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A cell-to-patient machine learning transfer approach uncovers novel basal-like breast cancer prognostic markers amongst alternative splice variants

Published Online: 2021-04-12

Published Print: 2021-12

Authors

Villemin, Jean-Philippe

Lorenzi, Claudio

Cabrillac, Marie-Sarah

Oldfield, Andrew

Ritchie, William

Luco, Reini F. https://orcid.org/0000-0002-9086-6507
Funding

Funding for this research was provided by:

Agence Nationale de la Recherche

LabEx EpiGenMed
License Information

Text and Data Mining valid from 2021-04-12

Version of Record valid from 2021-04-12
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Article History

Received: 13 November 2020

Accepted: 9 March 2021

First Online: 12 April 2021

Declarations

:

: Patients data was obtained from The Cancer Genome Atlas upon agreement of TCGA ethics and policies ()

: All patients gave consent for publication of their personal information.

: The authors declare no competing interests.

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