Zoeken
Zoeken kan via de modus 'eenvoudig zoeken' (één veld) of uitgebreid via 'geavanceerd zoeken' (meerdere velden). Zo kan je bv. zoeken op een combinatie van een auteursnaam (auteur), een jaartal (jaar) en een documenttype.
Boekenmand
Nuttige resultaten kan je aanvinken en toevoegen aan een mandje. De inhoud hiervan kan je exporteren of afdrukken (naar bv. PDF).
RSS
Op de hoogte blijven van nieuw toegevoegde publicaties binnen uw interessegebied? Dit kan door een RSS-feed (?) te maken van jouw zoekopdracht.
nieuwe zoekopdracht
The Ontology of Biological Attributes (OBA) - computational traits for the life sciences
Stefancsik, R.; Balhoff, J.P.; Balk, M.A.; Ball, R.L.; Bello, S.M.; Caron, A.R.; Chesler, E.J.; de Souza, V.; Gehrke, S.; Haendel, M.; Harris, L.W.; Harris, N.L.; Ibrahim, A.; Koehler, S.; Matentzoglu, N.; McMurry, J.A.; Mungall, C.J.; Munoz-Torres, M.C.; Putman, T.; Robinson, P.; Smedley, D.; Sollis, E.; Thessen, A.E.; Vasilevsky, N.; Walton, D.O.; Osumi-Sutherland, D. (2023). The Ontology of Biological Attributes (OBA) - computational traits for the life sciences. Mammalian Genome 34(3): 364-378. https://dx.doi.org/10.1007/s00335-023-09992-1
In: Mammalian Genome. Springer: New York. ISSN 0938-8990; e-ISSN 1432-1777
|   |
| Auteurs | | Top |
- Stefancsik, R.
- Balhoff, J.P.
- Balk, M.A.
- Ball, R.L.
- Bello, S.M.
- Caron, A.R.
- Chesler, E.J.
- de Souza, V.
- Gehrke, S.
|
- Haendel, M.
- Harris, L.W.
- Harris, N.L.
- Ibrahim, A.
- Koehler, S.
- Matentzoglu, N.
- McMurry, J.A.
- Mungall, C.J.
- Munoz-Torres, M.C.
|
- Putman, T.
- Robinson, P.
- Smedley, D.
- Sollis, E.
- Thessen, A.E.
- Vasilevsky, N.
- Walton, D.O.
- Osumi-Sutherland, D.
|
| 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. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.
