Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma
- DOI
- 10.7150/ijms.126491
- Published
- 2026-02-04
- Container
- International Journal of Medical Sciences
- Publisher
- Ivyspring International Publisher
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.7150/ijms.126491,
title = {Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma},
author = {Wei Lu and Susu Jiang and Qiran Sun and Yating Huang and Ying Yang and Xiaoqin Wang and Liwen Zhang and Yi Guo and Rujun Chen},
year = {2026},
journal = {International Journal of Medical Sciences},
doi = {10.7150/ijms.126491},
url = {https://doi.org/10.7150/ijms.126491}
}RIS
TY - JOUR TI - Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma AU - Wei Lu AU - Susu Jiang AU - Qiran Sun AU - Yating Huang AU - Ying Yang AU - Xiaoqin Wang AU - Liwen Zhang AU - Yi Guo AU - Rujun Chen PY - 2026 JO - International Journal of Medical Sciences DO - 10.7150/ijms.126491 UR - https://doi.org/10.7150/ijms.126491 ER -
APA
Lu, W., Jiang, S., Sun, Q., Huang, Y., Yang, Y., Wang, X., Zhang, L., Guo, Y., & Chen, R. (2026). Identification of Key Genes via Integrated Multi-Omics and Machine Learning Uncovers Tumor Biological Features and Prognostic Biomarkers in Uterine Leiomyosarcoma. International Journal of Medical Sciences. https://doi.org/10.7150/ijms.126491
Source records
- crossref · retrieved 2026-09-25T11:01:13.756Z