Jun Minowada
- Hematology top 0.5%
- Acute Myeloid Leukemia Research 43
- Chronic Myeloid Leukemia Treatments 32
- Immunology top 0.5%
- T-cell and Retrovirus Studies 52
- Immune Cell Function and Interaction 37
- Genetics top 0.5%
- Chronic Lymphocytic Leukemia Research 64
-
- Lymphoma Diagnosis and Treatment 39
- Oncology top 2%
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- Acute Lymphoblastic Leukemia research 70
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- Monoclonal and Polyclonal Antibodies Research 33
- Co-authors
- George E. MooreT OnumaHans G. DrexlerB. I. Sahai SrivastavaGerhard GaedickeT TsubotaYoshinobu MatsuoHira L. Gurtoo
- Cited by
- HematologyImmunologyGenetics
- Journals
- JNCI Journal of the National Cancer Institute (24 papers)Leukemia Research (21 papers)Cancer (16 papers)
- Partner nations
- United StatesJapanGermany
In The Last Decade
Jun Minowada
294 papers receiving 7.2k citations
Hit Papers
Peers
Comparison fields: 5 of 127
- Hematology 1.6k
- Immunology 3.0k
- Genetics 1.4k
- Pathology and Forensic Medicine 1.2k
- Oncology 1.6k
Countries citing papers authored by Jun Minowada
This map shows the geographic impact of Jun Minowada'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 Minowada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Minowada more than expected).
Fields of papers citing papers by Jun Minowada
This network shows the impact of papers produced by Jun Minowada. 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 Minowada. The network helps show where Jun Minowada may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jun Minowada, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1996 | 67 | |
| 2 | 1995 | 30 | |
| 3 | 1994 | 5 | |
| 4 | 1994 | 33 | |
| 5 | 1994 | 5 | |
| 6 | 1994 | 8 | |
| 7 | 1992 | 9 | |
| 8 | 1992 | 3 | |
| 9 | 1991 | 26 | |
| 10 | 1991 | 12 | |
| 11 | 1991 | 4 | |
| 12 | 1991 | 4 | |
| 13 | 1991 | 1 | |
| 14 | 1989 | 45 | |
| 15 | 1988 | 29 | |
| 16 | 1986 | 92 | |
| 17 | 1985 | 11 | |
| 18 | Human T and B lymphoid cells: an electron microscopic study on thymocytes, peripheral blood lymphocytes, mitogen-stimulated cells and lymphoid cell lines. | 1979 | 3 |
| 19 | Antigenic determinants common to established human B-cell lines, but not shared by human T-cell lines (molt and sommer). | 1975 | 6 |
| 20 | 1967 | 49 |
About Jun Minowada
Jun Minowada is a scholar working on Hematology, Genetics and Immunology, having authored 301 papers that have together received 8.0k indexed citations. Recurring topics across this work include Acute Lymphoblastic Leukemia research (70 papers), Chronic Lymphocytic Leukemia Research (64 papers), T-cell and Retrovirus Studies (52 papers), Acute Myeloid Leukemia Research (43 papers), Lymphoma Diagnosis and Treatment (39 papers), Immune Cell Function and Interaction (37 papers), Monoclonal and Polyclonal Antibodies Research (33 papers) and Chronic Myeloid Leukemia Treatments (32 papers). The work is most often cited by research in Hematology (1.6k citations), Immunology (3.0k citations) and Genetics (1.4k citations). Jun Minowada has collaborated with scholars based in United States, Japan and Germany. Frequent co-authors include George E. Moore, T Onuma, Hans G. Drexler, B. I. Sahai Srivastava, Gerhard Gaedicke, T Tsubota, Yoshinobu Matsuo, Hira L. Gurtoo, Tin Han and Tucker W. LeBien. Their work appears in journals such as JNCI Journal of the National Cancer Institute, Leukemia Research, Cancer, Blood and International Journal of Cancer.
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.