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      Thematic series on biomedical ontologies in JBMS: challenges and new directions

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          Abstract

          Over the past 15 years, the biomedical research community has increased its efforts to produce ontologies encoding biomedical knowledge, and to provide the corresponding infrastructure to maintain them. As ontologies are becoming a central part of biological and biomedical research, a communication channel to publish frequent updates and latest developments on them would be an advantage.

          Here, we introduce the JBMS thematic series on Biomedical Ontologies. The aim of the series is to disseminate the latest developments in research on biomedical ontologies and provide a venue for publishing newly developed ontologies, updates to existing ontologies as well as methodological advances, and selected contributions from conferences and workshops. We aim to give this thematic series a central role in the exploration of ongoing research in biomedical ontologies and intend to work closely together with the research community towards this aim. Researchers and working groups are encouraged to provide feedback on novel developments and special topics to be integrated into the existing publication cycles.

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          Most cited references30

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          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
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            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
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              ChEBI: a database and ontology for chemical entities of biological interest

              Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/
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                Author and article information

                Contributors
                Journal
                J Biomed Semantics
                J Biomed Semantics
                Journal of Biomedical Semantics
                BioMed Central
                2041-1480
                2014
                6 March 2014
                : 5
                : 15
                Affiliations
                [1 ]Department of Computer Science, Aberystwyth University, Llandinam Building, SY23 3DB Aberystwyth, UK
                [2 ]OHSU Library and Department of Medical Informatics, Portland, Oregon, USA
                [3 ]Department of Medical Informatics and Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
                [4 ]School of Computer Science, The University of Manchester, Oxford Road, M13 9PL Manchester, UK
                [5 ]Department of Computational Linguistics, University of Zürich, Binzmühlestrasse 14, 8050 Zürich, Switzerland
                [6 ]European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
                Article
                2041-1480-5-15
                10.1186/2041-1480-5-15
                4006457
                24602198
                94afb7ab-307b-45c2-a5c3-2be2f216ee33
                Copyright © 2014 Hoehndorf et al.; licensee 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. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 8 January 2014
                : 9 February 2014
                Categories
                Review

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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