Mining key circadian biomarkers for major depressive disorder by integrating bioinformatics and machine learning.

Journal: Aging

PMID: 38874508

Abstract

OBJECTIVE: This study aimed to identify key clock genes closely associated with major depressive disorder (MDD) using bioinformatics and machine learning approaches.

Authors

Yuhe Shi

Department of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.
Jue Zhu

Department of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.
Chaowen Hou

Department of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.
Xiaoling Li

Department of Infections，Beijing Hospital of Traditional Chinese Medicine, Affiliated to the Capital Medical University, No. 23, Back Road of the Art Gallery, Dongcheng District, Beijing 100010, China.
Qiaozhen Tong

Department of Pharmacy, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China.

Keywords

Adult Biomarkers Case-Control Studies Circadian Rhythm Computational Biology Depressive Disorder, Major Female Gene Expression Profiling Gene Regulatory Networks Humans Machine Learning Male Middle Aged

External Resources

View on PubMed Access via DOI PubMed (38874508)

Mining key circadian biomarkers for major depressive disorder by integrating bioinformatics and machine learning.

Abstract

Authors

Keywords

External Resources

Popular Topics

Recent Journals