Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning.

Journal: International immunopharmacology

PMID: 38608447

Abstract

BACKGROUND: There is mounting evidence that asthma might exacerbate depression. We sought to examine candidates for diagnostic genes in patients suffering from asthma and depression.

Authors

Hui Jiang

Queensland Alliance for Environmental Health Science (QAEHS), University of Queensland, 20 Cornwall Street, Woolloongabba, QLD 4012, Australia.
Chang-Yong Fu

Department of Neurology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China. Electronic address: shouyi2011@163.com.

Keywords

Animals Asthma Biomarkers Computational Biology Databases, Genetic Gene Expression Profiling Gene Regulatory Networks Humans Machine Learning Mice

External Resources

View on PubMed Access via DOI PubMed (38608447)

Identification of shared potential diagnostic markers in asthma and depression through bioinformatics analysis and machine learning.

Abstract

Authors

Keywords

External Resources

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