Serviceeinschränkungen vom 12.-22.02.2026 - weitere Infos auf der UB-Homepage

Treffer: Ontology based document enrichment in bioinformatics : Data integration in functional genomics and proteomics

Title:
Ontology based document enrichment in bioinformatics : Data integration in functional genomics and proteomics
Authors:
Source:
Comparative and functional genomics. 3(1):42-46
Publisher Information:
Chichester: Wiley, 2002.
Publication Year:
2002
Physical Description:
print, 9 ref
Original Material:
LGMI
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
ISSN:
1531-6912
Rights:
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Biological sciences. Generalities. Modelling. Methods

Generalities in biological sciences
Accession Number:
edscal.14477127
Database:
PASCAL Archive

Weitere Informationen

Controlled vocabularies are common within bioinformatics resources. They can be used to give a summary of the knowledge held about a particular entity. They are also used to constrain values given for particular attributes of an entity. This helps create a shared understanding of a domain and aids increased precision and recall during querying of resources. Ontologies can also provide such facilities, but can also enhance their utility. Controlled vocabularies are often simply lists of words, but may be viewed as a kind of ontology. Ideally ontologies are structurally enriched with relationships between terms within the vocabulary. Use of such rich forms of vocabularies in database annotation could enhance those resources usability by both humans and computers. The representation of the knowledge content of biological resources in a computationally accessible form opens the prospect of greater support for a biologist investigating new data.