Nimrod Megiddo
Journal of Symbolic Computation
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.
Nimrod Megiddo
Journal of Symbolic Computation
Moutaz Fakhry, Yuri Granik, et al.
SPIE Photomask Technology + EUV Lithography 2011
Donald Samuels, Ian Stobert
SPIE Photomask Technology + EUV Lithography 2007
Juliann Opitz, Robert D. Allen, et al.
Microlithography 1998