Mikio Tomida
Impact in
- Immunology top 5%
- Reproductive System and Pregnancy
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- Oncology top 5%
- Cytokine Signaling Pathways and Interactions
Papers in
-
- Glycosylation and Glycoproteins Research 8
- RNA Interference and Gene Delivery 8
- Oncology 22
- Cytokine Signaling Pathways and Interactions 20
- Co-authors
- Motoo Hozumi (33 shared papers)Yuri Yamamoto-Yamaguchi (12 shared papers)Tetsuo Ono (5 shared papers)Yuri Yamamoto (13 shared papers)Kinji Inoue (4 shared papers)Takashi Yokota (2 shared papers)Takeshi Saito (2 shared papers)Hirohiko Akiyama (3 shared papers)
In The Last Decade
Mikio Tomida
60 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 94
- Immunology 561
- Oncology 668
- Geriatrics and Gerontology 46
- Cell Biology 225
- Hematology 146
Countries citing papers authored by Mikio Tomida
This map shows the geographic impact of Mikio Tomida'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 Mikio Tomida with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikio Tomida more than expected).
Fields of papers citing papers by Mikio Tomida
This network shows the impact of papers produced by Mikio Tomida. 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 Mikio Tomida. The network helps show where Mikio Tomida may publish in the future.
Co-authors
The 25 scholars most cited alongside Mikio Tomida, 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 61 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1984 | 275 | |
| 2 | 1986 | 104 | |
| 3 | 2007 | 75 | |
| 4 | 2009 | 70 | |
| 5 | 1975 | 70 | |
| 6 | 1989 | 69 | |
| 7 | 1982 | 68 | |
| 8 | 1974 | 62 | |
| 9 | 2002 | 57 | |
| 10 | 1992 | 52 | |
| 11 | Serum hepatocyte growth factor and interleukin-6 are effective prognostic markers for non-small cell lung cancer. | 2012 | 43 |
| 12 | Stimulation by interferon of induction of differentiation of mouse myeloid leukemic cells. | 1980 | 42 |
| 13 | 1984 | 40 | |
| 14 | 1986 | 39 | |
| 15 | 1977 | 38 | |
| 16 | 1999 | 38 | |
| 17 | 2001 | 33 | |
| 18 | 1994 | 33 | |
| 19 | 2005 | 32 | |
| 20 | 1989 | 30 |
About Mikio Tomida
Mikio Tomida is a scholar working on Molecular Biology, Oncology, Immunology, Organic Chemistry and Hematology, having authored 61 papers that have together received 1.8k indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (20 papers), Glycosylation and Glycoproteins Research (8 papers), RNA Interference and Gene Delivery (8 papers), Immune Cell Function and Interaction (7 papers), Reproductive System and Pregnancy (6 papers), Carbohydrate Chemistry and Synthesis (6 papers), Immune Response and Inflammation (6 papers) and Proteoglycans and glycosaminoglycans research (5 papers). The work is most often cited by research in Immunology (561 citations), Oncology (668 citations), Geriatrics and Gerontology (46 citations), Cell Biology (225 citations) and Hematology (146 citations). Mikio Tomida has collaborated with scholars based in Japan, Germany and France. Frequent co-authors include Motoo Hozumi, Yuri Yamamoto-Yamaguchi, Tetsuo Ono, Yuri Yamamoto, Kinji Inoue, Takashi Yokota, Takeshi Saito, Hirohiko Akiyama, Chihiro Mogi and Chisato Miyaura. Their work appears in journals such as FEBS Letters, Leukemia Research, Biochemical and Biophysical Research Communications, Journal of Cellular Physiology and The Journal of Biochemistry.
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.