DualGCN-GE: integration of spatiotemporal representations from whole-blood expression data with dual-view graph convolution network to identify Parkinson’s disease subtypes

Abstract Background As a typical type of neurodegenerative disorders, Parkinson’s disease(PD) is characterized by significant clinical and progression heterogeneity. Based on gene expression data, reliable detection of PACE subtypes in Parkinson’s disease(PD-PACE) has played a crucial role in addres...

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Egile Nagusiak:	Wei Zhang, Zeqi Xu, Ruochen Yu, Mingfeng Jiang, Qi Dai
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	BMC 2025-08-01
Saila:	BMC Bioinformatics
Gaiak:	Dual-view graph learning Parkinson-specific gene graphs Spatiotemporal representations Whole-blood expression data Disease subtype detection
Sarrera elektronikoa:	https://doi.org/10.1186/s12859-025-06181-6
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