Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

Journal: The journal of headache and pain

PMID: 39833696

Abstract

BACKGROUND: Migraine is a complex neurological disorder characterized by recurrent episodes of severe headaches. Although genetic factors have been implicated, the precise molecular mechanisms, particularly gene expression patterns in migraine-associated brain regions, remain unclear. This study applies machine learning techniques to explore region-specific gene expression profiles and identify critical gene programs and transcription factors linked to migraine pathogenesis.

Authors

Lei Zhang

Division of Gastroenterology, Union Hospital, Tongji Medical College Medical College, Huazhong University of Science and Technology, Wuhan, China.
Yujie Li

College of Orthopedics and Traumatology, Henan University of Chinese Medicine, Zhengzhou, China.
Yunhao Xu

Clinical Systems Biology Laboratories, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
Wei Wang

State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
Guangyu Guo

Keywords

Gene Expression Profiling Gene Regulatory Networks Genetic Predisposition to Disease Genome-Wide Association Study Humans Machine Learning Migraine Disorders Polymorphism, Single Nucleotide Transcription Factors

External Resources

View on PubMed Access via DOI PubMed (39833696)

Machine learning-driven identification of critical gene programs and key transcription factors in migraine.

Abstract

Authors

Keywords

External Resources

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