Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients.

Zhang X, Guo H, Li X, Tao W, Ma X, Zhang Y, Xiao W

DOI: 10.1007/s00432-024-06001-z
Published: 2024 Oct 23
Container: Journal of cancer research and clinical oncology
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1007/s00432-024-06001-z,
  title = {Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients.},
  author = {Zhang X and Guo H and Li X and Tao W and Ma X and Zhang Y and Xiao W},
  year = {2024},
  journal = {Journal of cancer research and clinical oncology},
  doi = {10.1007/s00432-024-06001-z},
  url = {https://doi.org/10.1007/s00432-024-06001-z}
}

RIS

TY  - JOUR
TI  - Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients.
AU  - Zhang X
AU  - Guo H
AU  - Li X
AU  - Tao W
AU  - Ma X
AU  - Zhang Y
AU  - Xiao W
PY  - 2024
JO  - Journal of cancer research and clinical oncology
DO  - 10.1007/s00432-024-06001-z
UR  - https://doi.org/10.1007/s00432-024-06001-z
ER  -

APA

X, Z., H, G., X, L., W, T., X, M., Y, Z., & W, X. (2024). Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients.. Journal of cancer research and clinical oncology. https://doi.org/10.1007/s00432-024-06001-z

Source records

pubmed · retrieved 2026-09-25T19:08:20.542Z