Shoujun Bai

1.4k citations
34 papers · 694 · h-index 17

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
  • Nephrology top 5%
    • Chronic Kidney Disease and Diabetes

Papers in

    • Circular RNAs in diseases 8
    • Kruppel-like factors research 3
    • Renal and related cancers 3
    • Connective Tissue Growth Factor Research 3
    • Cancer-related molecular mechanisms research 9
    • MicroRNA in disease regulation 8

Shoujun Bai

31 papers receiving 686 citations

Peers

Shoujun Bai
Comparison fields: 5 of 80
  • Cancer Research 372
  • Nephrology 110
  • Molecular Biology 434
  • Geriatrics and Gerontology 12
  • Biomaterials 39
Replace Fu‐Xing‐Zi Li with:
Fu‐Xing‐Zi Li China
Jeff Yat‐Fai Chung Hong Kong
Huaner Ni China
Eric P. van der Veer Netherlands
Xiangyang Zhu United States
Qiao Liao China
Annemarie M. van Oeveren‐Rietdijk Netherlands
Yangguang Yin China
Shoujun Bai relative to Fu‐Xing‐Zi Li China Fu‐Xing‐Zi Li's profile →
Citations per field
00.5×1.5×2.4×
Fu‐Xing‐Zi Li · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Shoujun Bai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Shoujun Bai Line = papers co-authored together Shoujun Bai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201975
2 202065
3 201860
4 201249
5 202037
6 201034
7 202033
8 201832
9 201129
10 202127
11 201926
12 201223
13 201921
14 201120
15 202020
16 202018
17 202117
18 201916
19 202115
20 201913

About Shoujun Bai

Shoujun Bai is a scholar working on Molecular Biology, Cancer Research, Nephrology, Cardiology and Cardiovascular Medicine and Immunology, having authored 34 papers that have together received 694 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (9 papers), MicroRNA in disease regulation (8 papers), Circular RNAs in diseases (8 papers), Kruppel-like factors research (3 papers), Renal and related cancers (3 papers), Connective Tissue Growth Factor Research (3 papers), Lipid metabolism and disorders (3 papers) and Chronic Kidney Disease and Diabetes (3 papers). The work is most often cited by research in Cancer Research (372 citations), Nephrology (110 citations), Molecular Biology (434 citations), Geriatrics and Gerontology (12 citations) and Biomaterials (39 citations). Shoujun Bai has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Bo Tang, Tingting Ji, Yakun Wang, Tingting Ji, Xiaolei Qu, Yingchun Zhu, Xiaoyan Xiong, Chun Zhu, Ji Li and Xiaowei Wang. Their work appears in journals such as Journal of Cellular Physiology, Renal Failure, Journal of Cellular and Molecular Medicine, Aging and Oxidative Medicine and Cellular Longevity.

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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