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Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)
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...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564935/ https://www.ncbi.nlm.nih.gov/pubmed/23017167 http://dx.doi.org/10.1186/1471-2105-13-249 |
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author | Cheung, Warren A Ouellette, BF Francis Wasserman, Wyeth W |
author_facet | Cheung, Warren A Ouellette, BF Francis Wasserman, Wyeth W |
author_sort | Cheung, Warren A |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3564935 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35649352013-02-08 Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) Cheung, Warren A Ouellette, BF Francis Wasserman, Wyeth W BMC Bioinformatics Research Article 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. BioMed Central 2012-09-27 /pmc/articles/PMC3564935/ /pubmed/23017167 http://dx.doi.org/10.1186/1471-2105-13-249 Text en Copyright ©2012 Cheung et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 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. |
spellingShingle | Research Article Cheung, Warren A Ouellette, BF Francis Wasserman, Wyeth W Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title | Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title_full | Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title_fullStr | Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title_full_unstemmed | Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title_short | Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs) |
title_sort | quantitative biomedical annotation using medical subject heading over-representation profiles (meshops) |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3564935/ https://www.ncbi.nlm.nih.gov/pubmed/23017167 http://dx.doi.org/10.1186/1471-2105-13-249 |
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