Shunjun Fu

1.9k total citations
48 papers, 1.2k citations indexed

About

Shunjun Fu is a scholar working on Hepatology, Cancer Research and Oncology. According to data from OpenAlex, Shunjun Fu has authored 48 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Hepatology, 18 papers in Cancer Research and 15 papers in Oncology. Recurrent topics in Shunjun Fu's work include Hepatocellular Carcinoma Treatment and Prognosis (21 papers), Liver Disease Diagnosis and Treatment (8 papers) and Cancer, Lipids, and Metabolism (8 papers). Shunjun Fu is often cited by papers focused on Hepatocellular Carcinoma Treatment and Prognosis (21 papers), Liver Disease Diagnosis and Treatment (8 papers) and Cancer, Lipids, and Metabolism (8 papers). Shunjun Fu collaborates with scholars based in China, United States and Hong Kong. Shunjun Fu's co-authors include Baogang Peng, Shaoqiang Li, Li‐Jian Liang, Yunpeng Hua, Weikai Xiao, Beichu Guo, Zihai Li, Bei Liu, Jinyu Zhang and Shunli Shen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and The Journal of Immunology.

In The Last Decade

Shunjun Fu

44 papers receiving 1.2k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Shunjun Fu China 17 607 421 395 360 285 48 1.2k
Dan‐Yun Ruan China 17 407 0.7× 230 0.5× 285 0.7× 286 0.8× 236 0.8× 50 935
Ningling Ge China 20 505 0.8× 708 1.7× 411 1.0× 323 0.9× 328 1.2× 44 1.4k
Xinyu Bi China 17 480 0.8× 400 1.0× 245 0.6× 361 1.0× 216 0.8× 100 1.2k
Weikai Xiao China 18 477 0.8× 213 0.5× 473 1.2× 425 1.2× 122 0.4× 37 1.1k
Kota Arima Japan 19 644 1.1× 128 0.3× 260 0.7× 259 0.7× 231 0.8× 71 1.1k
Lijian Liang China 23 489 0.8× 407 1.0× 325 0.8× 529 1.5× 262 0.9× 74 1.4k
Yi‐Peng Fu China 17 389 0.6× 176 0.4× 259 0.7× 205 0.6× 137 0.5× 32 816
Susanna V. Ulahannan United States 17 524 0.9× 217 0.5× 168 0.4× 324 0.9× 217 0.8× 89 1.1k
Eun Yoon Cho South Korea 19 549 0.9× 242 0.6× 357 0.9× 377 1.0× 500 1.8× 50 1.6k
Mariko Tsukagoshi Japan 18 467 0.8× 158 0.4× 141 0.4× 228 0.6× 201 0.7× 108 956

Countries citing papers authored by Shunjun Fu

Since Specialization
Citations

This map shows the geographic impact of Shunjun Fu'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 Shunjun Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shunjun Fu more than expected).

Fields of papers citing papers by Shunjun Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shunjun Fu. 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 Shunjun Fu. The network helps show where Shunjun Fu may publish in the future.

Co-authorship network of co-authors of Shunjun Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Shunjun Fu. A scholar is included among the top collaborators of Shunjun Fu 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 Shunjun Fu. Shunjun Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Leshin, Rachel, et al.. (2025). “Kids and Girls”: Parents convey a male default in child-directed speech. Proceedings of the National Academy of Sciences. 122(11). e2420810122–e2420810122. 1 indexed citations
2.
Wang, Xiangyang, Linsen Ye, Yuhao Zheng, et al.. (2025). FXR inhibition functions as a checkpoint blockade of the pathogenic Tfh cell response in lupus. Cellular and Molecular Immunology. 22(8). 889–900. 1 indexed citations
3.
Xu, Yuyan, Yinghui Song, Ding Bai, et al.. (2025). Donafenib versus sorafenib in triple therapy for unresectable hepatocellular carcinoma: a propensity score-matched multicenter analysis. World Journal of Surgical Oncology. 23(1). 143–143.
4.
5.
Zhang, Chunyu, et al.. (2024). Dynamic stiffness formulation for vibration characteristics analysis of bi-dimensional functionally graded annular plate of variational thickness. Journal of Mechanical Science and Technology. 38(4). 1649–1660. 2 indexed citations
6.
Zhang, Cheng, Chang Li, Chunming Wang, et al.. (2023). Laparoscopic Anterior Right Hepatectomy: A Single-Center Experience. Journal of Visualized Experiments.
7.
Guo, Zeyi, Qingyu Xie, Yanping Wu, et al.. (2023). Aberrant expression of circular RNA DHPR facilitates tumor growth and metastasis by regulating the RASGEF1B/RAS/MAPK axis in hepatocellular carcinoma. Cellular Oncology. 46(5). 1333–1350. 10 indexed citations
8.
Cai, Lei, Cheng Zhang, Guolin He, et al.. (2022). Bloodless Laparoscopic Partial Splenectomy Assisted by Bipolar Radiofrequency Excision Hemostatic Device. Journal of Visualized Experiments. 1 indexed citations
9.
Xie, Wenxuan, Jiehui Tan, Бин Ли, et al.. (2021). Comparison of Hepatic Resection with Percutaneous Ablation for Hepatocellular Carcinoma in the Caudate Lobe Within Milan Criteria. Journal of Gastrointestinal Surgery. 26(2). 323–332. 1 indexed citations
10.
11.
Zhang, Yixi, Xiao-Jing Luo, Shunjun Fu, et al.. (2020). Gelsolin Promotes Cancer Progression by Regulating Epithelial-Mesenchymal Transition in Hepatocellular Carcinoma and Correlates with a Poor Prognosis. Journal of Oncology. 2020. 1–10. 22 indexed citations
12.
Hou, Yuchen, Nga Lei Tam, Bing Liao, et al.. (2018). Management of hepatic vein occlusive disease after liver transplantation. Medicine. 97(24). e11076–e11076. 6 indexed citations
13.
Wan, Daiwei, Shunli Shen, Shunjun Fu, et al.. (2016). miR-203 Suppresses the Proliferation and Metastasis of Hepatocellular Carcinoma by Targeting Oncogene ADAM9 and Oncogenic Long Non-coding RNA HULC. Anti-Cancer Agents in Medicinal Chemistry. 16(4). 414–423. 43 indexed citations
14.
Ji, Fei, Shunjun Fu, Shunli Shen, et al.. (2015). The prognostic value of combined TGF-β1 and ELF in hepatocellular carcinoma. BMC Cancer. 15(1). 116–116. 41 indexed citations
15.
Xiao, Weikai, Dong Chen, Shaoqiang Li, et al.. (2014). Prognostic significance of neutrophil-lymphocyte ratio in hepatocellular carcinoma: a meta-analysis. BMC Cancer. 14(1). 117–117. 189 indexed citations
16.
Shen, Shunli, Shunjun Fu, Xiongqing Huang, et al.. (2014). Elevated preoperative peripheral blood monocyte count predicts poor prognosis for hepatocellular carcinoma after curative resection. BMC Cancer. 14(1). 744–744. 31 indexed citations
17.
Xiao, Weikai, Dong Chen, Shaoqiang Li, et al.. (2014). Prognostic significance of glypican-3 in hepatocellular carcinoma: a meta-analysis. BMC Cancer. 14(1). 104–104. 39 indexed citations
18.
Fu, Shunjun, Shunli Shen, Shaoqiang Li, et al.. (2013). Prognostic value of preoperative peripheral neutrophil-to-lymphocyte ratio in patients with HBV-associated hepatocellular carcinoma after radical hepatectomy. Medical Oncology. 30(4). 721–721. 45 indexed citations
19.
Fu, Shunjun, et al.. (2013). Glypican-3 is a potential prognostic biomarker for hepatocellular carcinoma after curative resection. Surgery. 154(3). 536–544. 72 indexed citations
20.
Li, Shaoqiang, Lijian Liang, Yunpeng Hua, et al.. (2009). Bilateral liver resection for bilateral intrahepatic stones. World Journal of Gastroenterology. 15(29). 3660–3660. 6 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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