OntoloViz:使用MeSH和ATC本体学进行排名疾病或药物清单的交互可视化GUI
Matthias Ley1,2, Andreas Heinzel1,3, Lucas Fillinger1
1Computational Biology Department, Delta4 GmbH, Vienna 1080, Austria.
Bioinformatics advances
|March 18, 2024
概括
OntoloViz是一个新的图形用户界面工具,可以使用医学主题标题 (MeSH) 和解剖治疗化学 (ATC) 解剖学来可视化药物和疾病数据. 它简化了探索复杂的生物医学信息,而不需要广泛的编程技能.
科学领域:
- 生物信息学是一种生物信息学.
- 医疗信息学 医疗信息学
- 数据可视化 数据可视化
背景情况:
- 像医学科目标题 (MeSH) 和解剖治疗化学 (ATC) 等结构化词汇对注释科学文献和可视化聚合生物医学数据非常有价值.
- 这些本体学的等级性质支持疾病和药物的直观视觉显示,有助于诸如药物重新定位等背景.
- 现有的工具往往需要广泛的编程和数据处理技能,限制了基于本体学的可视化的可访问性.
研究的目的:
- 开发一个用户友好的图形用户界面 (GUI),用于可视化它们各自的MeSH或ATC本体学中的药物或疾病的注释列表.
- 为解释复杂的生物医学数据提供直观的日照布局.
- 为了促进基因和药物清单的探索,使价值在本体论树结构内向上传播.
主要方法:
- 开发了GUI工具 OntoloViz,该工具接受疾病或药物名称列表作为最小输入.
- 包含可选的数值参数用于增强可视化,例如术语频率.
- 实现了一个sunburst布局,用于在MeSH和ATC本体学中直观地表示数据.
主要成果:
- 在MeSH和ATC本体学的背景下,OntoloViz成功地可视化了注释的药物和疾病列表.
- 该工具通过允许值在本体论树上向上传播来促进数据的探索.
- 通过使用案例展示了实用性,包括可视化COVID-19药物 (ATC) 和人类疾病文献注释 (MeSH).
结论:
- OntoloViz提供了一种可访问的解决方案,用于使用结构化本体学来可视化复杂的生物医学数据.
- 图形用户界面简化了这个过程,需要最小的编程专业知识.
- 该工具可以在层次分类中增强对药物和疾病信息的理解和探索.
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