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
-
- RNA Interference and Gene Delivery 8
- Glycosylation and Glycoproteins Research 8
- Oncology 23
- Cytokine Signaling Pathways and Interactions 20
- Co-authors
- Motoo Hozumi (33 shared papers)Yuri Yamamoto-Yamaguchi (12 shared papers)Tetsuo Ono (5 shared papers)Hidenori Koyama (5 shared papers)Yuri Yamamoto (13 shared papers)Kinji Inoue (4 shared papers)Takashi Yokota (2 shared papers)Hirohiko Akiyama (3 shared papers)
In The Last Decade
Mikio Tomida
61 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 95
- Immunology 581
- Oncology 685
- Cell Biology 230
- Molecular Biology 929
- Hematology 148
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 62 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1984 | 276 | |
| 2 | 1986 | 104 | |
| 3 | 2007 | 75 | |
| 4 | 2009 | 70 | |
| 5 | 1975 | 70 | |
| 6 | 1989 | 69 | |
| 7 | 1982 | 68 | |
| 8 | 1974 | 62 | |
| 9 | 2002 | 56 | |
| 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 | 1999 | 39 | |
| 16 | 1977 | 38 | |
| 17 | 1994 | 33 | |
| 18 | 2001 | 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 62 papers that have together received 1.8k indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (20 papers), RNA Interference and Gene Delivery (8 papers), Glycosylation and Glycoproteins Research (8 papers), Immune Cell Function and Interaction (7 papers), Immune Response and Inflammation (6 papers), Carbohydrate Chemistry and Synthesis (6 papers), Reproductive System and Pregnancy (6 papers) and Proteoglycans and glycosaminoglycans research (5 papers). The work is most often cited by research in Immunology (581 citations), Oncology (685 citations), Cell Biology (230 citations), Molecular Biology (929 citations) and Hematology (148 citations). Mikio Tomida has collaborated with scholars based in Japan, Germany and France. Frequent co-authors include Motoo Hozumi, Yuri Yamamoto-Yamaguchi, Tetsuo Ono, Hidenori Koyama, Yuri Yamamoto, Kinji Inoue, Takashi Yokota, Hirohiko Akiyama, Takeshi Saito and Chihiro Mogi. Their work appears in journals such as FEBS Letters, Leukemia Research, Journal of Cellular Physiology, Biochemical and Biophysical Research Communications 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.