Uberon
Integrated cross-species ontology covering anatomical structures in animals
Uberon is a comprehensive, cross-species ontology that encompasses anatomical structures in a wide range of animals, including vertebrates and invertebrates. It is designed to facilitate the integration and comparison of anatomical data across different species, supporting research in comparative anatomy, evolutionary biology, and biomedical research.
Overview[edit | edit source]
Uberon provides a unified framework for representing anatomical entities, enabling researchers to map and compare anatomical structures across species. This ontology includes terms for organs, tissues, and cell types, and it is used in conjunction with other ontologies such as the Gene Ontology and the Cell Ontology.
The ontology is structured to support queries about anatomical structures, their relationships, and their developmental origins. It is particularly useful for studies involving model organisms, where researchers need to translate findings from one species to another.
Development and Maintenance[edit | edit source]
Uberon is developed and maintained by a collaborative team of researchers and ontology developers. The project is open-source, allowing contributions from the scientific community to enhance its coverage and accuracy. The ontology is regularly updated to incorporate new findings and to refine existing entries.
Applications[edit | edit source]
Uberon is widely used in various fields of biological research. In comparative genomics, it helps in identifying homologous structures across species, facilitating the study of evolutionary relationships. In biomedical research, Uberon supports the annotation of phenotypic data, aiding in the understanding of disease mechanisms and the development of new therapies.
Integration with Other Ontologies[edit | edit source]
Uberon is part of a larger ecosystem of biological ontologies, including the Phenotype and Trait Ontology (PATO) and the Experimental Factor Ontology (EFO). These ontologies are interconnected, allowing for comprehensive data integration and analysis across different biological domains.
Related pages[edit | edit source]
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Contributors: Prab R. Tumpati, MD
