Ming Bai
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Hypoxia, and Metabolism
- Molecular Biology top 10%
- Circular RNAs in diseases
- Extracellular vesicles in disease
- RNA modifications and cancer
- RNA Interference and Gene Delivery
Papers in
-
- Circular RNAs in diseases 6
- Extracellular vesicles in disease 2
- Inflammasome and immune disorders 2
- RNA regulation and disease 2
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- MicroRNA in disease regulation 5
- Cancer-related molecular mechanisms research 3
- Co-authors
- Yi Ba (3 shared papers)Jialu Li (2 shared papers)Haiyang Zhang (2 shared papers)Qian Fan (2 shared papers)Ting Deng (2 shared papers)Guoguang Ying (2 shared papers)Tao Ning (2 shared papers)Kegan Zhu (2 shared papers)
In The Last Decade
Ming Bai
19 papers receiving 928 citations
Ming Bai's Hit Papers
Peers
Comparison fields: 5 of 84
- Cancer Research 499
- Molecular Biology 715
- Pharmacology 38
- Complementary and alternative medicine 31
- Biological Psychiatry 6
Countries citing papers authored by Ming Bai
This map shows the geographic impact of Ming 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 Ming Bai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Bai more than expected).
Fields of papers citing papers by Ming Bai
This network shows the impact of papers produced by Ming 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 Ming Bai. The network helps show where Ming Bai may publish in the future.
Co-authors
The 25 scholars most cited alongside Ming Bai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Exosome‐delivered circRNA promotes glycolysis to induce chemoresistance through the miR‐122‐PKM2 axis in colorectal cancer Hit paper breakdown → | 2020 | 425 |
| 2 | 2020 | 163 | |
| 3 | 2015 | 89 | |
| 4 | 2022 | 42 | |
| 5 | 2020 | 41 | |
| 6 | 2021 | 29 | |
| 7 | 2018 | 25 | |
| 8 | 2020 | 19 | |
| 9 | 2024 | 19 | |
| 10 | 2023 | 17 | |
| 11 | 2025 | 15 | |
| 12 | 2021 | 14 | |
| 13 | 2022 | 8 | |
| 14 | 2020 | 8 | |
| 15 | 2024 | 7 | |
| 16 | 2012 | 5 | |
| 17 | 2009 | 4 | |
| 18 | 2011 | 3 | |
| 19 | 2024 | 1 | |
| 20 | 2024 | 0 |
About Ming Bai
Ming Bai is a scholar working on Molecular Biology, Cancer Research, Nephrology, Mechanics of Materials and Computational Theory and Mathematics, having authored 20 papers that have together received 934 indexed citations. Recurring topics across this work include Circular RNAs in diseases (6 papers), MicroRNA in disease regulation (5 papers), Cancer-related molecular mechanisms research (3 papers), Gout, Hyperuricemia, Uric Acid (2 papers), Extracellular vesicles in disease (2 papers), Inflammasome and immune disorders (2 papers), RNA regulation and disease (2 papers) and Nitric Oxide and Endothelin Effects (1 paper). The work is most often cited by research in Cancer Research (499 citations), Molecular Biology (715 citations), Pharmacology (38 citations), Complementary and alternative medicine (31 citations) and Biological Psychiatry (6 citations). Ming Bai has collaborated with scholars based in China and Japan. Frequent co-authors include Yi Ba, Jialu Li, Haiyang Zhang, Qian Fan, Ting Deng, Guoguang Ying, Tao Ning, Kegan Zhu, Haiou Yang and Xinyi Wang. Their work appears in journals such as Nature Communications, BMC Cardiovascular Disorders, Cellular & Molecular Biology Letters, Journal of Physiology and Biochemistry and Journal of Ethnopharmacology.
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.