Bai Ruan
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Hepatology top 5%
- Liver physiology and pathology
Papers in
- Hepatology 12
- Liver physiology and pathology 10
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- MicroRNA in disease regulation 9
- Cancer-related molecular mechanisms research 6
- Cancer, Hypoxia, and Metabolism 3
- Co-authors
- Juanli DuanLin WangKaishan TaoHua HanKefeng DouPing SongXisheng YangZhuochao Zhang
- Journals
- Tumor Biology (3 papers)Hepatology (3 papers)Oncotarget (3 papers)International Journal of Biological Sciences (2 papers)Signal Transduction and Targeted Therapy (2 papers)
- Partner nations
- China
In The Last Decade
Bai Ruan
31 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 79
- Cancer Research 567
- Hepatology 250
- Molecular Biology 782
- Epidemiology 295
- Immunology 169
Countries citing papers authored by Bai Ruan
This map shows the geographic impact of Bai Ruan'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 Bai Ruan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bai Ruan more than expected).
Fields of papers citing papers by Bai Ruan
This network shows the impact of papers produced by Bai Ruan. 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 Bai Ruan. The network helps show where Bai Ruan may publish in the future.
Co-authors
The 25 scholars most cited alongside Bai Ruan, 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 | 2024 | 4 | |
| 2 | 2024 | 0 | |
| 3 | 2023 | 4 | |
| 4 | 2023 | 15 | |
| 5 | 2022 | 11 | |
| 6 | 2022 | 33 | |
| 7 | 2022 | 35 | |
| 8 | 2021 | 43 | |
| 9 | 2021 | 69 | |
| 10 | 2021 | 14 | |
| 11 | 2017 | 25 | |
| 12 | 2017 | 245 | |
| 13 | 2016 | 25 | |
| 14 | 2015 | 22 | |
| 15 | 2015 | 51 | |
| 16 | 2015 | 32 | |
| 17 | 2014 | 39 | |
| 18 | 2014 | 17 | |
| 19 | Insulin-like growth factor binding protein-1 inhibits cancer cell invasion and is associated with poor prognosis in hepatocellular carcinoma. | 2014 | 37 |
| 20 | 2013 | 63 |
About Bai Ruan
Bai Ruan is a scholar working on Hepatology, Cancer Research, Modeling and Simulation, Sensory Systems and Geriatrics and Gerontology, having authored 33 papers that have together received 1.3k indexed citations. Recurring topics across this work include Liver physiology and pathology (10 papers), MicroRNA in disease regulation (9 papers), Cancer-related molecular mechanisms research (6 papers), Circular RNAs in diseases (5 papers), Liver Disease Diagnosis and Treatment (4 papers), Cancer Cells and Metastasis (4 papers), Cancer, Hypoxia, and Metabolism (3 papers) and Endoplasmic Reticulum Stress and Disease (3 papers). The work is most often cited by research in Cancer Research (567 citations), Hepatology (250 citations), Molecular Biology (782 citations), Epidemiology (295 citations) and Immunology (169 citations). Bai Ruan has collaborated with scholars based in China. Frequent co-authors include Juanli Duan, Lin Wang, Kaishan Tao, Hua Han, Kefeng Dou, Ping Song, Xisheng Yang, Zhuochao Zhang, Zhen‐Sheng Yue and Zhiqiang Fang. Their work appears in journals such as Tumor Biology, Hepatology, Oncotarget, International Journal of Biological 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.