Dai B
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
-
- Cardiovascular Function and Risk Factors
Papers in
-
- Ion Transport and Channel Regulation 3
- Circular RNAs in diseases 3
- RNA Research and Splicing 3
-
- Cancer-related molecular mechanisms research 9
- MicroRNA in disease regulation 8
- Co-authors
- Dao Wen Wang (16 shared papers)Jiahui Fan (14 shared papers)Zhongwei Yin (12 shared papers)Xiang Nie (11 shared papers)Chen Chen (11 shared papers)Yanru Zhao (12 shared papers)Huaping Li (4 shared papers)Feihu Chen (9 shared papers)
- Journals
- Molecular Therapy — Nucleic Acids (4 papers)Circulation Research (3 papers)Gene (2 papers)Science China Life Sciences (2 papers)Signal Transduction and Targeted Therapy (1 paper)
- Partner nations
- ChinaPolandUnited States
In The Last Decade
Dai B
40 papers receiving 964 citations
Peers
Comparison fields: 5 of 82
- Cancer Research 356
- Cardiology and Cardiovascular Medicine 185
- Molecular Biology 578
- Parasitology 36
- Rheumatology 57
Countries citing papers authored by Dai B
This map shows the geographic impact of Dai B'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 Dai B with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dai B more than expected).
Fields of papers citing papers by Dai B
This network shows the impact of papers produced by Dai B. 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 Dai B. The network helps show where Dai B may publish in the future.
Co-authors
The 25 scholars most cited alongside Dai B, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 154 | |
| 2 | 2018 | 123 | |
| 3 | 2018 | 78 | |
| 4 | 2019 | 55 | |
| 5 | 2020 | 54 | |
| 6 | 2017 | 50 | |
| 7 | 2016 | 48 | |
| 8 | 2018 | 44 | |
| 9 | 2021 | 37 | |
| 10 | 2017 | 33 | |
| 11 | 2019 | 28 | |
| 12 | 2020 | 27 | |
| 13 | 2021 | 23 | |
| 14 | 2019 | 22 | |
| 15 | 2024 | 21 | |
| 16 | Advances in research on leptospira and human leptospirosis in China. | 1992 | 19 |
| 17 | 2019 | 18 | |
| 18 | 2024 | 17 | |
| 19 | 2021 | 15 | |
| 20 | 2017 | 14 |
About Dai B
Dai B is a scholar working on Molecular Biology, Cancer Research, Parasitology, Epidemiology and Immunology, having authored 40 papers that have together received 974 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (9 papers), Leptospirosis research and findings (8 papers), MicroRNA in disease regulation (8 papers), Ion Transport and Channel Regulation (3 papers), Circular RNAs in diseases (3 papers), RNA Research and Splicing (3 papers), Viral Infections and Immunology Research (3 papers) and Autophagy in Disease and Therapy (3 papers). The work is most often cited by research in Cancer Research (356 citations), Cardiology and Cardiovascular Medicine (185 citations), Molecular Biology (578 citations), Parasitology (36 citations) and Rheumatology (57 citations). Dai B has collaborated with scholars based in China, Poland and United States. Frequent co-authors include Dao Wen Wang, Jiahui Fan, Zhongwei Yin, Xiang Nie, Chen Chen, Yanru Zhao, Huaping Li, Feihu Chen, Renpeng Zhou and Jin‐Fang Ge. Their work appears in journals such as Molecular Therapy — Nucleic Acids, Circulation Research, Gene, Science China Life Sciences and Signal Transduction and Targeted Therapy.
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.