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Identification of Leaf Rust-Related Gene Signature in Wheat (Triticum Aestivum L.) Using High-Throughput Sequencing, Network Analysis, and Machine Learning Algorithms

Crossref DOI link: https://doi.org/10.1186/s12284-025-00839-8

Published Online: 2025-08-23

Published Print: 2025-12

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

Authors

Farhan, Muhammad

Ikram, Muhammad

Sun, Jing-E

Yang, San-Wei

Wang, Yong
Funding

Funding for this research was provided by:

National Natural Science Foundation of China (No. 31972222)

Guizhou Provincial Science and Technology Department Platform Project (YWZ [2024]009)

Program of Introducing Talents of Discipline to Universities of China ((111 Program, D20023))

Guizhou Science and Technology Innovation Talent Team Project (([2020]5001))
License Information

Text and Data Mining valid from 2025-08-23

Version of Record valid from 2025-08-23
More Information

Article History

Received: 1 June 2025

Accepted: 9 August 2025

First Online: 23 August 2025

Declarations

:

: No specific permissions were required to conduct this study. The data used in this study were obtained from the SRA database and comply with relevant institutional, national, and international guidelines and legislation.

: Not applicable.

: The authors declare no competing interests.

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