Kejin Wu
Impact in
- Cancer Research top 10%
- Breast Cancer Treatment Studies
- Cancer-related molecular mechanisms research
- Cancer Genomics and Diagnostics
-
- HER2/EGFR in Cancer Research
- Cancer Immunotherapy and Biomarkers
Papers in
-
- Breast Cancer Treatment Studies 13
- Cancer-related molecular mechanisms research 2
- Oncology 12
- HER2/EGFR in Cancer Research 5
- Cancer Treatment and Pharmacology 3
- Co-authors
- Mingdi Zhang (12 shared papers)Hongliang Chen (11 shared papers)Peng Zhang (8 shared papers)Maoli Wang (7 shared papers)Fang Bai (7 shared papers)Yi‐Peng Fu (3 shared papers)Qianru Huang (2 shared papers)Dan Li (2 shared papers)
- Journals
- The Breast (2 papers)Annals of Surgical Oncology (2 papers)Cancer (1 paper)Scientific Reports (1 paper)Molecular Cancer Therapeutics (1 paper)
- Partner nations
- ChinaUnited StatesCroatia
In The Last Decade
Kejin Wu
26 papers receiving 493 citations
Peers
Comparison fields: 5 of 79
- Cancer Research 228
- Oncology 199
- Molecular Medicine 23
- Pathology and Forensic Medicine 71
- Molecular Biology 204
Countries citing papers authored by Kejin Wu
This map shows the geographic impact of Kejin Wu'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 Kejin Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kejin Wu more than expected).
Fields of papers citing papers by Kejin Wu
This network shows the impact of papers produced by Kejin Wu. 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 Kejin Wu. The network helps show where Kejin Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Kejin Wu, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 82 | |
| 2 | 2013 | 65 | |
| 3 | 2017 | 56 | |
| 4 | 2013 | 34 | |
| 5 | 2019 | 28 | |
| 6 | 2017 | 26 | |
| 7 | 2016 | 23 | |
| 8 | 2019 | 22 | |
| 9 | 2018 | 20 | |
| 10 | 2019 | 19 | |
| 11 | 2014 | 15 | |
| 12 | 2014 | 15 | |
| 13 | 2013 | 14 | |
| 14 | 2021 | 13 | |
| 15 | 2014 | 10 | |
| 16 | 2023 | 10 | |
| 17 | 2021 | 9 | |
| 18 | 2018 | 8 | |
| 19 | 2020 | 8 | |
| 20 | 2024 | 6 |
About Kejin Wu
Kejin Wu is a scholar working on Cancer Research, Oncology, Molecular Biology, Pulmonary and Respiratory Medicine and Pathology and Forensic Medicine, having authored 27 papers that have together received 499 indexed citations. Recurring topics across this work include Breast Cancer Treatment Studies (13 papers), HER2/EGFR in Cancer Research (5 papers), Breast Lesions and Carcinomas (5 papers), Advanced Breast Cancer Therapies (4 papers), Cancer Treatment and Pharmacology (3 papers), RNA Interference and Gene Delivery (3 papers), Ferroptosis and cancer prognosis (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (228 citations), Oncology (199 citations), Molecular Medicine (23 citations), Pathology and Forensic Medicine (71 citations) and Molecular Biology (204 citations). Kejin Wu has collaborated with scholars based in China, United States and Croatia. Frequent co-authors include Mingdi Zhang, Hongliang Chen, Peng Zhang, Maoli Wang, Fang Bai, Yi‐Peng Fu, Qianru Huang, Dan Li, Bin Li and Yunshu Lu. Their work appears in journals such as The Breast, Annals of Surgical Oncology, Cancer, Scientific Reports and Molecular Cancer Therapeutics.
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.