Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning.

Journal: BMC cardiovascular disorders

PMID: 39501130

Abstract

BACKGROUND: Type II diabetes mellitus (T2DM) is strongly linked with a heightened risk of coronary artery disease (CAD). Exploring biological targets common to T2DM and CAD is essential for CAD intervention strategies.

Authors

Li Xie

Department of Pharmacy The First People's Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology Kunming China.
Han Xiao

Department of Radiation Oncology, Zhongshan Hospital, Fudan University, Shanghai, China.
Maoyu Zhao

Department of Cardiology, The Second Affiliated Hospital, Army Medical University, Third Military Medical University, Chongqing, 400037, China.
Li Xu

College of Acupuncture and Massage, Shandong University of Traditional Chinese Medicine, Jinan, China.
Si Tang

Department of Cardiology, The Second Affiliated Hospital, Army Medical University, Third Military Medical University, Chongqing, 400037, China.
Youzhu Qiu

Department of Cardiology, The Second Affiliated Hospital, Army Medical University, Third Military Medical University, Chongqing, 400037, China. zeng000xim@163.com.

Keywords

Aged Computational Biology Coronary Artery Disease Databases, Genetic Diabetes Mellitus, Type 2 Female Fibroblast Growth Factor 7 Gene Expression Profiling Gene Regulatory Networks Genetic Predisposition to Disease Humans Machine Learning Male Middle Aged Myocytes, Cardiac Myocytes, Smooth Muscle Single-Cell Analysis Transcriptome

External Resources

View on PubMed Access via DOI PubMed (39501130)

Screening of CAD-related secretory genes associated with type II diabetes based on comprehensive bioinformatics analysis and machine learning.

Abstract

Authors

Keywords

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