The SIB Swiss Institute of Bioinformatics Semantic Web of data.

Details

Serval ID
serval:BIB_A29FECE3B301
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
The SIB Swiss Institute of Bioinformatics Semantic Web of data.
Journal
Nucleic acids research
Author(s)
Mendes de Farias T.
Working group(s)
SIB Swiss Institute of Bioinformatics RDF Group Members
Contributor(s)
Zdobnov E., Altenhoff A., Bairoch A., Bansal P., Baratin D., Bastian F., Bolleman J., Bridge A., Burdet F., Crameri K., Dauvillier J., Dessimoz C., Gehant S., Glover N., Gnodtke K., Hayes C., Ibberson M., Kriventseva E., Kuznetsov D., Frédérique L., Mehl F., Michel P.A., Moretti S., Morgat A., Österle S., Pagni M., Redaschi N., Robinson-Rechavi M., Samarasinghe K., Sima A.C., Szklarczyk D., Topalov O., Touré V., Unni D., von Mering C., Wollbrett J., Zahn-Zabal M.
ISSN
1362-4962 (Electronic)
ISSN-L
0305-1048
Publication state
Published
Issued date
05/01/2024
Peer-reviewed
Oui
Volume
52
Number
D1
Pages
D44-D51
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Abstract
The SIB Swiss Institute of Bioinformatics (https://www.sib.swiss/) is a federation of bioinformatics research and service groups. The international life science community in academia and industry has been accessing the freely available databases provided by SIB since its inception in 1998. In this paper we present the 11 databases which currently offer semantically enriched data in accordance with the FAIR principles (Findable, Accessible, Interoperable, Reusable), as well as the Swiss Personalized Health Network initiative (SPHN) which also employs this enrichment. The semantic enrichment facilitates the manipulation of large data sets from public databases and private data sets. Examples are provided to illustrate that the data from the SIB databases can not only be queried using precise criteria individually, but also across multiple databases, including a variety of non-SIB databases. Data manipulation, be it exploration, extraction, annotation, combination, and publication, is possible using the SPARQL query language. Providing documentation, tutorials and sample queries makes it easier to navigate this web of semantic data. Through this paper, the reader will discover how the existing SIB knowledge graphs can be leveraged to tackle the complex biological or clinical questions that are being addressed today.
Keywords
Computational Biology, Databases, Factual, Semantic Web, Switzerland, Humans
Pubmed
Web of science
Open Access
Yes
Create date
05/12/2023 16:30
Last modification date
07/03/2024 8:13
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