Dakai Yang
Impact in
- Hepatology top 5%
- Liver physiology and pathology
- Cancer Research top 10%
- MicroRNA in disease regulation
Papers in
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- Extracellular vesicles in disease 5
- Circular RNAs in diseases 3
- Gut microbiota and health 2
- PI3K/AKT/mTOR signaling in cancer 2
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- Liver physiology and pathology 3
- Co-authors
- Jing Liu (1 shared paper)Qin Zhuang (2 shared papers)Hui Qian (1 shared paper)Jing Liu (2 shared papers)Wenrong Xu (3 shared papers)Hui Qian (2 shared papers)Qinggong Yuan (4 shared papers)Asha Balakrishnan (4 shared papers)
- Journals
- Neuroreport (1 paper)Journal of Hepatology (1 paper)Frontiers in Cellular and Infection Microbiology (1 paper)Nature Communications (1 paper)American Journal Of Pathology (1 paper)
- Partner nations
- ChinaGermanyUnited States
In The Last Decade
Dakai Yang
18 papers receiving 1.0k citations
Dakai Yang's Hit Papers
Peers
Comparison fields: 5 of 90
- Hepatology 136
- Cancer Research 189
- Immunology 148
- Oncology 173
- Molecular Biology 440
Countries citing papers authored by Dakai Yang
This map shows the geographic impact of Dakai Yang'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 Dakai Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dakai Yang more than expected).
Fields of papers citing papers by Dakai Yang
This network shows the impact of papers produced by Dakai Yang. 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 Dakai Yang. The network helps show where Dakai Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Dakai Yang, 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 | Cancer-associated fibroblasts: from basic science to anticancer therapy Hit paper breakdown → | 2023 | 313 |
| 2 | 2016 | 163 | |
| 3 | 2022 | 123 | |
| 4 | 2021 | 62 | |
| 5 | 2016 | 48 | |
| 6 | 2021 | 47 | |
| 7 | 2021 | 41 | |
| 8 | 2023 | 39 | |
| 9 | 2017 | 37 | |
| 10 | 2014 | 34 | |
| 11 | 2024 | 32 | |
| 12 | 2018 | 30 | |
| 13 | 2022 | 27 | |
| 14 | 2020 | 13 | |
| 15 | 2023 | 12 | |
| 16 | 2020 | 11 | |
| 17 | 2024 | 5 | |
| 18 | 2020 | 4 | |
| 19 | 2026 | 0 | |
| 20 | 2025 | 0 |
About Dakai Yang
Dakai Yang is a scholar working on Molecular Biology, Hepatology, Cancer Research, Surgery and Physiology, having authored 20 papers that have together received 1.0k indexed citations. Recurring topics across this work include Extracellular vesicles in disease (5 papers), Liver physiology and pathology (3 papers), Circular RNAs in diseases (3 papers), MicroRNA in disease regulation (3 papers), Drug-Induced Hepatotoxicity and Protection (2 papers), Liver Disease Diagnosis and Treatment (2 papers), Gut microbiota and health (2 papers) and PI3K/AKT/mTOR signaling in cancer (2 papers). The work is most often cited by research in Hepatology (136 citations), Cancer Research (189 citations), Immunology (148 citations), Oncology (173 citations) and Molecular Biology (440 citations). Dakai Yang has collaborated with scholars based in China, Germany and United States. Frequent co-authors include Jing Liu, Qin Zhuang, Hui Qian, Jing Liu, Wenrong Xu, Hui Qian, Qinggong Yuan, Asha Balakrishnan, Tobias Cantz and Michael P. Manns. Their work appears in journals such as Neuroreport, Journal of Hepatology, Frontiers in Cellular and Infection Microbiology, Nature Communications and American Journal Of Pathology.
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.