Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning.

Wang L, Zhou Z, Zhou X, Liu Y, Wang M

DOI: 10.3389/fmed.2025.1661259
Published: 2025
Container: Frontiers in medicine
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3389/fmed.2025.1661259,
  title = {Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning.},
  author = {Wang L and Zhou Z and Zhou X and Liu Y and Wang M},
  year = {2025},
  journal = {Frontiers in medicine},
  doi = {10.3389/fmed.2025.1661259},
  url = {https://doi.org/10.3389/fmed.2025.1661259}
}

RIS

TY  - JOUR
TI  - Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning.
AU  - Wang L
AU  - Zhou Z
AU  - Zhou X
AU  - Liu Y
AU  - Wang M
PY  - 2025
JO  - Frontiers in medicine
DO  - 10.3389/fmed.2025.1661259
UR  - https://doi.org/10.3389/fmed.2025.1661259
ER  -

APA

L, W., Z, Z., X, Z., Y, L., & M, W. (2025). Identification of anoikis-related genes and immune infiltration characteristics in Sjögren's syndrome based on machine learning.. Frontiers in medicine. https://doi.org/10.3389/fmed.2025.1661259

Source records

pubmed · retrieved 2026-09-25T03:32:36.063Z