Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.

ABSTRACT: This retrospective transcriptomic study leveraged bioinformatics and machine learning algorithms to identify novel gene biomarkers and explore immune cell infiltration profiles associated with chronic obstructive pulmonary disease (COPD). Utilizing an integrated analysis of metadata encompassing six gene expression omnibus (GEO) microarray datasets, 987 differentially expressed genes were identified. Further gene ontology and pathway enrichment analyses revealed the enrichment of these genes across various biological processes and pathways. Moreover, a systematic integration of two machine learning algorithms along with pathway-gene correlations identified six candidate biomarkers, which were validated in a separate cohort comprising six additional microarray datasets, ultimately identifyi

SUBMITTER: Zhu Z 

PROVIDER: S-EPMC11440088 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature