ArticleMammalian genome : official journal of the International Mammalian Genome Society2023
The Ontology of Biological Attributes (OBA)-computational traits for the life sciences.
Article in Mammalian genome : official journal of the International Mammalian Genome Society, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis.Genome research · 2024Pooled it
- Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.Mammalian genome : official journal of the International Mammalian Genome Society · 2023Pooled it
- AI semantics for biomedical data integration.bioRxiv : the preprint server for biology · 2026Article
- The Cell Ontology in the age of single-cell omics.Scientific data · 2026Article
- Mondo: integrating disease terminology across communities.Genetics · 2026Article
- Extending mammal specimens with their essential phenotypic traits.Journal of mammalogy · 2025Article
- Article
- The Unified Phenotype Ontology : a framework for cross-species integrative phenomics.Genetics · 2025Article
- Using a units ontology to annotate pre-existing metadata.Scientific data · 2025Article
- The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity.Nucleic acids research · 2025Article
- The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity.bioRxiv : the preprint server for biology · 2024Article
- Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI).Journal of biomedical semantics · 2024Article
- The Unified Phenotype Ontology (uPheno): A framework for cross-species integrative phenomics.bioRxiv : the preprint server for biology · 2024Article
- The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.Nucleic acids research · 2024Article
- The Human Phenotype Ontology in 2024: phenotypes around the world.Nucleic acids research · 2024Article
- TermGenie - a web-application for pattern-based ontology class generation.Journal of biomedical semantics · 2014Article
- The Vertebrate Breed Ontology: Toward Effective Breed Data Standardization.Journal of veterinary internal medicineArticle
Corrections and comments
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Authors and funding
26 authors.
Funding
Abstract
Existing phenotype ontologies were originally developed to represent phenotypes that manifest as a character state in relation to a wild-type or other reference. However, these do not include the phenotypic trait or attribute categories required for the annotation of genome-wide association studies (GWAS), Quantitative Trait Loci (QTL) mappings or any population-focussed measurable trait data. The integration of trait and biological attribute information with an ever increasing body of chemical, environmental and biological data greatly facilitates computational analyses and it is also highly relevant to biomedical and clinical applications. The Ontology of Biological Attributes (OBA) is a formalised, species-independent collection of interoperable phenotypic trait categories that is intended to fulfil a data integration role. OBA is a standardised representational framework for observable attributes that are characteristics of biological entities, organisms, or parts of organisms. OBA has a modular design which provides several benefits for users and data integrators, including an automated and meaningful classification of trait terms computed on the basis of logical inferences drawn from domain-specific ontologies for cells, anatomical and other relevant entities. The logical axioms in OBA also provide a previously missing bridge that can computationally link Mendelian phenotypes with GWAS and quantitative traits. The term components in OBA provide semantic links and enable knowledge and data integration across specialised research community boundaries, thereby breaking silos.
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What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.