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For: Chen D, Feng X, Lv Z, Xu X, Lu Y, Wu W, Wu H, Liu H, Cao L, Ye S, Chen J, Wu J. ACADS acts as a potential methylation biomarker associated with the proliferation and metastasis of hepatocellular carcinomas. Aging (Albany NY) 2019;11:8825-44. [PMID: 31652420 DOI: 10.18632/aging.102292] [Cited by in Crossref: 14] [Cited by in F6Publishing: 14] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Gao X, Xu M, Wang H, Xia Z, Sun H, Liu M, Zhao S, Yang F, Niu Z, Gao H, Zhu H, Lu J, Zhou X. Development and validation of a mitochondrial energy metabolism-related risk model in hepatocellular carcinoma. Gene 2023;855:147133. [PMID: 36565797 DOI: 10.1016/j.gene.2022.147133] [Reference Citation Analysis]
2 Yang J, Yang X, Guo J, Liu S. A novel fatty acid metabolism-related gene prognostic signature and candidate drugs for patients with hepatocellular carcinoma. PeerJ 2023;11:e14622. [PMID: 36632140 DOI: 10.7717/peerj.14622] [Reference Citation Analysis]
3 Wang Y, Han Y, Zhou F, Fan T, Liu F. Simple Detection of DNA Methyltransferase with an Integrated Padlock Probe. Biosensors 2022;12:569. [DOI: 10.3390/bios12080569] [Reference Citation Analysis]
4 Shi Q, Liu Y, Lu M, Lei Q, Chen Z, Wang L, He X. A pathway-guided strategy identifies a metabolic signature for prognosis prediction and precision therapy for hepatocellular carcinoma. Computers in Biology and Medicine 2022;144:105376. [DOI: 10.1016/j.compbiomed.2022.105376] [Reference Citation Analysis]
5 Shi J, Yi Z, Jin L, Zhao L, Raskind A, Yeomans L, Nwosu ZC, Simeone DM, Lyssiotis CA, Stringer KA, Kwon RS. Cyst fluid metabolites distinguish malignant from benign pancreatic cysts. Neoplasia 2021;23:1078-88. [PMID: 34583246 DOI: 10.1016/j.neo.2021.09.004] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 2.0] [Reference Citation Analysis]
6 He D, Cai L, Huang W, Weng Q, Lin X, You M, Liao S. Prognostic value of fatty acid metabolism-related genes in patients with hepatocellular carcinoma. Aging (Albany NY) 2021;13:17847-63. [PMID: 34257161 DOI: 10.18632/aging.203288] [Cited by in Crossref: 7] [Cited by in F6Publishing: 9] [Article Influence: 3.5] [Reference Citation Analysis]
7 Zhang Q, Xiao Z, Sun S, Wang K, Qian J, Cui Z, Tao T, Zhou J. Integrated Proteomics and Bioinformatics to Identify Potential Prognostic Biomarkers in Hepatocellular Carcinoma. Cancer Manag Res 2021;13:2307-17. [PMID: 33732023 DOI: 10.2147/CMAR.S291811] [Cited by in Crossref: 6] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
8 Wu Q, Yan T, Chen Y, Chang J, Jiang Y, Zhu D, Wei Y. Integrated Analysis of Expression and Prognostic Values of Acyl-CoA Dehydrogenase short-chain in Colorectal Cancer. Int J Med Sci 2021;18:3631-43. [PMID: 34790035 DOI: 10.7150/ijms.63953] [Cited by in Crossref: 3] [Article Influence: 1.5] [Reference Citation Analysis]
9 He Z, Wang C, Xue H, Zhao R, Li G. Identification of a Metabolism-Related Risk Signature Associated With Clinical Prognosis in Glioblastoma Using Integrated Bioinformatic Analysis. Front Oncol 2020;10:1631. [PMID: 33042807 DOI: 10.3389/fonc.2020.01631] [Cited by in Crossref: 9] [Cited by in F6Publishing: 10] [Article Influence: 3.0] [Reference Citation Analysis]
10 Liu A, Wu Q, Peng D, Ares I, Anadón A, Lopez-Torres B, Martínez-Larrañaga MR, Wang X, Martínez MA. A novel strategy for the diagnosis, prognosis, treatment, and chemoresistance of hepatocellular carcinoma: DNA methylation. Med Res Rev 2020;40:1973-2018. [PMID: 32525219 DOI: 10.1002/med.21696] [Cited by in Crossref: 24] [Cited by in F6Publishing: 26] [Article Influence: 8.0] [Reference Citation Analysis]
11 Wang M, Ye Q, Mao D, Li H. Research Progress in Liver-Regenerating Microenvironment and DNA Methylation in Hepatocellular Carcinoma: The Role of Traditional Chinese Medicine. Med Sci Monit 2020;26:e920310. [PMID: 32144233 DOI: 10.12659/MSM.920310] [Cited by in Crossref: 3] [Cited by in F6Publishing: 5] [Article Influence: 1.0] [Reference Citation Analysis]