A simulation to analyze feature selection methods utilizing gene ontology for gene expression classification.

Gene expression profile classification is a pivotal research domain assisting in the transformation from traditional to personalized medicine. A major challenge associated with gene expression data classification is the small number of samples relative to the large number of genes. To address this problem, researchers have devised various feature selection algorithms to reduce the number of genes.

Expression of the tumor suppressor Krüppel-like factor 4 as a prognostic predictor for colon cancer.

Background: The zinc finger transcription factor Krüppel-like factor 4 (KLF4) regulates numerous physiologic processes, including proliferation, differentiation, and development. Studies also showed that KLF4 is involved in tumorigenesis and somatic cell reprogramming. Here, we aimed to assess whether KLF4 is a prognostic indicator for colon cancer.

Krüppel-like factor 5 is a crucial mediator of intestinal tumorigenesis in mice harboring combined ApcMin and KRASV12 mutations.

Background: Both mutational inactivation of the adenomatous polyposis coli (APC) tumor suppressor gene and activation of the KRAS oncogene are implicated in the pathogenesis of colorectal cancer. Mice harboring a germline ApcMin mutation or intestine-specific expression of the KRASV12 gene have been developed. Both mouse strains develop spontaneous intestinal tumors, including adenoma and carcinoma, though at a different age.