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Disease Ontology: improving and unifying disease annotations across species

Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficul...

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Autores principales: Bello, Susan M., Shimoyama, Mary, Mitraka, Elvira, Laulederkind, Stanley J. F., Smith, Cynthia L., Eppig, Janan T., Schriml, Lynn M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Company of Biologists Ltd 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5897730/
https://www.ncbi.nlm.nih.gov/pubmed/29590633
http://dx.doi.org/10.1242/dmm.032839
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author Bello, Susan M.
Shimoyama, Mary
Mitraka, Elvira
Laulederkind, Stanley J. F.
Smith, Cynthia L.
Eppig, Janan T.
Schriml, Lynn M.
author_facet Bello, Susan M.
Shimoyama, Mary
Mitraka, Elvira
Laulederkind, Stanley J. F.
Smith, Cynthia L.
Eppig, Janan T.
Schriml, Lynn M.
author_sort Bello, Susan M.
collection PubMed
description Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's and RGD's disease term annotations identified new terms that enhance DO's representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO's usability across human data, MGD, RGD and the rest of the model organism database community.
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spelling pubmed-58977302018-04-13 Disease Ontology: improving and unifying disease annotations across species Bello, Susan M. Shimoyama, Mary Mitraka, Elvira Laulederkind, Stanley J. F. Smith, Cynthia L. Eppig, Janan T. Schriml, Lynn M. Dis Model Mech Resource Article Model organisms are vital to uncovering the mechanisms of human disease and developing new therapeutic tools. Researchers collecting and integrating relevant model organism and/or human data often apply disparate terminologies (vocabularies and ontologies), making comparisons and inferences difficult. A unified disease ontology is required that connects data annotated using diverse disease terminologies, and in which the terminology relationships are continuously maintained. The Mouse Genome Database (MGD, http://www.informatics.jax.org), Rat Genome Database (RGD, http://rgd.mcw.edu) and Disease Ontology (DO, http://www.disease-ontology.org) projects are collaborating to augment DO, aligning and incorporating disease terms used by MGD and RGD, and improving DO as a tool for unifying disease annotations across species. Coordinated assessment of MGD's and RGD's disease term annotations identified new terms that enhance DO's representation of human diseases. Expansion of DO term content and cross-references to clinical vocabularies (e.g. OMIM, ORDO, MeSH) has enriched the DO's domain coverage and utility for annotating many types of data generated from experimental and clinical investigations. The extension of anatomy-based DO classification structure of disease improves accessibility of terms and facilitates application of DO for computational research. A consistent representation of disease associations across data types from cellular to whole organism, generated from clinical and model organism studies, will promote the integration, mining and comparative analysis of these data. The coordinated enrichment of the DO and adoption of DO by MGD and RGD demonstrates DO's usability across human data, MGD, RGD and the rest of the model organism database community. The Company of Biologists Ltd 2018-03-01 /pmc/articles/PMC5897730/ /pubmed/29590633 http://dx.doi.org/10.1242/dmm.032839 Text en © 2018. Published by The Company of Biologists Ltd http://creativecommons.org/licenses/by/3.0This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.
spellingShingle Resource Article
Bello, Susan M.
Shimoyama, Mary
Mitraka, Elvira
Laulederkind, Stanley J. F.
Smith, Cynthia L.
Eppig, Janan T.
Schriml, Lynn M.
Disease Ontology: improving and unifying disease annotations across species
title Disease Ontology: improving and unifying disease annotations across species
title_full Disease Ontology: improving and unifying disease annotations across species
title_fullStr Disease Ontology: improving and unifying disease annotations across species
title_full_unstemmed Disease Ontology: improving and unifying disease annotations across species
title_short Disease Ontology: improving and unifying disease annotations across species
title_sort disease ontology: improving and unifying disease annotations across species
topic Resource Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5897730/
https://www.ncbi.nlm.nih.gov/pubmed/29590633
http://dx.doi.org/10.1242/dmm.032839
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