Kai Ding
Impact in
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
- Hematology top 10%
Papers in
- Hematology 19
- Multiple Myeloma Research and Treatments 9
- Acute Myeloid Leukemia Research 7
- Immunology 17
- Immune Cell Function and Interaction 9
- Immunotherapy and Immune Responses 5
- T-cell and B-cell Immunology 5
- Immunodeficiency and Autoimmune Disorders 4
- Co-authors
- Rong Fu (31 shared papers)Zhaoyun Liu (21 shared papers)Yige Zhang (1 shared paper)Wenge Ding (1 shared paper)Hua Fei (1 shared paper)Wei‐Fen Xie (6 shared papers)Jia Song (19 shared papers)Hui Liu (6 shared papers)
- Journals
- Journal of Clinical Laboratory Analysis (3 papers)Clinical and Translational Medicine (2 papers)Molecular Cancer (2 papers)Annals of Hematology (2 papers)Scientific Reports (2 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Kai Ding
73 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 101
- Cancer Research 277
- Hematology 137
- Immunology 241
- Oncology 214
- Molecular Biology 581
Countries citing papers authored by Kai Ding
This map shows the geographic impact of Kai Ding'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 Kai Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kai Ding more than expected).
Fields of papers citing papers by Kai Ding
This network shows the impact of papers produced by Kai Ding. 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 Kai Ding. The network helps show where Kai Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Kai Ding, 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 77 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 119 | |
| 2 | 2020 | 112 | |
| 3 | 2022 | 74 | |
| 4 | 2016 | 73 | |
| 5 | 2018 | 71 | |
| 6 | 2018 | 63 | |
| 7 | 2018 | 57 | |
| 8 | 2017 | 40 | |
| 9 | 2016 | 38 | |
| 10 | 2019 | 37 | |
| 11 | 2018 | 31 | |
| 12 | The role of Pim kinase in immunomodulation. | 2020 | 30 |
| 13 | 2016 | 29 | |
| 14 | 2015 | 27 | |
| 15 | 2012 | 26 | |
| 16 | 2022 | 25 | |
| 17 | 2020 | 22 | |
| 18 | 2018 | 21 | |
| 19 | 2017 | 19 | |
| 20 | 2018 | 18 |
About Kai Ding
Kai Ding is a scholar working on Hematology, Immunology, Molecular Biology, Oncology and Cancer Research, having authored 77 papers that have together received 1.3k indexed citations. Recurring topics across this work include Multiple Myeloma Research and Treatments (9 papers), Immune Cell Function and Interaction (9 papers), Acute Myeloid Leukemia Research (7 papers), Immunotherapy and Immune Responses (5 papers), T-cell and B-cell Immunology (5 papers), Immunodeficiency and Autoimmune Disorders (4 papers), Peptidase Inhibition and Analysis (4 papers) and Liver physiology and pathology (4 papers). The work is most often cited by research in Cancer Research (277 citations), Hematology (137 citations), Immunology (241 citations), Oncology (214 citations) and Molecular Biology (581 citations). Kai Ding has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Rong Fu, Zhaoyun Liu, Yige Zhang, Wenge Ding, Hua Fei, Wei‐Fen Xie, Jia Song, Hui Liu, Chen‐Hong Ding and Ji Wu. Their work appears in journals such as Journal of Clinical Laboratory Analysis, Clinical and Translational Medicine, Molecular Cancer, Annals of Hematology and Scientific Reports.
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.