Bangmao Wang

5.6k total citations · 1 hit paper
149 papers, 3.5k citations indexed

About

Bangmao Wang is a scholar working on Molecular Biology, Surgery and Epidemiology. According to data from OpenAlex, Bangmao Wang has authored 149 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Molecular Biology, 49 papers in Surgery and 39 papers in Epidemiology. Recurrent topics in Bangmao Wang's work include Gut microbiota and health (43 papers), Liver Disease Diagnosis and Treatment (25 papers) and Liver Diseases and Immunity (19 papers). Bangmao Wang is often cited by papers focused on Gut microbiota and health (43 papers), Liver Disease Diagnosis and Treatment (25 papers) and Liver Diseases and Immunity (19 papers). Bangmao Wang collaborates with scholars based in China, United States and Netherlands. Bangmao Wang's co-authors include Hailong Cao, Tianyu Liu, Weilong Zhong, Sinan Wang, Wenxiao Dong, Lu Zhou, Xiang Liu, Xueli Song, Danfeng Chen and Qiang Tang and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Bangmao Wang

138 papers receiving 3.5k citations

Hit Papers

Clostridium butyricum, a butyrate-producing probiotic, in... 2019 2026 2021 2023 2019 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bangmao Wang China 30 2.0k 707 549 516 496 149 3.5k
Bangmao Wang China 31 1.9k 0.9× 613 0.9× 475 0.9× 484 0.9× 516 1.0× 100 3.4k
Leonilde Bonfrate Italy 29 1.4k 0.7× 678 1.0× 830 1.5× 768 1.5× 330 0.7× 74 3.4k
Glauben Landskron Chile 10 2.6k 1.3× 459 0.6× 366 0.7× 733 1.4× 799 1.6× 17 4.5k
Ravinder K. Gill United States 38 2.2k 1.1× 1.3k 1.8× 439 0.8× 627 1.2× 982 2.0× 142 4.6k
Hailong Cao China 39 3.4k 1.7× 683 1.0× 547 1.0× 740 1.4× 680 1.4× 138 5.2k
Eric L. Campbell United States 31 2.9k 1.4× 701 1.0× 574 1.0× 977 1.9× 420 0.8× 57 6.0k
Mingming Sun China 35 3.0k 1.5× 460 0.7× 573 1.0× 627 1.2× 293 0.6× 92 4.7k
Tianyu Liu China 32 2.3k 1.1× 372 0.5× 344 0.6× 508 1.0× 636 1.3× 100 3.4k
Rodrigo Quera Chile 22 2.3k 1.2× 887 1.3× 689 1.3× 775 1.5× 322 0.6× 147 4.6k
Atsushi Nishida Japan 29 2.3k 1.2× 662 0.9× 646 1.2× 573 1.1× 522 1.1× 104 4.5k

Countries citing papers authored by Bangmao Wang

Since Specialization
Citations

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

Fields of papers citing papers by Bangmao Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bangmao Wang

This figure shows the co-authorship network connecting the top 25 collaborators of Bangmao Wang. A scholar is included among the top collaborators of Bangmao Wang 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 Bangmao Wang. Bangmao Wang 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.
Wu, Qiuyan, Yali Wang, Yan Sun, et al.. (2025). Machine learning-based characterization of PANoptosis-related biomarkers and immune infiltration in ulcerative colitis: A comprehensive bioinformatics analysis and experimental validation. International Immunopharmacology. 151. 114298–114298. 3 indexed citations
2.
Xu, Xin, et al.. (2024). Gut microbiota in post-acute COVID-19 syndrome: not the end of the story. Frontiers in Microbiology. 15. 1500890–1500890. 3 indexed citations
4.
Li, Yanni, Hui Yang, Xue Zhang, et al.. (2024). Characterisation and Clinical Relevance of Tertiary Lymphoid Structures in Primary Biliary Cholangitis. Liver International. 45(4). e16157–e16157. 3 indexed citations
5.
Qin, Xiali, Wanyu Li, Jingyi Wu, et al.. (2024). A Saccharomyces boulardii-derived antioxidant protein, thioredoxin, ameliorates intestinal inflammation through transactivating epidermal growth factor receptor. Pharmacological Research. 208. 107372–107372. 6 indexed citations
6.
Ran, Ying, Xue Zhang, Hui Yang, et al.. (2024). Association of gut microbiota with lactose intolerance and coeliac disease: a two-sample Mendelian randomization study. Frontiers in Nutrition. 11. 1395801–1395801. 2 indexed citations
7.
Luo, Yang, Weilong Zhong, Siyuan Sun, et al.. (2023). Lafutidine Ameliorates Indomethacin-Induced Small Intestinal Damage in Rats by Modifying the Intestinal Mucosal Barrier, Inflammation, and Microbiota. Pharmacology. 108(3). 286–300. 5 indexed citations
8.
Wang, Jing, Ge Jin, Jingwen Zhao, et al.. (2023). Lactobacillus Acidophilus Supernatant Alleviates Osteoporosis by Upregulating Colonic SERT Expression. Future Microbiology. 18(9). 581–593. 3 indexed citations
9.
Zhou, Bingqian, et al.. (2023). Gut microbiota in COVID-19: new insights from inside. Gut Microbes. 15(1). 2201157–2201157. 17 indexed citations
10.
Jin, Ge, Qiang Tang, Shumin Huang, et al.. (2022). Early life Lactobacillus rhamnosus GG colonisation inhibits intestinal tumour formation. British Journal of Cancer. 126(10). 1421–1431. 21 indexed citations
11.
Liu, Li, Min Yang, Wenxiao Dong, et al.. (2021). Gut Dysbiosis and Abnormal Bile Acid Metabolism in Colitis-Associated Cancer. Gastroenterology Research and Practice. 2021. 1–12. 34 indexed citations
12.
Wang, Yi, Yanni Li, Ranko Gaćeša, et al.. (2020). Predicting Liver Disease Risk Using a Combination of Common Clinical Markers: A Screening Model from Routine Health Check-Up. Disease Markers. 2020. 1–11. 4 indexed citations
13.
Sun, Chao, et al.. (2020). Clinical Scoring Systems in Predicting the Outcomes of Small Bowel Bleeding. The Turkish Journal of Gastroenterology. 32(6). 493–499. 2 indexed citations
14.
Sun, Chao, et al.. (2020). Risk assessment of cirrhosis patients with esophageal and gastric variceal bleeding by three scoring systems. Zhonghua xiaohua neijing zazhi. 37(2). 105–110. 1 indexed citations
15.
Hui, Yangyang, Lanping Zhu, Bo Yang, et al.. (2019). Role of goblet cells in the progression of Barrett′s esophagus. Zhonghua xiaohua zazhi. 39(11). 731–734. 1 indexed citations
16.
Guo, Zixuan, Tianyu Liu, Kui Jiang, Bangmao Wang, & Hailong Cao. (2019). IDDF2019-ABS-0339 High-fat diet-induced gut microbiota dysbiosis activate MCP-1/CCR2 pathway and promote intestinal carcinogenesis. A43.2–A44. 1 indexed citations
17.
Cao, Xiaocang, et al.. (2016). Surgery for ulcerative colitis in the era of biological agents therapy. Zhōnghuá xiāohuà wàikē zázhì/Zhonghua xiaohua waike zazhi. 15(12). 1230.
18.
Wu, Yongdong, Shutian Zhang, Jianyu Hao, et al.. (2014). [Efficacy of compound digestive enzyme tablet for dyspeptic symptoms: a randomized double-blind parallel controlled multicenter clinical trial in China].. PubMed. 94(42). 3326–8. 2 indexed citations
19.
Sun, Chao, et al.. (2014). Learning Curve for Endoscopic Submucosal Dissection of Gastric Submucosal Tumors: Is It More Difficult Than It May Seem?. Journal of Laparoendoscopic & Advanced Surgical Techniques. 24(9). 623–627. 8 indexed citations
20.
Cao, Hailong, et al.. (2011). Clinical features of fundic gland polyps. Zhonghua xiaohua neijing zazhi. 28(10). 569–571.

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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