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SyntheVAEiser: augmenting traditional machine learning methods with VAE-based gene expression sample generation for improved cancer subtype predictions

Crossref DOI link: https://doi.org/10.1186/s13059-024-03431-3

Published Online: 2024-12-18

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

Authors

Karlberg, Brian https://orcid.org/0000-0002-7587-7849
Kirchgaessner, Raphael https://orcid.org/0000-0002-2937-6904
Lee, Jordan https://orcid.org/0000-0002-0983-0495
Peterkort, Matthew https://orcid.org/0009-0004-7313-826X
Beckman, Liam https://orcid.org/0009-0008-4585-9181
Goecks, Jeremy https://orcid.org/0000-0002-4583-5226
Ellrott, Kyle https://orcid.org/0000-0002-6573-5900
License Information

Text and Data Mining valid from 2024-12-18

Version of Record valid from 2024-12-18
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Article History

Received: 11 October 2023

Accepted: 30 October 2024

First Online: 18 December 2024

Declarations

:

: N/A.

: N/A.