Building a model for predicting metabolic syndrome using artificial intelligence based on an investigation of whole-genome sequencing.

ABSTRACT:

Background

The circadian system is responsible for regulating various physiological activities and behaviors and has been gaining recognition. The circadian rhythm is adjusted in a 24-h cycle and has transcriptional-translational feedback loops. When the circadian rhythm is interrupted, affecting the expression of circadian genes, the phenotypes of diseases could amplify. For example, the importance of maintaining the internal temporal homeostasis conferred by the circadian system is revealed as mutations in genes coding for core components of the clock result in diseases. This study will investigate the association between circadian genes and metabolic syndromes in a Taiwanese population.

Methods

We performed analysis using whole-genome sequencing, read vcf files and set ta

SUBMITTER: Hsu NW 

PROVIDER: S-EPMC9052619 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature