Jun Nakata
Impact in
- Hematology top 10%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
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- Immunotherapy and Immune Responses
- Immune Cell Function and Interaction
- T-cell and B-cell Immunology
Papers in
- Immunology 18
- Immunotherapy and Immune Responses 13
- Immune Cell Function and Interaction 8
- T-cell and B-cell Immunology 5
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- Renal and related cancers 15
- Co-authors
- Akihiro Tsuboi (25 shared papers)Yoshitaka Oka (24 shared papers)Haruo Sugiyama (23 shared papers)Yusuke Oji (23 shared papers)Naoki Hosen (20 shared papers)Sumiyuki Nishida (20 shared papers)Fumihiro Fujiki (20 shared papers)Soyoko Morimoto (20 shared papers)
- Journals
- Cancer Immunology Immunotherapy (6 papers)Annals of Hematology (2 papers)Bone Marrow Transplantation (2 papers)European Journal Of Haematology (2 papers)Oncotarget (2 papers)
- Partner nations
- JapanAustraliaUnited States
In The Last Decade
Jun Nakata
37 papers receiving 398 citations
Peers
Comparison fields: 5 of 48
- Hematology 112
- Immunology 182
- Oncology 155
- Genetics 35
- Molecular Biology 168
Countries citing papers authored by Jun Nakata
This map shows the geographic impact of Jun Nakata'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 Nakata with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Nakata more than expected).
Fields of papers citing papers by Jun Nakata
This network shows the impact of papers produced by Jun Nakata. 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 Nakata. The network helps show where Jun Nakata may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Nakata, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 43 | |
| 2 | 2012 | 38 | |
| 3 | 2017 | 30 | |
| 4 | 2012 | 28 | |
| 5 | 2015 | 27 | |
| 6 | 2011 | 25 | |
| 7 | 2016 | 19 | |
| 8 | 2020 | 17 | |
| 9 | 2022 | 14 | |
| 10 | 2018 | 14 | |
| 11 | 2018 | 14 | |
| 12 | 2015 | 13 | |
| 13 | 2015 | 9 | |
| 14 | 2022 | 8 | |
| 15 | 2013 | 8 | |
| 16 | 2020 | 7 | |
| 17 | 2021 | 7 | |
| 18 | 2016 | 7 | |
| 19 | 2015 | 7 | |
| 20 | 2020 | 7 |
About Jun Nakata
Jun Nakata is a scholar working on Immunology, Molecular Biology, Oncology, Hematology and Cardiology and Cardiovascular Medicine, having authored 38 papers that have together received 402 indexed citations. Recurring topics across this work include Renal and related cancers (15 papers), CAR-T cell therapy research (14 papers), Immunotherapy and Immune Responses (13 papers), Hematopoietic Stem Cell Transplantation (8 papers), Immune Cell Function and Interaction (8 papers), T-cell and B-cell Immunology (5 papers), Cancer Immunotherapy and Biomarkers (4 papers) and Cytomegalovirus and herpesvirus research (4 papers). The work is most often cited by research in Hematology (112 citations), Immunology (182 citations), Oncology (155 citations), Genetics (35 citations) and Molecular Biology (168 citations). Jun Nakata has collaborated with scholars based in Japan, Australia and United States. Frequent co-authors include Akihiro Tsuboi, Yoshitaka Oka, Haruo Sugiyama, Yusuke Oji, Naoki Hosen, Sumiyuki Nishida, Fumihiro Fujiki, Soyoko Morimoto, Hiroko Nakajima and Satoshi Yoshihara. Their work appears in journals such as Cancer Immunology Immunotherapy, Annals of Hematology, Bone Marrow Transplantation, European Journal Of Haematology and Oncotarget.
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.