ArticleJournal of cellular and molecular medicine2024
Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.
Article in Journal of cellular and molecular medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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The trial behind it
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Who cites it
9 citing papers in PubMed.
- Discovering potential key biomarkers and molecular mechanisms in Chronic Obstructive Pulmonary Disease and rheumatoid arthritis using integrated bioinformatics and machine learning approaches.Journal, genetic engineering & biotechnology · 2026Article
- Uncovering sodium overload-associated gene signatures in chronic obstructive pulmonary disease through integrated bioinformatics and machine learning.Journal of thoracic disease · 2026Article
- Tumor-intrinsic B4GALNT3 expression drives a protective immune microenvironment in endometriosis-associated ovarian cancer.Translational cancer research · 2026Article
- Critical Biological Functions and Clinical Implications of Epigenetic-Related Candidate Biomarkers in Chronic Obstructive Pulmonary Disease: Integrated Machine Learning Screening and Basic Experimental Validation.International journal of chronic obstructive pulmonary disease · 2026Article
- Article
- Investigating key genes and molecular mechanisms of prostate cancer and coronary heart disease through transcriptomics and experimental validation.Translational andrology and urology · 2025Article
- Article
- Advances in artificial intelligence applications for the management of chronic obstructive pulmonary disease.Frontiers in medicine · 2025Review
- Identification of diagnostic biomarkers and immune cell profiles associated with COPD integrated bioinformatics and machine learning.Journal of cellular and molecular medicine · 2024Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
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 identifying ADD3 and GNAS as diagnostic biomarkers for COPD. Subsequently, the diagnostic efficacy of ADD3 and GNAS was assessed, and the impact of their expression levels on overall survival was further evaluated and quantified in the validation cohort. Examination of immune cell subtype infiltration found increased proportions of cytotoxic CD8
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Registered trials
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