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Uberon, an integrative multi-species anatomy ontology
Open accessAbstract
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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![Figure 5 Expression of Distal-less (Dll) and Dll orthologs (Dlx) in 'legs'. (a) Three-day Molgula occidentalis ascidian larva from which an ampulla is extending. (b) Polychaete annelid Chaetopterus variopedatus, ventral view of larva just prior to metamorphosis (anterior to left). Dll expressing cells are visible in parapodial rudiments (arrows), antennae (out of focus on opposite dorsal surface), and in prospective feeding organs (bracket). (c) Metamorphosing Strongylocentrotus droebachiensis sea urchin larvae, aboral view. Cells at the distal tip of the tube feet (arrows) express Dll prior to and during extension from the body wall. (d) Expression in nine-day mouse embryo, lateral view, head top; arrows point to medial border of cells expressing one or more Dlx genes in the presumptive forelimb. (e) The evolutionary appearance of the various appendages for which Dll expression data are indicated in (a-d) are shown on this cladogram (branch lengths are not scaled). Reprinted with modification and permission from [49].](/paper-figures/9a8ed57976584e32bfaa40e23b58636d/uberon-an-integrative-multi-species-anatomy-ontology-figure-5.jpg)
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“When possible, all source tissues have been mapped to standardized Uberon (38) identifiers, enabling us to merge repetitive tissues.”
From TCRD and pharos 2021: mining the human proteome for disease biology (2021) · cites this paper as [38]
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Cites
An algorithm for suffix stripping
Porter, M. F. (1980) · Program · doi:10.1108/eb046814 · Cited by 8,096 · cited 1×
“Using the Blipkit framework [67], we took the names and synonyms from each ontology, tokenized them, and performed Porter-stemming [68], removed certain tokens such as ‘of’ and ‘the’, and matched two classes if the set of stemmed tokens from any label was identical.”
MethodThe OBO Foundry: coordinated evolution of ontologies to support biomedical data integration
Smith, B., Ashburner, M., Rosse, C., Bard, J., Bug, W. J., Ceusters, W. M., Goldberg, L. J., Eilbeck, K. L., Ireland, A., Mungall, C., et al. (2007) · Nature Biotechnology · doi:10.1038/nbt1346 · Cited by 2,546 · cited 1×
“We believe that Uberon meets the current need for an integrative cross-species anatomy ontology amongst the OBO Foundry suite [66].”
BackgroundDBpedia - A crystallization point for the Web of Data
Bizer, C., Lehmann, J., Kobilarov, G., Auer, S., Becker, C., Richard Cyganiak, A., & Hellmann, S. (2009) · Journal of Web Semantics · doi:10.1016/j.websem.2009.07.002 · Cited by 2,144 · cited 6×
“It is important to track the provenance of all information collected in an ontology, and this is particularly important for an ontology such as Uberon, which as a matter of expedience frequently includes ‘tertiary sources’ such as Wikipedia, and other ontologies.”
BackgroundInfluentialA reference ontology for biomedical informatics: the Foundational Model of Anatomy
Rosse, C., & Mejino, J. L. (2003) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2003.11.007 · Cited by 1,167 · cited 19×
“However, the FMA is designed primarily to represent post-embryonic human structures, and would be unsuitable for annotating zebrafish genes expressed in an embryonic fin bud.”
BackgroundInfluentialChEBI: a database and ontology for chemical entities of biological interest
Degtyarenko, K. N., de Matos, P., Ennis, M., Hastings, J., Zbinden, M., McNaught, A., Alcántara, R., Darsow, M., Guedj, M., & Ashburner, M. (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm791 · Cited by 1,130 · cited 1×
“We have included relationships and other logical axioms that reference other ontologies in Uberon, such as the GO, the Neuro Behavior Ontology (NBO) [30], the CL [15], the Protein Ontology [31] and CHEBI [32].”
MethodThe human phenotype ontology: a tool for annotating and analyzing human hereditary disease
Robinson, P. N., Köhler, S., Bauer, S., Seelow, D., Horn, D., & Mundlos, S. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.09.017 · Cited by 1,034 · cited 2×
“We used the MPO [74] and the Human Phenotype Ontology [58] in a method analogous to the one described for GO, above.”
MethodRelations in biomedical ontologies
Smith, B., Ceusters, W. M., Klagges, B. R. E., Köhler, J., Kumar, A., Lomax, J., Mungall, C., Neuhaus, F., Rector, A. L., & Rosse, C. (2005) · Genome biology · doi:10.1186/gb-2005-6-5-r46 · Cited by 1,030
FaCT++ Description Logic Reasoner: System Description
Tsarkov, D., & Horrocks, I. (2006) · Lecture notes in computer science · doi:10.1007/11814771_26 · Cited by 805
The Gene Ontology project in 2008
The Gene Ontology Consortium (2007) · Nucleic Acids Research · doi:10.1093/nar/gkm883 · Cited by 776
Systematic determination of patterns of gene expression during Drosophila embryogenesis
Tomančák, P., Beaton, A., Weiszmann, R., Kwan, E., Shu, S., Lewis, S., Richards, S., Ashburner, M., Hartenstein, V., Celniker, S., et al. (2002) · Genome biology · doi:10.1186/gb-2002-3-12-research0088 · Cited by 725 · cited 1×
“4 [80] to encode GCIs and other advanced OWL features within OBO format.”
Background
Research works printed but not linked: 4
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- Torniai C, Brush M, Vasilevsky N, Segerdell E, Wilson ML, Johnson T, Corday K, Shaffer C, Haendel M: Developing an application ontology for biomedical resource annotation and retrieval: Challenges and lessons learned. Proceedings of the Second International Conference on Biomedical Ontology: July 26-30, 2011; Buffalo, NY. 2011, [http://icbo.buffalo.edu/ICBO-2011_Proceedings.pdf]
- Segerdell E, Wilson ML, Bashor T, Bourges-Waldegg D, Corday K, Frost HR, Johnson T, Shaffer CJ, Stone L, Torniai C, Haendel MA: eagle-i: an ontology-driven framework for biomedical resource annotation and discovery. Nat Precedings. 2010, [http://precedings.nature.com/documents/5176/version/1/files/npre20105176-1.pdf]
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Items 101–200 of 750
Tarasov, S. (2019) · Systematic Biology · doi:10.1093/sysbio/syz005 · Cited by 72
“Such a graph, produced by linking the tail character with UBERON ontology (Mungall et al. 2012), is shown in Figure 7.”
MethodVempati, U. D., Chung, C., Mader, C. C., Koleti, A., Datar, N., Vidović, D., Wrobel, D., Erickson, S. D., Muhlich, J. L., Berriz, G. F., et al. (2014) · SLAS DISCOVERY · doi:10.1177/1087057114522514 · Cited by 75
Pan, H., Deutsch, G. H., Wert, S. E., Subcommittee, O. B. O. T. O., Ambalavanan, N., Ansong, C., Ardini-Poleske, M. E., Bagwell, J., Chan, C., Deutsch, G. H., et al. (2019) · Journal of Biomedical Semantics · doi:10.1186/s13326-019-0209-1 · Cited by 73
“Although these were constructed, in part, by adopting terms from existing ontologies, such as UBERON, CL, EMAP and MA, additional terms were drawn from the literature and incorporated into these ontologies, supplementing the terminology in current anatomic ontologies for mouse and human (Additional file 3).”
InfluentialHarmonizing semantic annotations for computational models in biology
Neal, M. L., König, M., Nickerson, D., Mısırlı, G., Kalbasi, R., Dräger, A., Atalag, K., Chelliah, V., Cooling, M. T., Cook, D. L., et al. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bby087 · Cited by 74
The Cancer Epitope Database and Analysis Resource (CEDAR)
Koşaloğlu‐Yalçın, Z., Blazeska, N., Vita, R., Carter, H. K., Nielsen, M., Schoenberger, S. P., Sette, A., & Peters, B. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac902 · Cited by 73
“The Ontology for Biomedical Investigations (OBI) (28) describes assay types, and the MHC Restriction Ontology (MRO) (29) is used for MHC alleles, Cell Ontology (30) for annotating responder, stimulator, and effector cell types, Uberon (31) for tissue types and the Disease Ontology (32) for describing disease states.”
MethodDeepBlue epigenomic data server: programmatic data retrieval and analysis of epigenome region sets
Albrecht, F., List, M., Bock, C., & Lengauer, T. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw211 · Cited by 71
“They are imported from the Cell Type Ontology (8), Experimental Factor Ontology (9) and Uber Anatomy Ontology (10), following IHEC policy.”
MethodThe Drosophila anatomy ontology
Costa, M., Reeve, S. P., Grumbling, G. B., & Osumi-Sutherland, D. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-32 · Cited by 72
“This approach is already being used to improve the Gene Ontology (GO) [12,13], a number of phenotype ontologies [14-16], the Cell Ontology (CL) [17] and is central to construction of the multi-species anatomy ontology Uberon [18].”
BackgroundMethodInfluentialBalhoff, J. P., Mikó, I., Yoder, M. J., Mullins, P., & DEANS, A. R. (2013) · Systematic Biology · doi:10.1093/sysbio/syt028 · Cited by 70
“2009) across Metazoa will be facilitated by further development of comprehensive multispecies anatomy ontologies such as Uberon (Mungall et al. 2012), which currently provides a coherent ontological structure, to varying degrees of granularity, for the anatomy of many animal groups including vertebrates, insects, and…”
BackgroundYates, J. A. F., Valtueña, A. A., Vågene, Å. J., Cribdon, B., Velsko, I. M., Borry, M., Bravo-Lopez, M., Fernàndez-Guerra, A., Green, E. J., Ramachandran, S. L., et al. (2021) · Scientific Data · doi:10.1038/s41597-021-00816-y · Cited by 69
Matentzoglu, N., Goutte-Gattat, D., Tan, S. Z. K., Balhoff, J. P., Carbon, S., Caron, A. R., Duncan, W. D., Flack, J., Haendel, M. A., Harris, N. L., et al. (2022) · Database · doi:10.1093/database/baac087 · Cited by 65
“ODK is currently used to maintain more than 70 ontologies, mostly in the biomedical domain, such as the widely used Human Phenotype Ontology (HPO) (9), the Cell ontology (CL) (10,11), Uberon (12), PATO (13), the Brain Data Standards Ontology and Provisional Cell Ontology (14).”
The zebrafish anatomy and stage ontologies: representing the anatomy and development of Danio rerio
Slyke, C. E. V., Bradford, Y. M., Westerfield, M., & Haendel, M. A. (2014) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-5-12 · Cited by 68
Phenotype Ontologies and Cross-Species Analysis for Translational Research
Robinson, P. N., & Webber, C. (2014) · PLoS Genetics · doi:10.1371/journal.pgen.1004268 · Cited by 67
“Furthermore, since the ontologies were constructed independently and according to different principles or focus, relating them requires some sophisticated ontological engineering techniques [40].”
BackgroundCell Taxonomy: a curated repository of cell types with multifaceted characterization
Jiang, S., Qian, Q., Zhu, T., Zong, W., Shang, Y., Jin, T., Zhang, Y., Chen, M., Wu, Z., Chu, Y., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac816 · Cited by 69
“The descriptive terms for tissues and diseases were adopted from Uber-anatomy ontology (UBERON) (21) and Disease Ontology (DO) (22), and cellular images were downloaded from Cell Image Library (23). scRNA-seq data collection and analysis To explore expression profiles for cell types and cell markers, a total of 146 sc…”
MethodMouse genetic and phenotypic resources for human genetics
Schofield, P. N., Hoehndorf, R., & Gkoutos, G. V. (2012) · Human Mutation · doi:10.1002/humu.22077 · Cited by 66
“In order to make mappings between these vertebrate anatomies, the metazoan, species-independent UBERON ontology is used in constructing anatomically based cross products [Mungall et al., 2012].”
MethodThe FaceBase Consortium: A comprehensive resource for craniofacial researchers
Brinkley, J. F., Fisher, S., Harris, M. P., Holmes, G., Hooper, J. E., Jabs, E. W., Jones, K. L., Kesselman, C., Klein, O. D., Maas, R. L., et al. (2016) · Development · doi:10.1242/dev.135434 · Cited by 65
“In addition, the Hub is collaborating with the Monarch Initiative (monarchinitiative.org) and the developers of the Uberon (Mungall et al., 2012) to contextualize FaceBase data within a broader set of anatomical and phenotypic data.”
An open source knowledge graph ecosystem for the life sciences
Callahan, T. J., Tripodi, I. J., Stefanski, A. L., Cappelletti, L., Taneja, S. B., Wyrwa, J. M., Casiraghi, E., Matentzoglu, N., Reese, J., Silverstein, J. C., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03171-w · Cited by 76
Nicheformer: A Foundation Model for Single-Cell and Spatial OmicsPreprint
Schaar, A. C., Tejada-Lapuerta, A., Palla, G., Gutgesell, R. M., Halle, L., Minaeva, M., Vornholz, L., Dony, L., Drummer, F., Bahrami, M., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.04.15.589472 · Cited by 66
Modelling kidney disease using ontology: insights from the Kidney Precision Medicine Project
Ong, E., Wang, L. L., Schaub, J. A., O’Toole, J. F., Steck, B., Rosenberg, A. Z., Dowd, F., Hansen, J., Barisoni, L. M. C., Jain, S. R., et al. (2020) · Nature Reviews Nephrology · doi:10.1038/s41581-020-00335-w · Cited by 66
“The OPMI reuses many terms and relationships from existing ontologies, including the Ontology of General Medical Science, OBI, HPO, Uberon, the Onto logy of Adverse Events 46 and the Informed Consent Ontology 47 .”
BackgroundMethodInfluentialDececchi, T. A., Balhoff, J. P., Lapp, H., & Mabee, P. (2015) · Systematic Biology · doi:10.1093/sysbio/syv031 · Cited by 65
“…The properties part_of (BFO:0000050) and connected_to (RO:0002170) are from the OBO Relations Ontology (Smith et al. 2005), and the classes “paired limb/fin” (UBERON:0004708) and “girdle skeleton” (UBERON:0010719) are from the Uberon anatomy ontology (Mungall et al. 2012; Haendel et al. 2014).”
BackgroundMethodInfluentialMirDIP 5.2: tissue context annotation and novel microRNA curation
Hauschild, A.-C., Pastrello, C., Ekaputeri, G. K. A., Bethune-Waddell, D., Abovsky, M., Ahmed, Z., Kotlyar, M., Lu, R., & Jurišica, I. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac1070 · Cited by 65
“com/NCI-Thesaurus/thesaurus-obo-edition), UBERON (32) and OBA (https://github.”
Roncaglia, P., Martone, M. E., Hill, D. P., Berardini, T., Foulger, R. E., Imam, F. T., Drabkin, H., Mungall, C., & Lomax, J. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-20 · Cited by 63
“The GO-CCO also excludes multicellular anatomical terms, with such structures being described by either species-specific ontologies (e.g., Zebrafish anatomy ontology [12], Mouse gross anatomy ontology [13]) or taxonomically broad anatomical ontologies (e.g., Uberon [14], PO).”
Mapping anatomical related entities to human body parts based on wikipedia in discharge summaries
Wang, Y., Fan, X., Chen, L., Chang, E., Ananiadou, S., Tsujii, J., & Xu, Y. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-3005-0 · Cited by 9
Overview of YAM - (Not) Yet Another Matcher for Ontology Alignment Task
Ngo, D., & Bellahsène, Z. (2016) · Journal of Web Semantics · doi:10.1016/j.websem.2016.09.002 · Cited by 57
“Notice that UMLS and Uberon contains a lot of mappings between Mouse anatomy and Human anatomy, which cannot be solely discovered by using common string similarity measures.”
MethodInfluentialPredicting candidate genes from phenotypes, functions and anatomical site of expression
Chen, J., Althagafi, A., & Hoehndorf, R. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa879 · Cited by 59
“…2014), their anatomical site of expression in functional genomics experiments (Consortium et al. , 2015) encoded using the UBERON anatomy ontology (Mungall et al. , 2012), and the phenotypes of their mouse orthologs from the Mouse Genome Informatics (MGI) database (Smith et al. , 2017) and…”
InfluentialSCPortalen: human and mouse single-cell centric database
Abugessaisa, I., Noguchi, S., Böttcher, M. E., Hasegawa, A., Kouno, T., Kato, S., Tada, Y., Ura, H., Abe, K., Shin, J. W., et al. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx949 · Cited by 60
“The ontology term was selected from the Cell Ontology (8), the Cell Line Ontology (9) or the Uber Anatomy Ontology (Uberon) (10).”
BackgroundMethodINFERNO: inferring the molecular mechanisms of noncoding genetic variants
Amlie‐Wolf, A., Tang, M., Mlynarski, E. E., Kuksa, P. P., Valladares, O., Katanić, Ž., Tsuang, D. W., Brown, C. D., Schellenberg, G. D., & Wang, L. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky686 · Cited by 56
“Building off existing categorization of Roadmap samples and informed by the UBERON and CL ontologies (24,25) used in the FANTOM5 facet-level classification and in GTEx, the different tissues and cell types from each data source were grouped into 32 major classes, with some data sources further grouped into 58 secondar…”
MethodRoux, J., Liu, J., & Robinson‐Rechavi, M. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx199 · Cited by 59
“Even more valuable, the expression patterns revealed by these hybridizations have been manually annotated to terms from anatomical ontologies, notably the cross-species ontology Uberon describing anatomical structures and their relationships in animals (Hayamizu et al. 2005, 2013; Sprague et al. 2006; Bastian et al. 2…”
BackgroundThe SPARC DRC: Building a Resource for the Autonomic Nervous System Community
Osanlouy, M., Bandrowski, A. E., de Bono, B., Brooks, D., Cassara, A. M., Christie, R., Ebrahimi, N., Gillespie, T., Grethe, J. S., Guercio, L. A., et al. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.693735 · Cited by 57
“SPARC data are aligned to common spatial standards through the processes described in section 7, and also annotated with FAIR vocabularies derived from community ontologies like UBERON (Mungall et al., 2012).”
MethodA guide to the BRAIN Initiative Cell Census Network data ecosystem
Hawrylycz, M., Martone, M. E., Ascoli, G. A., Bjaalie, J. G., Dong, H., Ghosh, S., Gillis, J., Hertzano, R. P., Haynor, D. R., Hof, P. R., et al. (2023) · PLoS Biology · doi:10.1371/journal.pbio.3002133 · Cited by 59
“As an extension of CL, BDSO is fully interoperable with both CL and Uberon [69], allowing data annotated with BDSO terms to be interoperable not only with the BICCN data, but also with datasets from the wider community.”
MethodDynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
Toro, S., Anagnostopoulos, A. V., Bello, S. M., Blumberg, K., Cameron, R., Carmody, L., Diehl, A. D., Dooley, D., Duncan, W. D., Fey, P., et al. (2024) · Journal of Biomedical Semantics · doi:10.1186/s13326-024-00320-3 · Cited by 96
“In the life sciences, ontologies such as the Gene Ontology (GO) [1], Mondo [2], Uberon [3], and FoodOn [4] are used for a variety of purposes such as curation of gene function and expression, classification of diseases, or annotation of food datasets.”
BackgroundBuilding bridges between cellular and molecular structural biology
Patwardhan, A., Brandt, R., Butcher, S. J., Collinson, L., Gault, D., Grünewald, K., Hecksel, C. W., Huiskonen, J. T., Iudin, A., Jones, M. L., et al. (2017) · eLife · doi:10.7554/elife.25835 · Cited by 54
“…Ontology (CMPO; Jupp et al., 2016), NCBI organismal classification (NCBITaxon), integrated cross-species for anatomical structures (UBERON; Mungall et al., 2012), imaging modality and sample preparation from Fbbi (Orloff et al., 2013), Foundational Model of Anatomy (FMA) and Cell Ontology…”
BackgroundGöpel, T., & Wirkner, C. S. (2018) · PLoS ONE · doi:10.1371/journal.pone.0201702 · Cited by 52
Enabling pan-repository reanalysis for big data science of public metabolomics data
Abiead, Y. E., Strobel, M. J., Payne, T., Fahy, E., O’Donovan, C., Subramamiam, S., Vizcaíno, J. A., Yurekten, O., Deleray, V., Zuffa, S., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-60067-y · Cited by 55
Ontology mapping for semantically enabled applications
Harrow, I., Balakrishnan, R., Jiménez-Ruiz, E., Jupp, S., Lomax, J., Reed, J. L., Romacker, M., Senger, C., Splendiani, A., Wilson, J., et al. (2019) · Drug Discovery Today · doi:10.1016/j.drudis.2019.05.020 · Cited by 52
“PhenomeNET is a further example, where species-specific phenotype ontologies are mapped based on the overarching, anatomy ontology, UBERON, which identifies equivalent phenotype features through anatomical concepts across different species [39,40].”
BackgroundEMAP/EMAPA ontology of mouse developmental anatomy: 2013 update
Hayamizu, T. F., Wicks, M. N., Davidson, D. R., Burger, A., Ringwald, M., & Baldock, R. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-15 · Cited by 51
“EMAPA terms and identifiers are also included in bridging extensions to the Uberon multispecies anatomy ontology [14], which will further serve to facilitate integration of mouse developmental data within the broader scientific domain.”
BackgroundGkoutos, G. V., Schofield, P. N., & Hoehndorf, R. (2012) · International review of neurobiology · doi:10.1016/b978-0-12-388408-4.00004-6 · Cited by 51
The Case for Holistic Data Integration
Rahm, E. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-44039-2_2 · Cited by 51
“Such integrated hub ontologies have been determined in the life sciences, e.g., UMLS [10] and Uberon [45], although with the need of a large amount of manual work by domain experts to achieve a high-quality integration result.”
BackgroundThe Plant Ontology Facilitates Comparisons of Plant Development Stages Across Species
Walls, R., Cooper, L., Elser, J. L., Gandolfo, M. A., Mungall, C., Smith, B., Stevenson, D. W., & Jaiswal, P. (2019) · Frontiers in Plant Science · doi:10.3389/fpls.2019.00631 · Cited by 51
The Alliance of Genome Resources: Building a Modern Data Ecosystem for Model Organism Databases
The Alliance of Genome Resources Consortium (2019) · Genetics · doi:10.1534/genetics.119.302523 · Cited by 51
A Unified Anatomy Ontology of the Vertebrate Skeletal System
Dahdul, W., Balhoff, J. P., Blackburn, D. C., Diehl, A. D., Haendel, M. A., Hall, B. K., Lapp, H., Lundberg, J. G., Mungall, C., Ringwald, M., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0051070 · Cited by 50
“Uberon Uber Anatomy Ontology* Metazoa [28] http://obofoundry.”
BackgroundGet GO! Retrieving GO Data Using AmiGO, QuickGO, API, Files, and Tools
Muñoz-Torres, M. C., & Carbon, S. J. (2016) · Methods in molecular biology · doi:10.1007/978-1-4939-3743-1_11 · Cited by 50
“That is, they assigned logical defi nitions (known as OWL axioms or self-evidently true statements) to all the classes; the Gene Ontology has been effectively axiomatized, that is, reduced to this system of axioms in OWL, and is highly dependent on the OWL tool stack [ 10 ].”
BackgroundHuman BioMolecular Atlas Program (HuBMAP): 3D Human Reference Atlas construction and usage
Börner, K., Blood, P. D., Silverstein, J. C., Ruffalo, M., Satija, R., Teichmann, S. A., Pryhuber, G., Misra, R. S., Purkerson, J. M., Fan, J., et al. (2025) · Nature Methods · doi:10.1038/s41592-024-02563-5 · Cited by 61
Matching disease and phenotype ontologies in the ontology alignment evaluation initiative
Harrow, I., Jiménez-Ruiz, E., Splendiani, A., Romacker, M., Woollard, P. M., Markel, S., Alam-Faruque, Y., Koch, M., MALONE, J. M., & Waaler, A. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0162-9 · Cited by 50
“AML has three sources of background knowledge which can be used as mediators between the input ontologies: the Uber Anatomy Ontology [37] (Uberon), the Human Disease Ontology [5] (DOID) and the Medical Subject Headings[17] (MeSH).”
MethodA Census of Disease Ontologies
Haendel, M. A., McMurry, J. A., Relevo, R., Mungall, C. J., Robinson, P. N., & Chute, C. G. (2018) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-080917-013459 · Cited by 49
“This release is a direct transformation of the NCIt using OBO-style term Internationalized Resource Identifiers and annotation properties, with direct references to terms from other domain-specific OBO Library ontologies [e.g., Cell Type Ontology (60) and the Uberon Anatomy Ontology (61)].”
MethodMouse model phenotypes provide information about human drug targets
Hoehndorf, R., Hiebert, T., Hardy, N. W., Schofield, P. N., Gkoutos, G. V., & Dumontier, M. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt613 · Cited by 49
“STITCH identifiers are based on the STITCH database, version 3.1 (Kuhn et al., 2012).”
MethodInfluentialDoelken, S. C., Köhler, S., Mungall, C., Gkoutos, G. V., Ruef, B. J., Smith, C. L., Smedley, D. P., Bauer, S., Klopocki, E., Schofield, P. N., et al. (2012) · Disease Models & Mechanisms · doi:10.1242/dmm.010322 · Cited by 47
“For example, the HPO term ‘increased bone mineral density’ is composed of the Quality (PATO) term ‘increased density’ and the human anatomy term ‘bone organ’, which itself is a subclass of the Uberon (cross-species anatomy ontology) class ‘bone’.”
MethodGulić, M., Vrdoljak, B., & Banek, M. (2016) · Journal of Web Semantics · doi:10.1016/j.websem.2016.09.001 · Cited by 48
Mouse anatomy ontologies: enhancements and tools for exploring and integrating biomedical data
Hayamizu, T. F., Baldock, R., & Ringwald, M. (2015) · Mammalian Genome · doi:10.1007/s00335-015-9584-9 · Cited by 49
Ament, S. A., Adkins, R. S., Carter, R., Chrysostomou, E., Colantuoni, C., Crabtree, J., Creasy, H. H., Degatano, K., Felix, V., Gandt, P., et al. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac962 · Cited by 51
“We are working to implement the use of standard ontologies and controlled vocabularies including NCBI Taxonomy (18), OBI (19), EDAM (20), Uberon (21) to capture information about organism, experimental assays, file types and formats, and anatomy respectively.”
MethodOntology application and use at the ENCODE DCC
Malladi, V. S., Erickson, D. T., Podduturi, N. R., Rowe, L. D., Chan, E. T., Davidson, J. M., Hitz, B. C., Ho, M., Lee, B. T., Miyasato, S. R., et al. (2015) · Database · doi:10.1093/database/bav010 · Cited by 45
“Uberon integrates with CL to provide details of the development and differentiation relationships of primary cells (11, 14).”
BackgroundTackling the challenges of matching biomedical ontologies
Faria, D., Pesquita, C., Mott, I., Martins, C., Couto, F. M., & Cruz, I. F. (2018) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0170-9 · Cited by 47
“For example, the Uber Anatomy Ontology (UBERON) class UBERON_0000948 has amongst its annotations: label “heart”, exact synonyms “vertebrate heart” and “cham-bered heart”, narrow synonym “branchial heart”, related synonym “cardium”, and even relational adjective “cardiac” [2].”
BackgroundMethodCellO: comprehensive and hierarchical cell type classification of human cells with the Cell Ontology
Bernstein, M. N., Ma, Z., Gleicher, M., & Dewey, C. N. (2021) · iScience · doi:10.1016/j.isci.2020.101913 · Cited by 45
Principles of metadata organization at the ENCODE data coordination center
Hong, E. L., Sloan, C. A., Chan, E. T., Davidson, J. M., Malladi, V. S., Strattan, J. S., Hitz, B. C., Gabdank, I., Narayanan, A. K., Ho, M., et al. (2016) · Database · doi:10.1093/database/baw001 · Cited by 47
Chen, C., Shi, W., Balaton, B. P., Matthews, A., Li, Y., Arenillas, D. J., Mathelier, A., Itoh, M., Kawaji, H., Lassmann, T., et al. (2016) · Scientific Reports · doi:10.1038/srep37324 · Cited by 44
GenoSurf: metadata driven semantic search system for integrated genomic datasets
Canakoglu, A., Bernasconi, A., Colombo, A., Masseroli, M., & Ceri, S. (2019) · Database · doi:10.1093/database/baz132 · Cited by 46
“The tissue field is enriched by concepts in the Uberon ontology (31), describing a multicellular component in its natural state, or the provenance tissue of cells.”
BackgroundDingerdissen, H., Bastian, F., Vijay‐Shanker, K., Robinson‐Rechavi, M., Bell, A. L., Gogate, N., Gupta, S., Holmes, E., Kahsay, R., Keeney, J., et al. (2020) · JCO Clinical Cancer Informatics · doi:10.1200/cci.19.00117 · Cited by 46
GenomicKB: a knowledge graph for the human genome
Feng, F., Tang, F., Gao, Y., Zhu, D., Li, T., Yang, S., Yao, Y., Huang, Y., & Liu, J. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac957 · Cited by 53
“GenomicKB includes well-established ontologies related to genes (GO (17) and HGNC (18)), tissues and cell lines (UBERON (19), BTO (20), CL (21), and EFO (22)).”
BackgroundRelation extraction using large language models: a case study on acupuncture point locations
Li, Y., Peng, X., Li, J., Zuo, X., Peng, S., Pei, D., Tao, C., Xu, H., & Hong, N. (2024) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocae233 · Cited by 45
Subramanian, S. L., Kitchen, R. R., Alexander, R. P., Carter, B. S., Cheung, K., Laurent, L. C., Pico, A. R., Roberts, L. R., Roth, M. E., Rozowsky, J. S., et al. (2015) · Journal of Extracellular Vesicles · doi:10.3402/jev.v4.27497 · Cited by 45
“These ontologies include Uber Anatomy Ontology (UBERON) (8) for tissues and Foundation Model of Anatomy (FMA) (9) for biofluids (including controlled values for exRNA sources such as serum, plasma, CSF, urine, saliva and other body fluids), Cell Ontology (CL) (10) for primary cell types and Experimental Factor Ontolog…”
MethodEvolution of biomedical ontologies and mappings: Overview of recent approaches
Groß, A., Pruski, C., & Rahm, E. (2016) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2016.08.002 · Cited by 44
“Beside the huge UMLS there are other merged ontologies such as Uberon [59] in the anatomical domain.”
BackgroundPafilis, E., Buttigieg, P. L., Ferrell, B. D., Pereira-Flores, E., Schnetzer, J., Arvanitidis, C., & Jensen, L. J. (2016) · Database · doi:10.1093/database/baw005 · Cited by 44
“Also, microbiomes associated with certain parts of specific organisms can be described by combining ENVO terms with taxa from NCBI Taxonomy (3) and terms from ontologies that model anatomy (4, 5) and disease phenotypes (6, 7).”
BackgroundTraitBank: Practical semantics for organism attribute data
Parr, C. S., Schulz, K. S., Hammock, J., Wilson, N., Leary, P. R., Rice, J., & Corrigan, R. J. (2016) · Semantic Web · doi:10.3233/sw-150190 · Cited by 43
“whenever possible through links to terms from the Phenotypic Quality Ontology (PATO) [26] or the Uber Anatomy Ontology (UBERON) [27].”
BackgroundModelling plankton ecosystems in the meta-omics era. Are we ready?
Stec, K., Caputi, L., Buttigieg, P. L., D’Alelio, D., Ibarbalz, F. M., Sullivan, M. B., Chaffron, S., Bowler, C., d’Alcalà, M. R., & Iudicone, D. (2017) · Marine Genomics · doi:10.1016/j.margen.2017.02.006 · Cited by 45
Segerdell, E., Ponferrada, V. G., James‐Zorn, C., Burns, K. A., Fortriede, J. D., Dahdul, W., Vize, P. D., & Zorn, A. M. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-31 · Cited by 42
“Its close integration with the cross-species Uber Anatomy Ontology (UBERON) [20] provides a bridge to cell types and other vertebrate anatomy ontologies.”
BackgroundThe Human Cell Atlas: Technical approaches and challenges
Hon, C.-C., Shin, J. W., Carninci, P., & Stubbington, M. J. T. (2017) · Briefings in Functional Genomics · doi:10.1093/bfgp/elx029 · Cited by 40
“Meta-cells might be further organized by anatomical concepts [176], based on the physiological origins of their child-cells or spatial relationships in the context of tissues [53].”
BackgroundAssessing the quality of domain ontologies: Metrics and an automated ranking system
McDaniel, M., Storey, V. C., & Sugumaran, V. (2018) · Data & Knowledge Engineering · doi:10.1016/j.datak.2018.02.001 · Cited by 42
Developing a Knowledge Graph for Pharmacokinetic Natural Product-Drug Interactions
Taneja, S. B., Callahan, T. J., Paine, M. F., Kane‐Gill, S. L., Halil Kilicoglu, B., Joachimiak, M. P., & Boyce, R. D. (2023) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2023.104341 · Cited by 46
Dahdul, W., Cui, H., Mabee, P., Mungall, C., Osumi-Sutherland, D., Walls, R., & Haendel, M. A. (2014) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-5-34 · Cited by 40
“For example, in most vertebrates, the naris (nostril) is bilaterally paired, and it is thus declared in UBERON (the cross-species metazoan Uber Anatomy Ontology) [32,33] as being in_lateral_side_of a head.”
BackgroundTermGenie – a web-application for pattern-based ontology class generation
Dietze, H., Berardini, T., Foulger, R. E., Hill, D. P., Lomax, J., Osumi-Sutherland, D., Roncaglia, P., & Mungall, C. (2014) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-5-48 · Cited by 39
“V metazoan_development X:Uberon anatomical structure development’ and ‘results in development of’ some ?”
BackgroundMethodInfluentialMIMU-Wear: Ontology-based sensor selection for real-world wearable activity recognition
Villalonga, C., Pomares, H., Rojas, I., & Baños, O. (2017) · Neurocomputing · doi:10.1016/j.neucom.2016.09.125 · Cited by 40
The Alzheimer’s Knowledge Base: A Knowledge Graph for Alzheimer Disease Research
Romano, J. D., Truong, V. Q., Kumar, R., Venkatesan, M., Graham, B. E., Hao, Y., Matsumoto, N., Li, X., Wang, Z. P., Ritchie, M. D., et al. (2023) · Journal of Medical Internet Research · doi:10.2196/46777 · Cited by 40
“…side effects (modeled as diseases) SIDER c,l [46] — m Tissue-specific gene expression data TISSUES c [47] 402 Human anatomical structures Uberon c [48] 298 Pathways and gene-pathway membership WikiPathways c [49] a As source data elements do not correspond in a 1-to-1 manner with entities in the…”
Improving ontologies by automatic reasoning and evaluation of logical definitions
Köhler, S., Bauer, S., Mungall, C., Carletti, G., Smith, C. L., Schofield, P. N., Gkoutos, G. V., & Robinson, P. N. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-418 · Cited by 39
OGER++: hybrid multi-type entity recognition
Furrer, L., Jancso, A., Colic, N., & Rinaldi, F. (2019) · Journal of Cheminformatics · doi:10.1186/s13321-018-0326-3 · Cited by 39
“For the speed benchmarks, we used the default configuration of OGER’s web service, which uses up-to-date versions of the resources mentioned above and, in addition, Cellosaurus [49], CTD chemicals and diseases [50], MeSH [51], Swiss-Prot [52], and Uberon [53].”
MethodThe road towards data integration in human genomics: players, steps and interactions
Bernasconi, A., Canakoglu, A., Masseroli, M., & Ceri, S. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa080 · Cited by 39
The importance of digitized biocollections as a source of trait data and a new VertNet resource
Guralnick, R., Zermoglio, P., Wieczorek, J. R., LaFrance, R., Bloom, D., & Russell, L. (2016) · Database · doi:10.1093/database/baw158 · Cited by 39
“Although some of these traits, such as ‘gonads’, ‘tarsus’ or ‘grassland’, might map well to terms already defined in ontologies such as Uberon (53), VTO, the Environment Ontology (54, 55) etc., others will require working with existing initiatives to add new terms or to further clarify properties in order to enhance i…”
BackgroundPast and future uses of text mining in ecology and evolution
Farrell, M. J., Brierley, L., Willoughby, A. R., Yates, A., & Mideo, N. (2022) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2021.2721 · Cited by 38
Martens, M., Evelo, C. T., & Willighagen, E. (2022) · Applied In Vitro Toxicology · doi:10.1089/aivt.2021.0010 · Cited by 38
Use of Model Organism and Disease Databases to Support Matchmaking for Human Disease Gene Discovery
Mungall, C., Washington, N. L., Nguyen-Xuan, J., Condit, C., Smedley, D. P., Köhler, S., Groza, T., Shefchek, K., Hochheiser, H., Robinson, P. N., et al. (2015) · Human Mutation · doi:10.1002/humu.22857 · Cited by 37
“Previously, we have shown how phenotype ontologies from human, mouse, and more distant species such as zebrafish and C. elegans can be integrated together [Mungall et al., 2010; K¨ohler et al., 2013] through the use of multispecies organ system ontologies [Mungall et al., 2012; Haendel et al., 2014].”
BackgroundMethodEnabling semantic queries across federated bioinformatics databases
Sima, A. C., de Farias, T. M., Zbinden, E., Anisimova, M. O., Gil, M., Heinz Stockinger, C., Stockinger, K., Robinson‐Rechavi, M., & Dessimoz, C. (2019) · Database · doi:10.1093/database/baz106 · Cited by 37
EvoTol: a protein-sequence based evolutionary intolerance framework for disease-gene prioritization
Rackham, O. J. L., Shihab, H. A., Johnson, M. R., & Petretto, E. G. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku1322 · Cited by 35
“In addition, EvoTol can integrate cell-type-specific gene expression (from the FANTOM5 consortium (21)) classified using the UBERON cell-type ontology (22).”
MethodExtending gene ontology in the context of extracellular RNA and vesicle communication
Cheung, K.-H., Keerthikumar, S., Roncaglia, P., Subramanian, S. L., Roth, M. E., Samuel, M., Anand, S., Gangoda, L., Gould, S. J., Alexander, R. P., et al. (2016) · Journal of Biomedical Semantics · doi:10.1186/s13326-016-0061-5 · Cited by 37
“A version of GO containing all relationships, including information from the Uber anatomy ontology (UBERON) [39], the Chemical Entities of Biological Interest ontology (ChEBI) [40], the Plant Ontology for plant structure/stage (PO) [41], the Phenotypic Quality Ontology (PATO) [42], and the Sequence…”
Vogt, L. (2016) · Cladistics · doi:10.1111/cla.12179 · Cited by 36
“…(Vogt, 2008b, 2009, 2011; Dahdul et al., 2010; Yoder et al., 2010; Vogt et al., 2010; Vogt et al., 2013; Serna et al., 2011; Deans et al., 2012; Mungall et al., 2012; Richter and Wirkner, 2014; a contrary opinion has been advocated by Franz, 2014).13 This aspect of a non-evolutionary…”
BackgroundBovine Genome Database: new annotation tools for a new reference genome
Shamimuzzaman, M., Tourneau, J. J. L., Unni, D. R., Diesh, C. M., Triant, D. A., Walsh, A. T., Tayal, A., Conant, G. C., Hagen, D. E., & Elsik, C. G. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz944 · Cited by 36
“We have added several new ontologies, including Vertebrate Trait Ontology (46), Evidence Code Ontology (47), Uberon Anatomy Ontology (48), Protein–Protein Interaction and Molecular Interaction Ontology (49), Livestock Breed Ontology (https: //www.animalgenome.org/bioinfo/projects/lbo/) and…”
COPO: a metadata platform for brokering FAIR data in the life sciences
Shaw, F., Etuk, A., Minotto, A., Gonzalez-Beltran, A. N., Johnson, D., Rocca‐Serra, P., Laporte, M., Arnaud, E., Devare, M., Kersey, P. J., et al. (2020) · F1000Research · doi:10.12688/f1000research.23889.1 · Cited by 36
Background knowledge in ontology matching: A survey
Portisch, J., Hladik, M., & Paulheim, H. (2022) · Semantic Web · doi:10.3233/sw-223085 · Cited by 43
“UMLS can be used without charge but a download 23 requires a registration at the NLM. UBERON In the anatomy domain, the Uber-anatomy ontology (UBERON) [161, 162] is an ontology for multiple species comprising of more than 13,000 classes (as of 2021).”
MethodTarget-driven merging of taxonomies with Atom
Raunich, S., & Rahm, E. (2013) · Information Systems · doi:10.1016/j.is.2013.11.001 · Cited by 35
Biomedical discovery through the integrative biomedical knowledge hub (iBKH)
Su, C., Hou, Y., Zhou, M., Rajendran, S., Maasch, J. R. M. A., Abedi, Z., Zhang, H., Bai, Z., Cuturrufo, A., Guo, W. L., et al. (2023) · iScience · doi:10.1016/j.isci.2023.106460 · Cited by 37
“For anatomy entity type, we used the Uberon (Mungall et al., 2012) for initializing the vocabulary, as it is a cross-species anatomical ontology based on traditional anatomical classification.”
BackgroundMethodInfluentialGreenfest‐Allen, E., Valladares, O., Kuksa, P. P., Gangadharan, P., Lee, W., Cifello, J., Katanić, Ž., Kuzma, A. B., Wheeler, N. R., Bush, W. S., et al. (2023) · Alzheimer s & Dementia · doi:10.1002/alz.13509 · Cited by 32
Evaluating phenotype-driven approaches for genetic diagnoses from exomes in a clinical setting
Pengelly, R. J., Alom, T., Zhang, Z., Hunt, D., Ennis, S., & Collins, A. R. (2017) · Scientific Reports · doi:10.1038/s41598-017-13841-y · Cited by 35
“Different ontologies are considered which integrate human and model organism data including: Gene Ontology 19 , HPO 14 , Uberon 20 , Disease Ontology 21 and The Pathway Ontology 22 .”
BackgroundTen Simple Rules for Selecting a Bio-ontology
MALONE, J. M., Stevens, R., Jupp, S., Hancocks, T., Parkinson, H., & Brooksbank, C. (2016) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1004743 · Cited by 35
“These ontologies cover areas such as diseases [6], phenotypes [7], anatomy [8], experimental conditions [9,10], cell types [11], and bioinformatics software [12].”
An ontology-based knowledge graph for representing interactions involving RNA molecules
Cavalleri, E., Cabri, A., Soto-Gomez, M., Bonfitto, S., Perlasca, P., Gliozzo, J., Callahan, T. J., Reese, J., Robinson, P. N., Casiraghi, E., et al. (2024) · Scientific Data · doi:10.1038/s41597-024-03673-7 · Cited by 33
Integrating phenotype ontologies with PhenomeNET
Rodríguez‐García, M. Á., Gkoutos, G. V., Schofield, P. N., & Hoehndorf, R. (2017) · Journal of Biomedical Semantics · doi:10.1186/s13326-017-0167-4 · Cited by 33
“AML can further make use of exter-nal resources such as DO, UBERON, MeSH and Wordnet, which provide background knowledge to improve the generation of mappings, and AML further provides methods for identifying and repairing incoherent matches between two ontologies.”
InfluentialDavis, A. P., Wiegers, T. C., Wiegers, J., Grondin, C., Johnson, R. J., Sciaky, D., & Mattingly, C. J. (2021) · Current Research in Toxicology · doi:10.1016/j.crtox.2021.03.001 · Cited by 33
Spatial architecture of development and disease
Lázár, E., & Lundeberg, J. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00892-5 · Cited by 38
“…latter, such as HuBMAP 168 and the Human Cell Atlas 37 , have developed 3D anatomical reference models and used accompanying ontologies, such as ASCT + B tables 169 and Uberon 170 , to facilitate consistent annotation and registration of multimodal data using anatomical landmarks and semantic tags.”
Cross‐organism analysis using InterMine
Lyne, R., Sullivan, J. M., Butano, D., Contrino, S., Heimbach, J., Hu, F., Kalderimis, A., Lyne, M., Smith, R. N., Štěpán, R., et al. (2015) · genesis · doi:10.1002/dvg.22869 · Cited by 32
Towards Responsible Plant Data Linkage: Data Challenges for Agricultural Research and Development
Williamson, H. F., & Leonelli, S. (2022) · Springer eBooks · doi:10.1007/978-3-031-13276-6 · Cited by 35
Semi-automatic Adaptation of Mappings between Life Science Ontologies
Groß, A., dos Reis, J. C., Hartung, M., Pruski, C., & Rahm, E. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-39437-9_8 · Cited by 32
“For instance, mappings are needed to merge several ontologies into an integrated ontology, e.g., the multispecies anatomy ontology Uberon [4].”
Cornish, A. J., Filippis, I., David, A., & Sternberg, M. J. E. (2015) · Genome Medicine · doi:10.1186/s13073-015-0212-9 · Cited by 30
“If a MeSH term did not contain sufficient anatomical information to differentiate the facet or sub-facet from others, then we used the Uberon anatomical ontology [33], which is also cross-referenced in FF.”
MethodTassy, O., & Pourquié, O. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt807 · Cited by 31
“The correspondence between terms from FMA and MA are found using the Uber-anatomy ontology [UBERON (12)].”
MethodUpdates to BioSamples database at European Bioinformatics Institute
Faulconbridge, A., Burdett, T., Brandizi, M., Gostev, M., Pereira, R. P., Vasant, D., Sarkans, U., Brāzma, A., & Parkinson, H. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1081 · Cited by 31
“EFO has been expanded in parallel to support BioSamples use cases, including an import of a ‘SLIM’ of the Uber Anatomy Ontology Uberon (10) and a genetic disease classification from Orphanet (11).”
Method
Metadata
- Authors
- Mungall, C. J., Torniai, C., Gkoutos, G. V., Lewis, S. E., & Haendel, M. A.
- Affiliations
- Oregon Health & Science University (US)
- University of Cambridge (GB)
- Lawrence Berkeley National Laboratory (US)
- Venue
- Genome biology
- Published
- 2012-01-31
- Volume
- 13
- Issue
- 1
- Pages
- R5-R5
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC3334586
- OpenAlex
- W2116034137
- Cited by
- 732
- References
- 67
- Citations by year
- 2026: 60 · 2025: 69 · 2024: 55 · 2023: 66 · 2022: 55 · 2021: 51 · 2020: 46 · 2019: 45 · 2018: 55 · 2017: 46 · 2016: 49 · 2015: 50 · 2014: 34 · 2013: 28 · 2012: 21
- FWCI
- 17.73
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) (submittedVersion)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Funders
- U.S. Department of Energy (-AC02-05CH11231, 05CH11231, DE AC02 05CH11231, DE-AC02-)
- National Institutes of Health (2p41hg002273-07, 5u24rr029825-02, DE-AC02–05CH11231)
- Office of Science (DEAC02–05CH11231, AC02-05CH11231, DE-AC02, 05CH11231)
- National Human Genome Research Institute (U41HG002273, R01HG004838, P41HG002273-09S1, P41-HG002273)
- National Center for Research Resources (1U24RR029825-01)
- Basic Energy Sciences (DE-AC02, DE-AC02-05CH11231., AC02–05CH11231)
- Topics
- Health Sciences › Medicine › Health Informatics › Biomedical Text Mining and Ontologies
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- UBERON, anatomy ontology, anatomical classification, taxonomic variation, human anatomy
- MeSH terms
- Anatomy, Comparative, Classification, Humans, Phenotype, Software, Species Specificity, Databases, Factual, Computational Biology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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