34
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Disease Ontology: improving and unifying disease annotations across species

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          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.

          Abstract

          Summary: Analyzing diverse disease data requires a comprehensive, robust disease ontology to integrate annotations and retrieve accurate, interpretable results. MGD, RGD and DO are working in collaboration to achieve this goal.

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Uberon, an integrative multi-species anatomy ontology

          We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            MouseMine: a new data warehouse for MGI

            MouseMine (www.mousemine.org) is a new data warehouse for accessing mouse data from Mouse Genome Informatics (MGI). Based on the InterMine software framework, MouseMine supports powerful query, reporting, and analysis capabilities, the ability to save and combine results from different queries, easy integration into larger workflows, and a comprehensive Web Services layer. Through MouseMine, users can access a significant portion of MGI data in new and useful ways. Importantly, MouseMine is also a member of a growing community of online data resources based on InterMine, including those established by other model organism databases. Adopting common interfaces and collaborating on data representation standards are critical to fostering cross-species data analysis. This paper presents a general introduction to MouseMine, presents examples of its use, and discusses the potential for further integration into the MGI interface.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              MEDIC: a practical disease vocabulary used at the Comparative Toxicogenomics Database

              The Comparative Toxicogenomics Database (CTD) is a public resource that promotes understanding about the effects of environmental chemicals on human health. CTD biocurators manually curate a triad of chemical–gene, chemical–disease and gene–disease relationships from the scientific literature. The CTD curation paradigm uses controlled vocabularies for chemicals, genes and diseases. To curate disease information, CTD first had to identify a source of controlled terms. Two resources seemed to be good candidates: the Online Mendelian Inheritance in Man (OMIM) and the ‘Diseases’ branch of the National Library of Medicine's Medical Subject Headers (MeSH). To maximize the advantages of both, CTD biocurators undertook a novel initiative to map the flat list of OMIM disease terms into the hierarchical nature of the MeSH vocabulary. The result is CTD’s ‘merged disease vocabulary’ (MEDIC), a unique resource that integrates OMIM terms, synonyms and identifiers with MeSH terms, synonyms, definitions, identifiers and hierarchical relationships. MEDIC is both a deep and broad vocabulary, composed of 9700 unique diseases described by more than 67 000 terms (including synonyms). It is freely available to download in various formats from CTD. While neither a true ontology nor a perfect solution, this vocabulary has nonetheless proved to be extremely successful and practical for our biocurators in generating over 2.5 million disease-associated toxicogenomic relationships in CTD. Other external databases have also begun to adopt MEDIC for their disease vocabulary. Here, we describe the construction, implementation, maintenance and use of MEDIC to raise awareness of this resource and to offer it as a putative scaffold in the formal construction of an official disease ontology. Database URL: http://ctd.mdibl.org/voc.go?type=disease
                Bookmark

                Author and article information

                Journal
                Dis Model Mech
                Dis Model Mech
                DMM
                dmm
                Disease Models & Mechanisms
                The Company of Biologists Ltd
                1754-8403
                1754-8411
                1 March 2018
                1 March 2018
                : 11
                : 3
                : dmm032839
                Affiliations
                [1 ]The Jackson Laboratory , Bar Harbor, ME, USA
                [2 ]Department of Biomedical Engineering, Medical College of Wisconsin , Milwaukee, WI, USA
                [3 ]Department of Epidemiology and Public Health, Institute for Genome Sciences, University of Maryland School of Medicine , Baltimore, MD, USA
                Author notes
                [*]

                Present address: Faculty of Computer Science, Dalhousie University, Halifax, NS, Canada.

                []Author for correspondence ( susan.bello@ 123456jax.org )
                Author information
                http://orcid.org/0000-0003-4606-0597
                http://orcid.org/0000-0003-1176-0796
                http://orcid.org/0000-0003-0719-3485
                http://orcid.org/0000-0001-5356-4174
                http://orcid.org/0000-0003-3691-0324
                http://orcid.org/0000-0003-1652-8072
                http://orcid.org/0000-0001-8910-9851
                Article
                DMM032839
                10.1242/dmm.032839
                5897730
                29590633
                5cbe74dc-973a-41cf-bbf2-408223d4fc63
                © 2018. Published by The Company of Biologists Ltd

                This 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.

                History
                : 31 October 2017
                : 8 February 2018
                Funding
                Funded by: National Human Genome Research Institute, http://dx.doi.org/10.13039/100000051;
                Award ID: 3U41HG000330-27S2
                Award ID: 5U41HG000330
                Funded by: National Heart, Lung, and Blood Institute, http://dx.doi.org/10.13039/100000050;
                Award ID: 3R01HLB64541
                Categories
                Resource Article

                Molecular medicine
                disease models,mouse,ontologies,rat
                Molecular medicine
                disease models, mouse, ontologies, rat

                Comments

                Comment on this article