Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks.
Overview
- Human Phenome Institute, Zhangjiang Fudan International Innovation Center, MOE Key Laboratory of Contemporary Anthropology, Fudan University, Shanghai, China
- Department of Neurology, Children's Hospital of Fudan University, Shanghai, China
- Shanghai Key Laboratory of Gene Editing and Cell Therapy for Rare Diseases, Fudan University, Shanghai, China
- Ningbo Key Laboratory of Genomic Medicine and Birth Defects Prevention, The Affiliated Women and Children's Hospital of Ningbo University, Ningbo, China
- Department of Neurology, Children's Hospital of Fudan University, National Children's Medical Center, Shanghai, China
- Department of Neurosurgery, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- Department of Neurosurgery, Children's Hospital of Fudan University, Shanghai, China
- Department of Pathology, Children's Hospital of Fudan University, Shanghai, China
- State Key Laboratory of Genetic Engineering, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China
- Institute of Medical Genetics and Genomics, Fudan University, Shanghai, China
Abstract
The abstract is not reproduced here: the paper's license (CC BY-NC-ND) does not allow it. Read it in the paper, at the publisher or on Europe PMC.
Code
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Data
Datasets cited
- geo:GSE256068, at NCBI GEO; found in the text, “Validation of the subtyping framework in an…”
Data availability statement
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- it says that the data are available on request
Read it in the paper: doi.org/10.1002/epi.70161.
Versions
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Version 1, 30 September 2026: the first record
Recorded: type, language, journal, volume, issue, pages, dates, 12 authors, 5 keywords, 9 MeSH terms, 3 funders, 45 references.
Cite
This paper
Weng, Y., Ma, Y., Hou, W., Li, H., Zhou, Y., Zhao, R., Li, H., Chen, L., Ma, Y., Jin, L., Wang, Y., & An, Y. (2026). Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks. Epilepsia, 67(6), 3211-3225. https://
BibTeX
@article{weng2026decodin
author = {Weng, Yanping and Ma, Yu and Hou, Wanwan and Li, Haibo and Zhou, Yuanfeng and Zhao, Rui and Li, Hao and Chen, Lian and Ma, Yangyang and Jin, Li and Wang, Yi and An, Yu},
title = {{Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks}},
journal = {Epilepsia},
year = {2026},
month = mar,
volume = {67},
number = {6},
pages = {3211--3225},
publisher = {Wiley},
issn = {0013-9580},
doi = {10.1002/
url = {https://
pmid = {41823335},
pmcid = {PMC13285232}
}
RIS
TY - JOUR
AU - Weng, Yanping
AU - Ma, Yu
AU - Hou, Wanwan
AU - Li, Haibo
AU - Zhou, Yuanfeng
AU - Zhao, Rui
AU - Li, Hao
AU - Chen, Lian
AU - Ma, Yangyang
AU - Jin, Li
AU - Wang, Yi
AU - An, Yu
TI - Decoding epilepsy's molecular blueprint: Machine learning unravels transcriptomic subtypes and regulatory networks
T2 - Epilepsia
J2 - Epilepsia
PY - 2026
DA - 2026/
VL - 67
IS - 6
SP - 3211
EP - 3225
SN - 0013-9580
PB - Wiley
DO - 10.1002/
UR - https://
LA - en
ER -
CSL-JSON
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