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For: Zeng L, Fan X, Wang X, Deng H, Zhang K, Zhang X, He S, Li N, Han Q, Liu Z. Bioinformatics Analysis based on Multiple Databases Identifies Hub Genes Associated with Hepatocellular Carcinoma. Curr Genomics 2019;20:349-61. [PMID: 32476992 DOI: 10.2174/1389202920666191011092410] [Cited by in Crossref: 25] [Cited by in F6Publishing: 26] [Article Influence: 6.3] [Reference Citation Analysis]
Number Citing Articles
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2 Liao X, Chen L, Liu J, Hu H, Hou D, You R, Wang X, Huang H. m(6)A RNA methylation regulators predict prognosis and indicate characteristics of tumour microenvironment infiltration in acute myeloid leukaemia. Epigenetics 2022;:1-20. [PMID: 36567510 DOI: 10.1080/15592294.2022.2160134] [Reference Citation Analysis]
3 Yuan Y, Yang B, He Y, Zhang W, E G. Genome-Wide Selection Signal Analysis of Australian Boer Goat by Insertion/Deletion Variants. Russ J Genet 2022;58:1504-1512. [DOI: 10.1134/s1022795422120158] [Reference Citation Analysis]
4 Song S, Zhang M, Xie P, Wang S, Wang Y. Comprehensive analysis of cuproptosis-related genes and tumor microenvironment infiltration characterization in breast cancer. Front Immunol 2022;13:978909. [DOI: 10.3389/fimmu.2022.978909] [Reference Citation Analysis]
5 Peng Q, Huang H, Zhu C, Hou Q, Wei S, Xiao Y, Zhang Z, Sun X, Ali Sheikh MS. CDC20 May Serve as a Potential Biomarker-Based Risk Score System in Predicting the Prognosis of Patients with Hepatocellular Carcinoma. Oxidative Medicine and Cellular Longevity 2022;2022:1-21. [DOI: 10.1155/2022/8421813] [Reference Citation Analysis]
6 Lu X, Li R, Ying Y, Zhang W, Wang W. Gene signatures, immune infiltration, and drug sensitivity based on a comprehensive analysis of m6a RNA methylation regulators in cervical cancer. J Transl Med 2022;20:385. [PMID: 36058934 DOI: 10.1186/s12967-022-03600-7] [Reference Citation Analysis]
7 Ding J, Yao H, Chen Q. A Nomogram-Based Risk Classification System Predicting the Overall Survival of Childhood with Clear Cell Sarcoma of the Kidney Based on the SEER Database. Evidence-Based Complementary and Alternative Medicine 2022;2022:1-9. [DOI: 10.1155/2022/3784300] [Reference Citation Analysis]
8 Weng M, Li T, Zhao J, Guo M, Zhao W, Gu W, Sun C, Yue Y, Zhong Z, Nan K, Liao Q, Sun M, Zhou D, Miao C. mRNAsi-related metabolic risk score model identifies poor prognosis, immunoevasive contexture, and low chemotherapy response in colorectal cancer patients through machine learning. Front Immunol 2022;13:950782. [DOI: 10.3389/fimmu.2022.950782] [Reference Citation Analysis]
9 Liu C, Huang R, Yu H, Gong Y, Wu P, Feng Q, Li X. Fuzheng Xiaozheng prescription exerts anti-hepatocellular carcinoma effects by improving lipid and glucose metabolisms via regulating circRNA-miRNA-mRNA networks. Phytomedicine 2022;103:154226. [DOI: 10.1016/j.phymed.2022.154226] [Reference Citation Analysis]
10 Meng L, Chen S, Shi G, He S, Wang Z, Shen J, Wang J, Sooranna SR, Zhao J, Song J. Use of Single Cell Transcriptomic Techniques to Study the Role of High-Risk Human Papillomavirus Infection in Cervical Cancer. Front Immunol 2022;13:907599. [DOI: 10.3389/fimmu.2022.907599] [Cited by in Crossref: 1] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Li D, Liang J, Zhang W, Wu X, Fan J. A Distinct Glucose Metabolism Signature of Lung Adenocarcinoma With Prognostic Value. Front Genet 2022;13:860677. [DOI: 10.3389/fgene.2022.860677] [Reference Citation Analysis]
12 Li Z, Fang J, Chen S, Liu H, Zhou J, Huang J, Liu S, Peng Y. A Risk Model Developed Based on Necroptosis Predicts Overall Survival for Hepatocellular Carcinoma and Identification of Possible Therapeutic Drugs. Front Immunol 2022;13:870264. [PMID: 35422802 DOI: 10.3389/fimmu.2022.870264] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
13 Chang T, Wang M. Genomic analyses identify key molecules and significant signaling pathways in Sorafenib treated hepatocellular cancer cells.. [DOI: 10.1101/2022.03.15.484435] [Reference Citation Analysis]
14 Yang A, Wu M, Ni M, Zhang L, Li M, Wei P, Yang Y, Xiao W, An X. A risk scoring system based on tumor microenvironment cells to predict prognosis and immune activity in triple-negative breast cancer. Breast Cancer. [DOI: 10.1007/s12282-021-01326-w] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
15 Yu J, Nong C, Zhao J, Meng L, Song J, Xie Z. An Integrative Bioinformatic Analysis of Microbiome and Transcriptome for Predicting the Risk of Colon Adenocarcinoma. Disease Markers 2022;2022:1-12. [DOI: 10.1155/2022/7994074] [Reference Citation Analysis]
16 Zhang W, Liu Z, Xia S, Yao L, Li L, Gan Z, Tang H, Guo Q, Yan X, Sun Z. GDI2 is a novel diagnostic and prognostic biomarker in hepatocellular carcinoma. Aging (Albany NY) 2021;13:25304-24. [PMID: 34894398 DOI: 10.18632/aging.203748] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
17 Wang J, Huang M, Huang P, Zhao J, Tan J, Huang F, Ma R, Xiao Y, Deng G, Wei L, Wei Q, Wang Z, He S, Shen J, Sooranna S, Meng L, Song J. The Identification of a Tumor Infiltration CD8+ T-Cell Gene Signature That Can Potentially Improve the Prognosis and Prediction of Immunization Responses in Papillary Renal Cell Carcinoma. Front Oncol 2021;11:757641. [PMID: 34858833 DOI: 10.3389/fonc.2021.757641] [Cited by in F6Publishing: 1] [Reference Citation Analysis]
18 Shi H, Han L, Zhao J, Wang K, Xu M, Shi J, Dong Z. Tumor stemness and immune infiltration synergistically predict response of radiotherapy or immunotherapy and relapse in lung adenocarcinoma. Cancer Med 2021. [PMID: 34741449 DOI: 10.1002/cam4.4377] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
19 Yuan J, Wang Y, Liu F, Li W, Hong X, Chen C, Yu L, Ni W, Wei C, Liu X, Zhu X. Comparative transcriptomic analysis reveals the gonadal development-related gene response to environmental temperature in Mauremys mutica. Comp Biochem Physiol Part D Genomics Proteomics 2021;40:100925. [PMID: 34689019 DOI: 10.1016/j.cbd.2021.100925] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
20 Zhou S, Sun Y, Chen T, Wang J, He J, Lyu J, Shen Y, Chen X, Yang R. The Landscape of the Tumor Microenvironment in Skin Cutaneous Melanoma Reveals a Prognostic and Immunotherapeutically Relevant Gene Signature. Front Cell Dev Biol 2021;9:739594. [PMID: 34660598 DOI: 10.3389/fcell.2021.739594] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
21 Wu J, Zhu Y, Luo M, Li L. Comprehensive Analysis of Pyroptosis-Related Genes and Tumor Microenvironment Infiltration Characterization in Breast Cancer. Front Immunol 2021;12:748221. [PMID: 34659246 DOI: 10.3389/fimmu.2021.748221] [Cited by in Crossref: 25] [Cited by in F6Publishing: 26] [Article Influence: 12.5] [Reference Citation Analysis]
22 Wu Y, Meng L, Cai K, Zhao J, He S, Shen J, Wei Q, Wang Z, Sooranna S, Li H, Song J. A Tumor-Infiltration CD8+ T Cell-Based Gene Signature for Facilitating the Prognosis and Estimation of Immunization Responses in HPV+ Head and Neck Squamous Cell Cancer. Front Oncol 2021;11:749398. [PMID: 34650931 DOI: 10.3389/fonc.2021.749398] [Cited by in Crossref: 4] [Cited by in F6Publishing: 5] [Article Influence: 2.0] [Reference Citation Analysis]
23 Cheng Y, Li F, Zhang WS, Zou GY, Shen YX. Silencing BLNK protects against interleukin-1β-induced chondrocyte injury through the NF-κB signaling pathway. Cytokine 2021;148:155686. [PMID: 34521030 DOI: 10.1016/j.cyto.2021.155686] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
24 Dong C, Tian X, He F, Zhang J, Cui X, He Q, Si P, Shen Y. Integrative analysis of key candidate genes and signaling pathways in ovarian cancer by bioinformatics. J Ovarian Res 2021;14:92. [PMID: 34253236 DOI: 10.1186/s13048-021-00837-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
25 Wang X, Gao G, Chen Z, Chen Z, Han M, Xie X, Jin Q, Du H, Cao Z, Zhang H. Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis. Cancer Cell Int 2021;21:358. [PMID: 34315491 DOI: 10.1186/s12935-021-02058-9] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
26 Sun Y, Wu J, Yuan Y, Lu Y, Luo M, Lin L, Ma S. Construction of a Promising Tumor-Infiltrating CD8+ T Cells Gene Signature to Improve Prediction of the Prognosis and Immune Response of Uveal Melanoma. Front Cell Dev Biol 2021;9:673838. [PMID: 34124058 DOI: 10.3389/fcell.2021.673838] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 1.5] [Reference Citation Analysis]
27 Wu X, Sheng H, Wang L, Xia P, Wang Y, Yu L, Lv W, Hu J. A five-m6A regulatory gene signature is a prognostic biomarker in lung adenocarcinoma patients. Aging (Albany NY) 2021;13:10034-57. [PMID: 33795529 DOI: 10.18632/aging.202761] [Cited by in Crossref: 5] [Cited by in F6Publishing: 5] [Article Influence: 2.5] [Reference Citation Analysis]
28 Zhang H, Liu R, Sun L, Guo W, Ji X, Hu X. Comprehensive Analysis of Gene Expression Changes and Validation in Hepatocellular Carcinoma. Onco Targets Ther 2021;14:1021-31. [PMID: 33623390 DOI: 10.2147/OTT.S294500] [Cited by in Crossref: 10] [Cited by in F6Publishing: 10] [Article Influence: 5.0] [Reference Citation Analysis]
29 Chen H, Wu J, Lu L, Hu Z, Li X, Huang L, Zhang X, Chen M, Qin X, Xie L. Identification of Hub Genes Associated With Immune Infiltration and Predict Prognosis in Hepatocellular Carcinoma via Bioinformatics Approaches. Front Genet 2020;11:575762. [PMID: 33505422 DOI: 10.3389/fgene.2020.575762] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]