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      The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability

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          Abstract

          Background

          The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies.

          Construction and content

          Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class ‘cell in vitro’ have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning.

          Utility and discussion

          The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies—for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs.

          Conclusions

          The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.

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          Most cited references42

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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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            Standardizing immunophenotyping for the Human Immunology Project.

            The heterogeneity in the healthy human immune system, and the immunological changes that portend various diseases, have been only partially described. Their comprehensive elucidation has been termed the 'Human Immunology Project'. The accurate measurement of variations in the human immune system requires precise and standardized assays to distinguish true biological changes from technical artefacts. Thus, to be successful, the Human Immunology Project will require standardized assays for immunophenotyping humans in health and disease. A major tool in this effort is flow cytometry, which remains highly variable with regard to sample handling, reagents, instrument setup and data analysis. In this Review, we outline the current state of standardization of flow cytometry assays and summarize the steps that are required to enable the Human Immunology Project.
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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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                Author and article information

                Contributors
                addiehl@buffalo.edu
                tmeehan@ebi.ac.uk
                ybradford@zfin.org
                brushm@ohsu.edu
                wasila.dahdul@usd.edu
                David.Dougall@UTSouthwestern.edu
                yongqunh@med.umich.edu
                davidos@ebi.ac.uk
                alan.ruttenberg@gmail.com
                siiraa@ebi.ac.uk
                van_slyke@zfin.org
                vasilevs@ohsu.edu
                haendel@ohsu.edu
                judith.blake@jax.org
                cjmungall@lbl.gov
                Journal
                J Biomed Semantics
                J Biomed Semantics
                Journal of Biomedical Semantics
                BioMed Central (London )
                2041-1480
                4 July 2016
                4 July 2016
                2016
                : 7
                : 44
                Affiliations
                [ ]Department of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, Buffalo, NY 14203 USA
                [ ]European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, Cambridge, CB10 1SD UK
                [ ]ZFIN, the Zebrafish Model Organism Database, 5291 University of Oregon, Eugene, OR 97403 USA
                [ ]Ontology Development Group, Library, Oregon Health and Science University, Portland, Oregon 97239 USA
                [ ]Department of Biology, University of South Dakota, Vermillion, SD 57069 USA
                [ ]National Evolutionary Synthesis Center, Durham, NC 27705 USA
                [ ]Southwestern Medical Center, University of Texas, Dallas, TX 75235 USA
                [ ]Unit for Laboratory Animal Medicine, University of Michigan Medical School, Ann Arbor, MI 48109 USA
                [ ]Oral Diagnostics Sciences, University at Buffalo School of Dental Medicine, Buffalo, NY 14210 USA
                [ ]The Jackson Laboratory, Bar Harbor, ME 04609 USA
                [ ]Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, CA 94720 USA
                Article
                88
                10.1186/s13326-016-0088-7
                4932724
                27377652
                36b9be77-fd4e-4bf7-a4d9-ab5d7a4d7635
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
                : 15 April 2016
                : 23 June 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000051, National Human Genome Research Institute;
                Award ID: HG002273-09Z
                Award ID: HG002273
                Award ID: HG002659
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100006151, Basic Energy Sciences;
                Award ID: DE-AC02-05CH11231
                Funded by: FundRef http://dx.doi.org/10.13039/100000052, NIH Office of the Director;
                Award ID: 1R24OD011883
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000001, National Science Foundation;
                Award ID: DBI-0641025
                Award ID: DBI-1062404
                Award ID: DBI-1062542
                Award ID: EF-0423641
                Award ID: EF-0905606
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: 1R01AI081062
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;
                Award ID: 2R01GM080646-06
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000060, National Institute of Allergy and Infectious Diseases;
                Award ID: HHSN272201200028C
                Categories
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                © The Author(s) 2016

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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