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      Uberon, an integrative multi-species anatomy ontology

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          Abstract

          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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          Most cited references38

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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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            The Gene Ontology project in 2008

            (2008)
            The Gene Ontology (GO) project (http://www.geneontology.org/) provides a set of structured, controlled vocabularies for community use in annotating genes, gene products and sequences (also see http://www.sequenceontology.org/). The ontologies have been extended and refined for several biological areas, and improvements to the structure of the ontologies have been implemented. To improve the quantity and quality of gene product annotations available from its public repository, the GO Consortium has launched a focused effort to provide comprehensive and detailed annotation of orthologous genes across a number of ‘reference’ genomes, including human and several key model organisms. Software developments include two releases of the ontology-editing tool OBO-Edit, and improvements to the AmiGO browser interface.
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              Modeling sample variables with an Experimental Factor Ontology

              Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users. Results: We present the Experimental Factor Ontology, designed to meet cross-domain, application focused use cases for gene expression data. We describe our methodology and open source tools used to create the ontology. These include tools for creating ontology mappings, ontology views, detecting ontology changes and using ontologies in interfaces to enhance querying. The application of reference ontologies to data is a key problem, and this work presents guidelines on how community ontologies can be presented in an application ontology in a data-driven way. Availability: http://www.ebi.ac.uk/efo Contact: malone@ebi.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Genome Biol
                Genome Biol
                Genome Biology
                BioMed Central
                1465-6906
                1465-6914
                2012
                31 January 2012
                : 13
                : 1
                : R5
                Affiliations
                [1 ]Genomics Division, Lawrence Berkeley National Laboratory, 1 Cycltotron Road MS 64-121, Berkeley, CA 94720, USA
                [2 ]Library and Department of Medical Informatics and Clinical Epidemiology Oregon Health and Science University, 3181 SW Sam Jackson Park Rd, Portland, OR 97239, USA
                [3 ]Department of Genetics, University of Cambridge, Downing Street, Cambridge, CB2 3EH, UK
                Article
                gb-2012-13-1-r5
                10.1186/gb-2012-13-1-r5
                3334586
                22293552
                4009d8c8-eee1-4444-a31f-4d2eb7c94003
                Copyright ©2012 Mungall 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.

                History
                : 2 December 2011
                : 31 January 2012
                Categories
                Method

                Genetics
                Genetics

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