语管理是复杂的,因为不同的命名和命名策略.
- 治疗本体学的数量和复杂性不断增加,需要协调的跨资源映射.
- 在不同的数据结构和语义表示中连接类似概念是一个重大挑战.
研究的目的:
- 开发一种协调治疗术语的方法.
- 为药物和治疗术语创建统一的概念映射.
- 为了使相似的概念能够联系在一起,尽管有源特定的差异.
主要方法:
- 开发了Thera-Py,这是一个Python包和Web API.
- 利用了9个公共资源和药物和治疗术语的词库.
- 采用定向图形方法来捕获别名,商业名称,注释和关联.
- 将多种描述符结合到单个,可搜索的概念记录中.
主要成果:
- 从9个不同的来源创建了16069个独特的合并治疗概念.
- 观察到在协调后 (9.8%-41.8%) 跨知识库的治疗概念重叠的显著增加.
- 证明了 Thera-Py 统一描述符的能力,无论其本体起源如何.
结论:
- 疗法-Py有效地使治疗概念正常化,通常是它们的活性成分.
- 该包将多种治疗描述符统一到连贯的概念记录中.
- 通过Therapy-Py进行协调,提高了跨资源治疗知识的整合和可比性.
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