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

BMC Bioinformatics

Research Article

Wyeth W Wasserman¹  Warren A Cheung²  BF Francis Ouellette³ 

[1] Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada;Centre for Molecular Medicine and Therapeutics at the Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, Canada;Bioinformatics Graduate Program, University of British Columbia, Vancouver, BC, Canada;Ontario Institute for Cancer Research, Toronto, ON, Canada;Department of Cell and Systems Biology, University of Toronto, Toronto, ON, Canada;

关键词: MeSH;    MeSH Term;    Unify Medical Language System;    Gene Ontology Annotation;    Annotation Property;   

DOI  :  10.1186/1471-2105-13-249

 received in 2012-02-23, accepted in 2012-09-24,  发布年份 2012

来源: Springer

【 摘 要 】

BackgroundMEDLINE®/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.ResultsWe 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.ConclusionsMeSHOPs 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.

【 授权许可】

Unknown   
© Cheung et al.; licensee BioMed Central Ltd. 2012. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.