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Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)

机译:使用医学主题词过度陈述档案(MeSHOP)的定量生物医学注释

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Background MEDLINE?/PubMed? indexes over 20 million biomedical articles, providing curated annotation of its contents using a controlled vocabulary known as Medical Subject Headings (MeSH). The MeSH vocabulary, developed over 50+ years, provides a broad coverage of topics across biomedical research. Distilling the essential biomedical themes for a topic of interest from the relevant literature is important to both understand the importance of related concepts and discover new relationships. Results We introduce a novel method for determining enriched curator-assigned MeSH annotations in a set of papers associated to a topic, such as a gene, an author or a disease. We generate MeSH Over-representation Profiles (MeSHOPs) to quantitatively summarize the annotations in a form convenient for further computational analysis and visualization. Based on a hypergeometric distribution of assigned terms, MeSHOPs statistically account for the prevalence of the associated biomedical annotation while highlighting unusually prevalent terms based on a specified background. MeSHOPs can be visualized using word clouds, providing a succinct quantitative graphical representation of the relative importance of terms. Using the publication dates of articles, MeSHOPs track changing patterns of annotation over time. Since MeSHOPs are quantitative vectors, MeSHOPs can be compared using standard techniques such as hierarchical clustering. The reliability of MeSHOP annotations is assessed based on the capacity to re-derive the subset of the Gene Ontology annotations with equivalent MeSH terms. Conclusions MeSHOPs allows quantitative measurement of the degree of association between any entity and the annotated medical concepts, based directly on relevant primary literature. Comparison of MeSHOPs allows entities to be related based on shared medical themes in their literature. A web interface is provided for generating and visualizing MeSHOPs.
机译:背景MEDLINE?/ PubMed?索引超过2000万条生物医学文章,并使用称为医学主题词(MeSH)的受控词汇对其内容进行精选注释。 MeSH词汇已发展了50多年,涵盖了生物医学研究的广泛主题。从相关文献中提炼出感兴趣的主题的基本生物医学主题对于理解相关概念的重要性和发现新的关系非常重要。结果我们引入了一种新颖的方法,用于确定与主题(例如基因,作者或疾病)相关的一组论文中由策展人分配的MeSH注释。我们生成MeSH过度代表配置文件(MeSHOP),以一种便于进一步进行计算分析和可视化的形式对注释进行定量汇总。基于分配术语的超几何分布,MeSHOP从统计学上解释了相关生物医学注释的流行,同时根据指定的背景突出显示了异常流行的术语。可以使用词云将MeSHOP可视化,从而提供术语相对重要性的简洁定量图形表示。使用文章的发布日期,MeSHOP可以跟踪注释随时间变化的模式。由于MeSHOP是定量向量,因此可以使用标准技术(例如层次聚类)比较MeSHOP。 MeSHOP注释的可靠性是基于使用等效MeSH术语重新推导基因本体注释的子集的能力来评估的。结论MeSHOPs可以直接基于相关的主要文献定量测量任何实体与注释医学概念之间的关联度。 MeSHOP的比较使实体可以根据文献中共享的医学主题进行关联。提供了用于生成和可视化MeSHOP的Web界面。

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