Dataset Information

Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon.

ABSTRACT: BACKGROUND:Elucidating disease and developmental dysfunction requires understanding variation in phenotype. Single-species model organism anatomy ontologies (ssAOs) have been established to represent this variation. Multi-species anatomy ontologies (msAOs; vertebrate skeletal, vertebrate homologous, teleost, amphibian AOs) have been developed to represent 'natural' phenotypic variation across species. Our aim has been to integrate ssAOs and msAOs for various purposes, including establishing links between phenotypic variation and candidate genes. RESULTS:Previously, msAOs contained a mixture of unique and overlapping content. This hampered integration and coordination due to the need to maintain cross-references or inter-ontology equivalence axioms to the ssAOs, or to perform large-scale obsolescence and modular import. Here we present the unification of anatomy ontologies into Uberon, a single ontology resource that enables interoperability among disparate data and research groups. As a consequence, independent development of TAO, VSAO, AAO, and vHOG has been discontinued. CONCLUSIONS:The newly broadened Uberon ontology is a unified cross-taxon resource for metazoans (animals) that has been substantially expanded to include a broad diversity of vertebrate anatomical structures, permitting reasoning across anatomical variation in extinct and extant taxa. Uberon is a core resource that supports single- and cross-species queries for candidate genes using annotations for phenotypes from the systematics, biodiversity, medical, and model organism communities, while also providing entities for logical definitions in the Cell and Gene Ontologies. THE ONTOLOGY RELEASE FILES ASSOCIATED WITH THE ONTOLOGY MERGE DESCRIBED IN THIS MANUSCRIPT ARE AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/2013-02-21/ CURRENT ONTOLOGY RELEASE FILES ARE AVAILABLE ALWAYS AVAILABLE AT: http://purl.obolibrary.org/obo/uberon/releases/

SUBMITTER: Haendel MA

PROVIDER: S-EPMC4089931 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background In times of exponential data growth in the life sciences, machine-supported approaches are becoming increasingly important and with them the need for FAIR (Findable, Accessible, Interoperable, Reusable) and eScience-compliant data and metadata standards. Ontologies, with their queryable knowledge resources, play an essential role in providing these standards. Unfortunately, biomedical ontologies only provide ontological definitions that answer What is it? questions, but no method-dependent empirical recognition criteria that answer How does it look? questions. Consequently, biomedical ontologies contain knowledge of the underlying ontological nature of structural kinds, but often lack sufficient diagnostic knowledge to unambiguously determine the reference of a term. Results We argue that this is because ontology terms are usually textually defined and conceived as essentialistic classes, while recognition criteria often require perception-based definitions because perception-based contents more efficiently document and communicate spatial and temporal information—a picture is worth a thousand words. Therefore, diagnostic knowledge often must be conceived as cluster classes or fuzzy sets. Using several examples from anatomy, we point out the importance of diagnostic knowledge in anatomical research and discuss the role of cluster classes and fuzzy sets as concepts of grouping needed in anatomy ontologies in addition to essentialistic classes. In this context, we evaluate the role of the biological type concept and discuss its function as a general container concept for groupings not covered by the essentialistic class concept. Conclusions We conclude that many recognition criteria can be conceptualized as text-based cluster classes that use terms that are in turn based on perception-based fuzzy set concepts. Finally, we point out that only if biomedical ontologies model also relevant diagnostic knowledge in addition to ontological knowledge, they will fully realize their potential and contribute even more substantially to the establishment of FAIR and eScience-compliant data and metadata standards in the life sciences. Supplementary Information The online version contains supplementary material available at 10.1186/s13326-022-00268-2.

Project description:Core concepts offer coherence to the discourse of a scientific discipline and facilitate teaching by identifying large unifying themes that can be tailored to the level of the class and expertise of the instructor. This approach to teaching has been shown to encourage deeper learning that can be integrated across subdisciplines of biology and has been adopted by several other biology subdisciplines. However, Comparative Vertebrate Anatomy, although one of the oldest biological areas of study, has not had its core concepts identified. Here, we present five core concepts and seven competencies (skills) for Comparative Vertebrate Anatomy that came out of an iterative process of engagement with the broader community of vertebrate morphologists over a 3-year period. The core concepts are (A) evolution, (B) structure and function, (C) morphological development, (D) integration, and (E) human anatomy is the result of vertebrate evolution. The core competencies students should gain from the study of comparative vertebrate anatomy are (F) tree thinking, (G) observation, (H) dissection of specimens, (I) depiction of anatomy, (J) appreciation of the importance of natural history collections, (K) science communication, and (L) data integration. We offer a succinct description of each core concept and competency, examples of learning outcomes that could be used to assess teaching effectiveness, and examples of relevant resources for both instructors and students. Additionally, we pose a grand challenge to the community, arguing that the field of Comparative Vertebrate Anatomy needs to acknowledge racism, androcentrism, homophobia, genocide, slavery, and other influences in its history and address their lingering effects in order to move forward as a thriving discipline that is inclusive of all students and scientists and continues to generate unbiased knowledge for the betterment of humanity. Despite the rigorous process used to compile these core concepts and competencies, we anticipate that they will serve as a framework for an ongoing conversation that ensures Comparative Vertebrate Anatomy remains a relevant field in discovery, innovation, and training of future generations of scientists.

Dataset Information

Unification of multi-species vertebrate anatomy ontologies for comparative biology in Uberon.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets