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Cited by in F6Publishing
For: Li G, Du X, Wu X, Wu S, Zhang Y, Xu J, Wang H, Chen T. Large-Scale Transcriptome Analysis Identified a Novel Cancer Driver Genes Signature for Predicting the Prognostic of Patients With Hepatocellular Carcinoma. Front Pharmacol 2021;12:638622. [PMID: 34335239 DOI: 10.3389/fphar.2021.638622] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
Number Citing Articles
1 Miao Y, Liu J, Liu X, Yuan Q, Li H, Zhang Y, Zhan Y, Feng X. Machine learning identification of cuproptosis and necroptosis-associated molecular subtypes to aid in prognosis assessment and immunotherapy response prediction in low-grade glioma. Front Genet 2022;13:951239. [DOI: 10.3389/fgene.2022.951239] [Reference Citation Analysis]
2 Wang L, Zhang W, Yang T, He L, Liao Y, Lu J. Construction and Comprehensive Analysis of a Stratification System Based on AGTRAP in Patients with Hepatocellular Carcinoma. Dis Markers 2021;2021:6144476. [PMID: 34840632 DOI: 10.1155/2021/6144476] [Cited by in F6Publishing: 3] [Reference Citation Analysis]
3 Du XW, Li G, Liu J, Zhang CY, Liu Q, Wang H, Chen TS. Comprehensive analysis of the cancer driver genes in breast cancer demonstrates their roles in cancer prognosis and tumor microenvironment. World J Surg Oncol 2021;19:273. [PMID: 34507558 DOI: 10.1186/s12957-021-02387-z] [Cited by in F6Publishing: 4] [Reference Citation Analysis]