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M$$\vphantom{0}^2$$DGAT: Multi-view multi-scale dynamic graph attention network(GAT) based prediction of Parkinson’s disease(PD) progression using whole-blood RNA sequencing data

Crossref DOI link: https://doi.org/10.1038/s41598-026-40636-x

Published Online: 2026-03-02

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

Authors

Wei, Zhang

Zeqi, Xu

Chenjun, Wu

Qi, Dai
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (62302455)

Natural Science Foundation of Zhejiang Province (LQ24F030007)
License Information

Text and Data Mining valid from 2026-03-02

Version of Record valid from 2026-04-09
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Article History

Received: 28 February 2025

Accepted: 13 February 2026

First Online: 2 March 2026

Declarations

:

: The authors declare no competing interests.

: Approval was obtained from the Ethics Committee of the Zhejiang Sci-Tech University. The authors confirm that experimental analysis was performed in accordance with relevant guidelines and regulations.

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