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Development and validation of a reliable DNA copy-number-based machine learning algorithm (CopyClust) for breast cancer integrative cluster classification

Crossref DOI link: https://doi.org/10.1038/s41598-024-62724-6

Published Online: 2024-05-24

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Young, Cameron C.

Eason, Katherine

Manzano Garcia, Raquel

Moulange, Richard

Mukherjee, Sach

Chin, Suet-Feung

Caldas, Carlos

Rueda, Oscar M.
Funding

Funding for this research was provided by:

Cancer Research UK (Caldas Core Grant A16942 and CRUK Cambridge Institute Core Grant A29580)

Horizon 2020 (ERC-2015-AdG-694620)

NIHR Cambridge Biomedical Research Centre (BRC-1215-20014)

Medical Research Council (MC_UU_00002/16)
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Text and Data Mining valid from 2024-05-24

Version of Record valid from 2024-05-24
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Article History

Received: 6 February 2024

Accepted: 21 May 2024

First Online: 24 May 2024

Competing interests

: C.C. is a member of the iMED External Science Panel for AstraZeneca, the Scientific Advisory Board for Illumina, and is a recipient of research grants (administered by the University of Cambridge) from AstraZeneca, Genentech, Roche, and Servier. The remaining authors declare no competing interests.

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