Shoujun Bai

1.4k total citations
34 papers, 694 citations indexed

About

Shoujun Bai is a scholar working on Molecular Biology, Cancer Research and Nephrology. According to data from OpenAlex, Shoujun Bai has authored 34 papers receiving a total of 694 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 14 papers in Cancer Research and 11 papers in Nephrology. Recurrent topics in Shoujun Bai's work include Cancer-related molecular mechanisms research (9 papers), MicroRNA in disease regulation (8 papers) and Circular RNAs in diseases (8 papers). Shoujun Bai is often cited by papers focused on Cancer-related molecular mechanisms research (9 papers), MicroRNA in disease regulation (8 papers) and Circular RNAs in diseases (8 papers). Shoujun Bai collaborates with scholars based in China, United States and Germany. Shoujun Bai's co-authors include Bo Tang, Tingting Ji, Yakun Wang, Tingting Ji, Xiaolei Qu, Yingchun Zhu, Xiaoyan Xiong, Ji Li, Chun Zhu and Xiaowei Wang and has published in prestigious journals such as Gene, Journal of Cellular Physiology and Journal of Alloys and Compounds.

In The Last Decade

Shoujun Bai

31 papers receiving 686 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shoujun Bai China 17 434 372 110 66 49 34 694
Eric P. van der Veer Netherlands 13 405 0.9× 245 0.7× 46 0.4× 79 1.2× 19 0.4× 22 673
Fu‐Xing‐Zi Li China 17 798 1.8× 433 1.2× 108 1.0× 102 1.5× 114 2.3× 32 1.2k
Huaner Ni China 9 588 1.4× 369 1.0× 24 0.2× 81 1.2× 43 0.9× 13 728
Nabil A. Rashdan United States 13 197 0.5× 48 0.1× 57 0.5× 80 1.2× 41 0.8× 18 460
Annemarie M. van Oeveren‐Rietdijk Netherlands 11 306 0.7× 243 0.7× 37 0.3× 33 0.5× 32 0.7× 12 528
Ge‐cai Chen China 13 208 0.5× 111 0.3× 40 0.4× 78 1.2× 20 0.4× 31 470
Di Gu China 10 382 0.9× 192 0.5× 81 0.7× 12 0.2× 21 0.4× 18 603
Alexander A. Kremzer Ukraine 17 381 0.9× 106 0.3× 51 0.5× 221 3.3× 67 1.4× 45 625
Sílvia Carbonell Sala Italy 12 391 0.9× 278 0.7× 24 0.2× 27 0.4× 162 3.3× 28 857

Countries citing papers authored by Shoujun Bai

Since Specialization
Citations

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

Fields of papers citing papers by Shoujun Bai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shoujun Bai

This figure shows the co-authorship network connecting the top 25 collaborators of Shoujun Bai. A scholar is included among the top collaborators of Shoujun Bai 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 Shoujun Bai. Shoujun Bai 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
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Ji, Li & Shoujun Bai. (2025). Cardiometabolic index as a predictor of gallstone incidence in U.S. adults: insights from NHANES 2017–2020. BMC Gastroenterology. 25(1). 45–45. 1 indexed citations
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Bai, Shoujun, et al.. (2021). hsa‐miR‐199b‐3p Prevents the Epithelial‐Mesenchymal Transition and Dysfunction of the Renal Tubule by Regulating E‐cadherin through Targeting KDM6A in Diabetic Nephropathy. Oxidative Medicine and Cellular Longevity. 2021(1). 8814163–8814163. 15 indexed citations
6.
Wang, Xiaowei, et al.. (2021). FOXO3a Protects against Kidney Injury in Type II Diabetic Nephropathy by Promoting Sirt6 Expression and Inhibiting Smad3 Acetylation. Oxidative Medicine and Cellular Longevity. 2021(1). 5565761–5565761. 17 indexed citations
7.
Xiao, Min, Shoujun Bai, Jing Chen, et al.. (2021). CDKN2B-AS1 participates in high glucose-induced apoptosis and fibrosis via NOTCH2 through functioning as a miR-98-5p decoy in human podocytes and renal tubular cells. Diabetology & Metabolic Syndrome. 13(1). 107–107. 12 indexed citations
8.
Bai, Shoujun, et al.. (2020). Exosomal circ_DLGAP4 promotes diabetic kidney disease progression by sponging miR-143 and targeting ERBB3/NF-κB/MMP-2 axis. Cell Death and Disease. 11(11). 1008–1008. 65 indexed citations
9.
Wang, Yakun, et al.. (2020). Circ_LARP4 regulates high glucose-induced cell proliferation, apoptosis, and fibrosis in mouse mesangial cells. Gene. 765. 145114–145114. 18 indexed citations
10.
Zhu, Yingchun, Xu Jiang, Wenxing Liang, et al.. (2019). miR-98-5p Alleviated Epithelial-to-Mesenchymal Transition and Renal Fibrosis via Targeting Hmga2 in Diabetic Nephropathy. International Journal of Endocrinology. 2019. 1–10. 21 indexed citations
11.
Xiong, Xiaoyan, Lin Bai, Shoujun Bai, Yakun Wang, & Tingting Ji. (2019). Uric acid induced epithelial−mesenchymal transition of renal tubular cells through PI3K/p‐Akt signaling pathway. Journal of Cellular Physiology. 234(9). 15563–15569. 16 indexed citations
12.
Wang, Xiaowei, Yong Xu, Yingchun Zhu, et al.. (2018). LncRNA NEAT1 promotes extracellular matrix accumulation and epithelial‐to‐mesenchymal transition by targeting miR‐27b‐3p and ZEB1 in diabetic nephropathy. Journal of Cellular Physiology. 234(8). 12926–12933. 60 indexed citations
13.
Zhu, Yingchun, et al.. (2017). The effect of Baicalein on the NF-κB/P65 expression in the peripheral blood of patients with diabetic nephropathy and in vitro. Biomedical Research-tokyo. 28(12). 5540–5545. 3 indexed citations
14.
Zhu, Yingchun, et al.. (2017). Suppression of CIP4/Par6 attenuates TGF-β1-induced epithelial-mesenchymal transition in NRK-52E cells. International Journal of Molecular Medicine. 40(4). 1165–1171. 8 indexed citations
15.
Bai, Shoujun, Rui Zeng, Qiaodan Zhou, et al.. (2012). Cdc42-Interacting Protein-4 Promotes TGF-Β1-Induced Epithelial-Mesenchymal Transition and Extracellular Matrix Deposition in Renal Proximal Tubular Epithelial Cells. International Journal of Biological Sciences. 8(6). 859–869. 23 indexed citations
16.
Ying, Yao, Honglan Wei, Lili Liu, et al.. (2011). Upregulated DJ-1 promotes renal tubular EMT by suppressing cytoplasmic PTEN expression and Akt activation. Journal of Huazhong University of Science and Technology [Medical Sciences]. 31(4). 469–475. 20 indexed citations
17.
Zhou, Qiaodan, Rui Zeng, Chuou Xu, et al.. (2011). Erbin inhibits TGF-β1-induced EMT in renal tubular epithelial cells through an ERK-dependent pathway. Journal of Molecular Medicine. 90(5). 563–574. 29 indexed citations
18.
Jian-e, Zhang, et al.. (2010). Gypenosides inhibit renal fibrosis by regulating expression of related genes in rats with unilateral ureteral obstruction. Journal of Nephrology. 24(1). 112–118. 7 indexed citations
19.
Zeng, Rui, Min Ho Han, Chun Li, et al.. (2010). Role of Sema4C in TGF- 1-induced mitogen-activated protein kinase activation and epithelial-mesenchymal transition in renal tubular epithelial cells. Nephrology Dialysis Transplantation. 26(4). 1149–1156. 34 indexed citations
20.
Nagasawa, H., et al.. (1992). Effects of some natural products as components of Chinese herbal medicines on mammary gland growth and function in mice.. PubMed. 6(2). 135–40. 1 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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