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Machine learning- and WGCNA-mediated double analysis based on genes associated with disulfidptosis, cuproptosis and ferroptosis for the construction and validation of the prognostic model for breast cancer

Crossref DOI link: https://doi.org/10.1007/s00432-023-05378-7

Published Online: 2023-09-15

Published Print: 2023-12

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

Authors

Xu, Lijun

Wang, Shanshan

Zhang, Dan

Wu, Yunxi

Shan, Jiali

Zhu, Huixia

Wang, Chongyu

Wang, Qingqing
Funding

Funding for this research was provided by:

Postgraduate Research & Practice Innovation Program of Jiangsu Province (SJCX22_1631)

Research project on teaching reform of Nantong University (2020B43)

Jiangsu Province Capability Improvement Project through Science，Technology and Education (ZDXK202234)
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Text and Data Mining valid from 2023-09-15

Version of Record valid from 2023-09-15
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Article History

Received: 20 July 2023

Accepted: 30 August 2023

First Online: 15 September 2023

Declarations

:

: The authors declare no competing interests.

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