T Kishida
Impact in
-
- Immune Cell Function and Interaction
- IL-33, ST2, and ILC Pathways
- Biotechnology top 10%
- Microbial Inactivation Methods
Papers in
-
- Microbial Inactivation Methods 2
-
- Immune Cell Function and Interaction 1
- interferon and immune responses 1
- Co-authors
- Osam Mazda (9 shared papers)Jirô Imanishi (8 shared papers)Masaharu Shin‐Ya (6 shared papers)Masaki Kita (3 shared papers)K Kataoka (1 shared paper)Junichi Sakagami (1 shared paper)Ryusuke Takada (1 shared paper)Yoichiro Iwakura (1 shared paper)
- Journals
- Gene Therapy (5 papers)Lara D. Veeken (1 paper)Biochemical and Biophysical Research Communications (1 paper)Osteoarthritis and Cartilage (1 paper)Clinical & Experimental Immunology (1 paper)
- Partner nations
- JapanUnited States
In The Last Decade
T Kishida
12 papers receiving 721 citations
Peers
Comparison fields: 5 of 81
- Immunology 199
- Biotechnology 72
- Genetics 172
- Cancer Research 81
- Molecular Biology 343
Countries citing papers authored by T Kishida
This map shows the geographic impact of T Kishida'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 T Kishida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites T Kishida more than expected).
Fields of papers citing papers by T Kishida
This network shows the impact of papers produced by T Kishida. 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 T Kishida. The network helps show where T Kishida may publish in the future.
Co-authors
The 25 scholars most cited alongside T Kishida, 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 | 2006 | 308 | |
| 2 | Suppression of growth of renal carcinoma cells by the von Hippel-Lindau tumor suppressor gene. | 1995 | 93 |
| 3 | 2001 | 85 | |
| 4 | 2006 | 60 | |
| 5 | 2003 | 50 | |
| 6 | 2006 | 50 | |
| 7 | 2001 | 47 | |
| 8 | 2015 | 18 | |
| 9 | 1992 | 14 | |
| 10 | Antitumor effects of interferon on transplanted tumors in congenitally athymic nude mice. | 1976 | 11 |
| 11 | 2006 | 6 | |
| 12 | 2006 | 1 | |
| 13 | 2003 | 1 |
About T Kishida
T Kishida is a scholar working on Biotechnology, Immunology, Rheumatology, Molecular Biology and Software, having authored 13 papers that have together received 744 indexed citations. Recurring topics across this work include RNA Interference and Gene Delivery (4 papers), Virus-based gene therapy research (2 papers), Viral Infectious Diseases and Gene Expression in Insects (2 papers), Microbial Inactivation Methods (2 papers), Immune Cell Function and Interaction (1 paper), Animal Virus Infections Studies (1 paper), Microfluidic and Bio-sensing Technologies (1 paper) and interferon and immune responses (1 paper). The work is most often cited by research in Immunology (199 citations), Biotechnology (72 citations), Genetics (172 citations), Cancer Research (81 citations) and Molecular Biology (343 citations). T Kishida has collaborated with scholars based in Japan and United States. Frequent co-authors include Osam Mazda, Jirô Imanishi, Masaharu Shin‐Ya, Masaki Kita, K Kataoka, Junichi Sakagami, Ryusuke Takada, Yoichiro Iwakura, Reiko Ito and Yoshihiro Ueda. Their work appears in journals such as Gene Therapy, Lara D. Veeken, Biochemical and Biophysical Research Communications, Osteoarthritis and Cartilage and Clinical & Experimental Immunology.
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.