Order Article Reprints

Li L, Li L, Wang Y, Wu B, Guan Y, Chen Y, Zhao J. Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response. Genes. 2024; 15(11):1458. https://doi.org/10.3390/genes15111458

Li, Longpeng, Longhui Li, Yaxin Wang, Baoai Wu, Yue Guan, Yinghua Chen, and Jinfeng Zhao. 2024. "Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response" Genes 15, no. 11: 1458. https://doi.org/10.3390/genes15111458

Li, L., Li, L., Wang, Y., Wu, B., Guan, Y., Chen, Y., & Zhao, J. (2024). Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response. Genes, 15(11), 1458. https://doi.org/10.3390/genes15111458