cancercelllines.org-a novel resource for genomic variants in cancer cell lines.


Journal

Database : the journal of biological databases and curation
ISSN: 1758-0463
Titre abrégé: Database (Oxford)
Pays: England
ID NLM: 101517697

Informations de publication

Date de publication:
30 Apr 2024
Historique:
accepted: 27 03 2024
revised: 19 02 2024
received: 07 12 2023
medline: 30 4 2024
pubmed: 30 4 2024
entrez: 30 4 2024
Statut: ppublish

Résumé

Cancer cell lines are an important component in biological and medical research, enabling studies of cellular mechanisms as well as the development and testing of pharmaceuticals. Genomic alterations in cancer cell lines are widely studied as models for oncogenetic events and are represented in a wide range of primary resources. We have created a comprehensive, curated knowledge resource-cancercelllines.org-with the aim to enable easy access to genomic profiling data in cancer cell lines, curated from a variety of resources and integrating both copy number and single nucleotide variants data. We have gathered over 5600 copy number profiles as well as single nucleotide variant annotations for 16 000 cell lines and provide these data with mappings to the GRCh38 reference genome. Both genomic variations and associated curated metadata can be queried through the GA4GH Beacon v2 Application Programming Interface (API) and a graphical user interface with extensive data retrieval enabled using GA4GH data schemas under a permissive licensing scheme. Database URL: https://cancercelllines.org.

Identifiants

pubmed: 38687868
pii: 7660350
doi: 10.1093/database/baae030
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

© The Author(s) 2024. Published by Oxford University Press.

Auteurs

Rahel Paloots (R)

Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland.
Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland.

Michael Baudis (M)

Institute of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich 8057, Switzerland.
Swiss Institute of Bioinformatics, Winterthurerstrasse 190, Zurich 8057, Switzerland.

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Classifications MeSH