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

Crossref DOI link: https://doi.org/10.1186/s12859-025-06181-6

Published Online: 2025-08-12

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhang, Wei

Xu, Zeqi

Yu, Ruochen

Jiang, Mingfeng

Dai, Qi
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (62302455)

National Natural Science Foundation of China (62302455)

National Natural Science Foundation of China (62302455)

National Natural Science Foundation of China (62172369)

Natural Science Foundation of Zhejiang Province, China (LQ24F030007)
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Text and Data Mining valid from 2025-08-12

Version of Record valid from 2025-08-12
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Article History

Received: 4 October 2024

Accepted: 2 June 2025

First Online: 12 August 2025

Declarations

:

: Not applicable.

: Not applicable.

: The authors declare no Conflict of interest.

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