A. Skumanich
SPIE OE/LASE 1992
Colorectal cancer (CRC) benefits from a multi-omics-based stratification in the context of survival. Our TCGA-based study employs targeted feature selection and unsupervised clustering to stratify patients based on disease-specific survival, identifying an event-free subgroup undetectable with unimodal data or established consensus molecular subtypes. An analysis of variance and gene set enrichment coupled with clinical characterisation of the clusters reveal findings that support multi-omics-driven precision medicine in CRC.
A. Skumanich
SPIE OE/LASE 1992
John R. Kender, Rick Kjeldsen
IEEE Transactions on Pattern Analysis and Machine Intelligence
Charles Micchelli
Journal of Approximation Theory
Ziv Bar-Yossef, T.S. Jayram, et al.
Journal of Computer and System Sciences