Jun Deng
Impact in
- Hematology top 10%
- Multiple Myeloma Research and Treatments
- Oncology top 10%
- CAR-T cell therapy research
Papers in
- Hematology 15
- Blood Coagulation and Thrombosis Mechanisms 6
- Multiple Myeloma Research and Treatments 6
- Oncology 14
- CAR-T cell therapy research 9
- Co-authors
- Yu Hu (20 shared papers)Heng Mei (15 shared papers)Tao Guo (4 shared papers)Huiwen Jiang (5 shared papers)Lisha Ai (3 shared papers)Yaohui Wu (3 shared papers)Lin Liu (4 shared papers)Chenggong Li (8 shared papers)
- Journals
- Blood (5 papers)Thrombosis and Haemostasis (2 papers)Annals of Hematology (2 papers)Journal of Autoimmunity (1 paper)Molecular & Cellular Proteomics (1 paper)
- Partner nations
- ChinaUnited StatesUnited Kingdom
In The Last Decade
Jun Deng
33 papers receiving 701 citations
Peers
Comparison fields: 5 of 79
- Hematology 141
- Oncology 340
- Internal Medicine 36
- Immunology 94
- Critical Care and Intensive Care Medicine 21
Countries citing papers authored by Jun Deng
This map shows the geographic impact of Jun Deng'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 Jun Deng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Deng more than expected).
Fields of papers citing papers by Jun Deng
This network shows the impact of papers produced by Jun Deng. 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 Jun Deng. The network helps show where Jun Deng may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Deng, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 95 | |
| 2 | 2019 | 91 | |
| 3 | 2019 | 67 | |
| 4 | 2017 | 62 | |
| 5 | 2018 | 54 | |
| 6 | 2018 | 49 | |
| 7 | 2023 | 45 | |
| 8 | 2019 | 32 | |
| 9 | 2022 | 27 | |
| 10 | 2023 | 25 | |
| 11 | 2014 | 22 | |
| 12 | 2015 | 20 | |
| 13 | 1989 | 19 | |
| 14 | 2015 | 19 | |
| 15 | 2023 | 14 | |
| 16 | 2019 | 9 | |
| 17 | 2019 | 8 | |
| 18 | 2017 | 8 | |
| 19 | General anesthesia soon after dialysis may increase postoperative hypotension - A pilot study. | 2014 | 8 |
| 20 | 2023 | 7 |
About Jun Deng
Jun Deng is a scholar working on Hematology, Oncology, Molecular Biology, Immunology and Pulmonary and Respiratory Medicine, having authored 37 papers that have together received 714 indexed citations. Recurring topics across this work include CAR-T cell therapy research (9 papers), Blood Coagulation and Thrombosis Mechanisms (6 papers), Multiple Myeloma Research and Treatments (6 papers), Venous Thromboembolism Diagnosis and Management (5 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Glycosylation and Glycoproteins Research (3 papers), Blood properties and coagulation (3 papers) and Hemodynamic Monitoring and Therapy (2 papers). The work is most often cited by research in Hematology (141 citations), Oncology (340 citations), Internal Medicine (36 citations), Immunology (94 citations) and Critical Care and Intensive Care Medicine (21 citations). Jun Deng has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yu Hu, Heng Mei, Tao Guo, Huiwen Jiang, Lisha Ai, Yaohui Wu, Lin Liu, Chenggong Li, Jian Dong and Zhiwei Xia. Their work appears in journals such as Blood, Thrombosis and Haemostasis, Annals of Hematology, Journal of Autoimmunity and Molecular & Cellular Proteomics.
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.