Yongfei Tan

2.3k total citations
71 papers, 1.9k citations indexed

About

Yongfei Tan is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Yongfei Tan has authored 71 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Molecular Biology, 21 papers in Oncology and 11 papers in Cancer Research. Recurrent topics in Yongfei Tan's work include RNA modifications and cancer (10 papers), TGF-β signaling in diseases (7 papers) and Peptidase Inhibition and Analysis (7 papers). Yongfei Tan is often cited by papers focused on RNA modifications and cancer (10 papers), TGF-β signaling in diseases (7 papers) and Peptidase Inhibition and Analysis (7 papers). Yongfei Tan collaborates with scholars based in China, United States and Norway. Yongfei Tan's co-authors include Jianwei Zhou, Zhijun Ge, Yan Zhou, Weiliang Ding, Tieliang Ma, Yawei Zhao, Li Chen, Guojun Jiang, Meilin Wang and Jin Bai and has published in prestigious journals such as PLoS ONE, Cancer and Clinical Cancer Research.

In The Last Decade

Yongfei Tan

71 papers receiving 1.8k citations

Peers

Yongfei Tan

ONCOL

PFM

PRM

Weidong Jin China

Simona Ceccarelli Italy

Halina Waś Poland

Miao Chen China

Jianguo Feng China

Yupeng Liu China

Bo Ding China

Guillermo N. Armaiz-Peña United States

Zhizhong Li China

Xiaoyan Zhou China

Weidong Jin China

Yongfei Tan

972 ×1.0

583 ×1.2

ONCOL

318 ×0.8

109 ×0.6

PFM

181 ×1.0

PRM

Citations per year, relative to Yongfei Tan Yongfei Tan (= 1×) peers Weidong Jin

Countries citing papers authored by Yongfei Tan

Since Specialization

Citations

This map shows the geographic impact of Yongfei Tan's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Yongfei Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yongfei Tan more than expected).

Fields of papers citing papers by Yongfei Tan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yongfei Tan. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yongfei Tan. The network helps show where Yongfei Tan may publish in the future.

Co-authorship network of co-authors of Yongfei Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Yongfei Tan. A scholar is included among the top collaborators of Yongfei Tan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yongfei Tan. Yongfei Tan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Han, Hao, Yawei Zhao, Xuehan Yang, et al.. (2023). Exercise improves cognitive dysfunction and neuroinflammation in mice through Histone H3 lactylation in microglia. Immunity & Ageing. 20(1). 63–63. 53 indexed citations

Tan, Yongfei, et al.. (2023). High-frequency chest wall oscillation multiple times daily can better reduce the loss of pulmonary surfactant and improve lung compliance in mechanically ventilated patients. Heart & Lung. 61. 114–119. 2 indexed citations

Zhang, Honghong, Weiyong Zhao, Dongying Gu, et al.. (2018). Association of Antioxidative Enzymes Polymorphisms with Efficacy of Platin and Fluorouracil-Based Adjuvant Therapy in Gastric Cancer. Cellular Physiology and Biochemistry. 48(6). 2247–2257. 14 indexed citations

Xu, Ying, Wenjie Jiang, Guochang Chen, et al.. (2017). L-carnitine treatment of insulin resistance: A systematic review and meta-analysis. Advances in Clinical and Experimental Medicine. 26(2). 333–338. 80 indexed citations

Chen, Xiang, Zhijun Ge, Hong Chen, et al.. (2015). Effects of the JWA gene in the regulation of human breast cancer cells. Molecular Medicine Reports. 11(5). 3848–3853. 7 indexed citations

Han, Chao, Weiliang Ding, Wenjie Jiang, et al.. (2015). A comparison of the effects of midazolam, propofol and dexmedetomidine on the antioxidant system: A randomized trial. Experimental and Therapeutic Medicine. 9(6). 2293–2298. 17 indexed citations

Zhang, Yangmei, Meilin Wang, Dongying Gu, et al.. (2013). Association of XRCC1 Gene Polymorphisms with the Survival and Clinicopathological Characteristics of Gastric Cancer. DNA and Cell Biology. 32(3). 111–118. 10 indexed citations

Chen, Yansu, Xiaowei Xia, Shouyu Wang, et al.. (2013). High FAK combined with low JWA expression: clinical prognostic and predictive role for adjuvant fluorouracil–leucovorin–oxaliplatin treatment in resectable gastric cancer patients. Journal of Gastroenterology. 48(9). 1034–1044. 11 indexed citations

Chen, Yansu, Yefei Huang, Yulin Huang, et al.. (2013). JWA suppresses tumor angiogenesis via Sp1-activated matrix metalloproteinase-2 and its prognostic significance in human gastric cancer. Carcinogenesis. 35(2). 442–451. 50 indexed citations

10.

Yang, Ye, Xuan Li, Jing‐Jing Yang, et al.. (2013). MDM2 is a useful prognostic biomarker for resectable gastric cancer. Cancer Science. 104(5). 590–598. 23 indexed citations

11.

Wang, Shouyu, Xuming Wu, Yansu Chen, et al.. (2012). Prognostic and Predictive Role of JWA and XRCC1 Expressions in Gastric Cancer. Clinical Cancer Research. 18(10). 2987–2996. 102 indexed citations

12.

Yu, Haifeng, et al.. (2012). Overexpression of HOXA1 correlates with poor prognosis in patients with hepatocellular carcinoma. Tumor Biology. 33(6). 2125–2134. 38 indexed citations

13.

Ge, Zhijun, et al.. (2012). Downregulation of <I>JWA</I> Expression in Human Esophageal Squamous Cell Carcinoma and its Clinical Significance. Oncology Research Featuring Preclinical and Clinical Cancer Therapeutics. 20(4). 157–162. 6 indexed citations

14.

Zhao, Qinghong, Wei Wang, Zhengdong Zhang, et al.. (2011). A genetic variation in APE1 is associated with gastric cancer survival in a Chinese population. Cancer Science. 102(7). 1293–1297. 12 indexed citations

15.

Bai, Jin, Yan Zhou, Guangdi Chen, et al.. (2010). Overexpression of Cullin1 is associated with poor prognosis of patients with gastric cancer. Human Pathology. 42(3). 375–383. 71 indexed citations

16.

Jin, Guangfu, Ruifen Miao, Zhibin Hu, et al.. (2007). TGFB1 and TGFBR2 functional polymorphisms and risk of esophageal squamous cell carcinoma: a case–control analysis in a Chinese population. Journal of Cancer Research and Clinical Oncology. 134(3). 345–351. 35 indexed citations

17.

Gao, Jun, Ke Qiao, Hongxia Ma, et al.. (2007). Functional Polymorphisms in the Cyclooxygenase 2 (COX-2) Gene and Risk of Breast Cancer in a Chinese Population. Journal of Toxicology and Environmental Health. 70(11). 908–915. 40 indexed citations

18.

Yu, Rongbin, Hong Xin, Weiliang Ding, et al.. (2007). The association between the genetic polymorphism of HLA‐DQA1, DQB1, and DRB1 and serum alanine aminotransferase levels in chronic hepatitis C in the Chinese population. Journal of Gastroenterology and Hepatology. 23(9). 1394–1402. 21 indexed citations

19.

Jin, Guangfu, Lina Wang, Wensen Chen, et al.. (2006). Variant alleles of TGFB1 and TGFBR2 are associated with a decreased risk of gastric cancer in a Chinese population. International Journal of Cancer. 120(6). 1330–1335. 60 indexed citations

20.

Ge, Zhijun, Zeng Yin-ming, & Yongfei Tan. (2005). Effects of intrathecal 6-hydroxydopamine, alpha1 and alpha2 adrenergic receptor antagonists on antinociception of propofol in mice. Acta Pharmacologica Sinica. 26(2). 186–191. 9 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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