Moutaz Fakhry, Yuri Granik, et al.
SPIE Photomask Technology + EUV Lithography 2011
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.
Moutaz Fakhry, Yuri Granik, et al.
SPIE Photomask Technology + EUV Lithography 2011
James Lee Hafner
Journal of Number Theory
Sonia Cafieri, Jon Lee, et al.
Journal of Global Optimization
John A. Hoffnagle, William D. Hinsberg, et al.
Microlithography 2003