Label propagation-based semi-supervised feature selection on decoding clinical phenotypes with RNA-seq data.

ABSTRACT:

Background

Clinically, behavior, cognitive, and mental functions are affected during the neurodegenerative disease progression. To date, the molecular pathogenesis of these complex disease is still unclear. With the rapid development of sequencing technologies, it is possible to delicately decode the molecular mechanisms corresponding to different clinical phenotypes at the genome-wide transcriptomic level using computational methods. Our previous studies have shown that it is difficult to distinguish disease genes from non-disease genes. Therefore, to precisely explore the molecular pathogenesis under complex clinical phenotypes, it is better to identify biomarkers corresponding to different disease stages or clinical phenotypes. So, in this study, we designed a label propagation-

SUBMITTER: Jiang X 

PROVIDER: S-EPMC8406783 | biostudies-literature | 2021 Aug

REPOSITORIES: biostudies-literature