Journal article
Development and validation of asthma risk prediction models using co-expression gene modules and machine learning methods
Abstract
Asthma is a heterogeneous respiratory disease characterized by airway inflammation and obstruction. Despite recent advances, the genetic regulation of asthma pathogenesis is still largely unknown. Gene expression profiling techniques are well suited to study complex diseases including asthma. In this study, differentially expressed genes (DEGs) followed by weighted gene co-expression network analysis (WGCNA) and machine learning techniques …
Authors
Dessie EY; Gautam Y; Ding L; Altaye M; Beyene J; Mersha TB
Journal
Scientific Reports, Vol. 13, No. 1,
Publisher
Springer Nature
DOI
10.1038/s41598-023-35866-2
ISSN
2045-2322