=Paper=
{{Paper
|id=Vol-3939/abstract3
|storemode=property
|title=Standardising Biological Trait Representation with the Ontology of Biological
						Attributes (OBA)
|pdfUrl=https://ceur-ws.org/Vol-3939/abstract3.pdf
|volume=Vol-3939
|authors=Arwa Ibrahim,Ray Stefancsik,Vinicius de Souza,Anita R. Caron,Nicolas Matentzoglu,James McLaughlin, Zoë M. Pendlington
|dblpUrl=https://dblp.org/rec/conf/icbo/IbrahimSSCMMP24
}}
==Standardising Biological Trait Representation with the Ontology of Biological
						Attributes (OBA)==
<pdf width="1500px">https://ceur-ws.org/Vol-3939/abstract3.pdf</pdf>
<pre>
                         Standardising biological trait representation with the
                         Ontology of Biological Attributes (OBA) – Abstract
                         Arwa Ibrahim1,∗ , Ray Stefancsik1 , Vinicius de Souza1 , Anita R. Caron1 , Nicolas Matentzoglu2 ,
                         James McLaughlin1 and Zoë M. Pendlington1
                         1
                             European Bioinformatics Institute (EMBL-EBI), Hinxton, Cambridgeshire CB10 1SD, UK
                         2
                             Semanticly, Athens, Greece


                                        Abstract
                                        The Ontology of Biological Attributes (OBA) is a standardised, species-independent, computationally-amenable
                                        representation of phenotype traits relevant to biological, clinical, environmental and life science applications.
                                        While many current phenotype ontologies describe abnormal phenotypes relative to some wild-type state,
                                        OBA represents neutral traits or attributes. OBA has a central data integration role and employs Dead Simple
                                        Ontology Design Patterns (DOS-DPs) templates for the automated classification of traits, drawing on terms
                                        from domain-specific reference ontologies in a post-compositional approach. This computation based on logical
                                        inferences and automated reasoners promotes interoperability as multiple links to these ontologies enables
                                        powerful querying, knowledge graph integration and inference. In addition, due to its rich axiomatisation, a
                                        central OBA use case is to provide structure to weakly axiomatised ontologies like the Vertebrate Ontology (VT)
                                        and the Experimental Factor Ontology (EFO). The logical axioms in OBA provide a previously missing bridge that
                                        can link Mendelian phenotypes with genome-wide association studies (GWAS) and measurable traits. The GWAS
                                        Catalog incorporates EFO in its curation workflows and there is an ongoing OBA mapping effort of the EFO
                                        measurement branch. The Open Targets Platform, which identifies potential therapeutic drug targets, is a major
                                        consumer of GWAS data, so OBA classes imported into EFO can facilitate computational drug target identification.
                                        Also, there is an increasing demand from the GWAS Catalog for new trait terms to annotate summary statistics
                                        sometimes containing hundreds or thousands of GWAS studies. The template-based curation workflow of OBA
                                        means that the addition of new terms is highly scalable which is important in the context of the generation
                                        of large amounts of scientific data, reducing the need for manual curation and eliminating human error. OBA
                                        is a component of the Unified Phenotype Ontology (uPheno 2) and this integration allows for the grouping of
                                        phenotypic effects across biological attributes. It is an Open Biological and Biomedical Ontologies (OBO) Foundry
                                        compliant ontology and uses the Ontology Development Kit (ODK) to run releases, quality control checks and
                                        external dependencies. It currently uses eleven DOS-DP templates that cover many anatomical, metabolite and
                                        cellular attributes needed for data integration with the possibility to expand based on stakeholder and community
                                        use cases.

                                        Keywords
                                        OBO ontologies, traits, attributes, phenotypes, ontology design patterns, DOS-DP, data integration, interoperabil-
                                        ity, mappings




                         15th International Conference on Biomedical Ontologies 2024, July 17-19, 2024, Enschede, The Netherlands
                         ∗
                             Corresponding author.
                         Envelope-Open aibrahim@ebi.ac.uk (A. Ibrahim); stefancsik@ebi.ac.uk (R. Stefancsik); vinicius@ebi.ac.uk (V. d. Souza); anitac@ebi.ac.uk
                         (A. R. Caron); nicolas.matentzoglu@gmail.com (N. Matentzoglu); jmcl@ebi.ac.uk (J. McLaughlin); zmp@ebi.ac.uk
                         (Z. M. Pendlington)
                         Orcid 0000-0001-6757-4744 (A. Ibrahim); 0000-0001-8314-2140 (R. Stefancsik); 0000-0003-3961-0247 (V. d. Souza);
                         0000-0002-6523-4866 (A. R. Caron); 0000-0002-7356-1779 (N. Matentzoglu); 0000-0002-8361-2795 (J. McLaughlin);
                         0000-0002-4071-8397 (Z. M. Pendlington)
                                       © 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).


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