Keisuke Kataoka
Impact in
- Hematology top 1%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
- Genetics top 2%
Papers in
- Hematology 56
- Acute Myeloid Leukemia Research 37
- Hematopoietic Stem Cell Transplantation 21
- Chronic Myeloid Leukemia Treatments 10
- Co-authors
- Mineo Kurokawa (29 shared papers)Seishi Ogawa (33 shared papers)Yasunori Kogure (22 shared papers)Keiki Kumano (12 shared papers)Junji Koya (16 shared papers)Shunya Arai (11 shared papers)Akihide Yoshimi (10 shared papers)Yasuhito Nannya (11 shared papers)
- Journals
- Blood (24 papers)Experimental Hematology (7 papers)Cancer Science (5 papers)Bone Marrow Transplantation (5 papers)Stroke (5 papers)
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Keisuke Kataoka
130 papers receiving 3.0k citations
Keisuke Kataoka's Hit Papers
Peers
Comparison fields: 5 of 121
- Hematology 877
- Genetics 404
- Immunology 718
- Oncology 683
- Cancer Research 309
Countries citing papers authored by Keisuke Kataoka
This map shows the geographic impact of Keisuke Kataoka'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 Keisuke Kataoka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Keisuke Kataoka more than expected).
Fields of papers citing papers by Keisuke Kataoka
This network shows the impact of papers produced by Keisuke Kataoka. 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 Keisuke Kataoka. The network helps show where Keisuke Kataoka may publish in the future.
Co-authors
The 25 scholars most cited alongside Keisuke Kataoka, 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 145 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2006 | 296 | |
| 2 | 2020 | 194 | |
| 3 | 2014 | 171 | |
| 4 | 2011 | 126 | |
| 5 | 2018 | 111 | |
| 6 | 2017 | 100 | |
| 7 | 2009 | 97 | |
| 8 | 2016 | 90 | |
| 9 | 1989 | 88 | |
| 10 | 2020 | 84 | |
| 11 | Chemically defined cytokine-free expansion of human haematopoietic stem cells Hit paper breakdown → | 2023 | 78 |
| 12 | 2016 | 67 | |
| 13 | 2016 | 65 | |
| 14 | 1998 | 63 | |
| 15 | 2017 | 61 | |
| 16 | 2017 | 60 | |
| 17 | 2014 | 48 | |
| 18 | 2011 | 47 | |
| 19 | 1991 | 43 | |
| 20 | 2018 | 41 |
About Keisuke Kataoka
Keisuke Kataoka is a scholar working on Hematology, Molecular Biology, Oncology, Immunology and Genetics, having authored 145 papers that have together received 3.0k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (37 papers), Hematopoietic Stem Cell Transplantation (21 papers), T-cell and Retrovirus Studies (18 papers), Lymphoma Diagnosis and Treatment (16 papers), CAR-T cell therapy research (12 papers), Immune Cell Function and Interaction (11 papers), Chronic Myeloid Leukemia Treatments (10 papers) and Chronic Lymphocytic Leukemia Research (9 papers). The work is most often cited by research in Hematology (877 citations), Genetics (404 citations), Immunology (718 citations), Oncology (683 citations) and Cancer Research (309 citations). Keisuke Kataoka has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Mineo Kurokawa, Seishi Ogawa, Yasunori Kogure, Keiki Kumano, Junji Koya, Shunya Arai, Akihide Yoshimi, Yasuhito Nannya, Yoichiro Iwakura and Hiroshi Kobayashi. Their work appears in journals such as Blood, Experimental Hematology, Cancer Science, Bone Marrow Transplantation and Stroke.
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.