Tetsuya Taga
Impact in
- Immunology top 0.05%
- Immune Cell Function and Interaction
- Immune Response and Inflammation
- T-cell and B-cell Immunology
- Reproductive System and Pregnancy
- Oncology top 0.05%
- Cytokine Signaling Pathways and Interactions
Papers in
- Oncology 109
- Cytokine Signaling Pathways and Interactions 85
-
- Epigenetics and DNA Methylation 15
- Co-authors
- Tadamitsu Kishimoto (72 shared papers)Shizuo Akira (10 shared papers)Toshio Hirano (14 shared papers)Masashi Narazaki (13 shared papers)Kiyoshi Yasukawa (30 shared papers)Masahiko Hibi (13 shared papers)Kinichi Nakashima (27 shared papers)Shizuo Akira (2 shared papers)
- Journals
- Blood (15 papers)Proceedings of the National Academy of Sciences (14 papers)The Journal of Experimental Medicine (11 papers)Genes to Cells (10 papers)The Journal of Immunology (8 papers)
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Tetsuya Taga
245 papers receiving 35.4k citations
Tetsuya Taga's Hit Papers
Peers
Comparison fields: 5 of 171
- Immunology 12.9k
- Oncology 14.6k
- Developmental Neuroscience 2.1k
- Hematology 3.2k
- Cancer Research 3.7k
Countries citing papers authored by Tetsuya Taga
This map shows the geographic impact of Tetsuya Taga'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 Tetsuya Taga with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tetsuya Taga more than expected).
Fields of papers citing papers by Tetsuya Taga
This network shows the impact of papers produced by Tetsuya Taga. 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 Tetsuya Taga. The network helps show where Tetsuya Taga may publish in the future.
Co-authors
The 25 scholars most cited alongside Tetsuya Taga, 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 246 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Complementary DNA for a novel human interleukin (BSF-2) that induces B lymphocytes to produce immunoglobulin Hit paper breakdown → | 1986 | 1805 |
| 2 | Autocrine generation and requirement of BSF-2/IL-6 for human multiple myelomas Hit paper breakdown → | 1988 | 1414 |
| 3 | 1997 | 1239 | |
| 4 | Interleukin-6 triggers the association of its receptor with a possible signal transducer, gp130 Hit paper breakdown → | 1989 | 1217 |
| 5 | Interleukin-6 in Biology and Medicine Hit paper breakdown → | 1993 | 1170 |
| 6 | Molecular cloning and expression of an IL-6 signal transducer, gp130 Hit paper breakdown → | 1990 | 1143 |
| 7 | Cytokine signal transduction Hit paper breakdown → | 1994 | 1139 |
| 8 | Structure and function of a new STAT-induced STAT inhibitor Hit paper breakdown → | 1997 | 1124 |
| 9 | Biology of multifunctional cytokines: IL 6 and related molecules (IL 1 and TNF) Hit paper breakdown → | 1990 | 1119 |
| 10 | Interleukin-6 family of cytokines and gp130 Hit paper breakdown → | 1995 | 1074 |
| 11 | Cloning and Expression of the Human Interleukin-6 (BSF-2/IFNβ 2) Receptor Hit paper breakdown → | 1988 | 919 |
| 12 | Biological and clinical aspects of interleukin 6 Hit paper breakdown → | 1990 | 915 |
| 13 | Persistence of a small subpopulation of cancer stem-like cells in the C6 glioma cell line Hit paper breakdown → | 2004 | 800 |
| 14 | Interleukin-6 and Its Receptor: A Paradigm for Cytokines Hit paper breakdown → | 1992 | 765 |
| 15 | Synergistic Signaling in Fetal Brain by STAT3-Smad1 Complex Bridged by p300 Hit paper breakdown → | 1999 | 731 |
| 16 | Soluble interleukin-6 receptor triggers osteoclast formation by interleukin 6. Hit paper breakdown → | 1993 | 700 |
| 17 | IL-6-Induced Homodimerization of gp130 and Associated Activation of a Tyrosine Kinase Hit paper breakdown → | 1993 | 629 |
| 18 | CNTF and LIF act on neuronal cells via shared signaling pathways that involve the IL-6 signal transducing receptor component gp130 Hit paper breakdown → | 1992 | 593 |
| 19 | Purification to homogeneity and characterization of human B-cell differentiation factor (BCDF or BSFp-2). Hit paper breakdown → | 1985 | 589 |
| 20 | LIFRβ and gp130 as Heterodimerizing Signal Transducers of the Tripartite CNTF Receptor Hit paper breakdown → | 1993 | 556 |
About Tetsuya Taga
Tetsuya Taga is a scholar working on Oncology, Molecular Biology, Immunology, Cancer Research and Cell Biology, having authored 246 papers that have together received 36.4k indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (85 papers), Immune Cell Function and Interaction (33 papers), Reproductive System and Pregnancy (20 papers), Advanced MIMO Systems Optimization (17 papers), Neurogenesis and neuroplasticity mechanisms (17 papers), Millimeter-Wave Propagation and Modeling (16 papers), Epigenetics and DNA Methylation (15 papers) and Zebrafish Biomedical Research Applications (15 papers). The work is most often cited by research in Immunology (12.9k citations), Oncology (14.6k citations), Developmental Neuroscience (2.1k citations), Hematology (3.2k citations) and Cancer Research (3.7k citations). Tetsuya Taga has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Tadamitsu Kishimoto, Shizuo Akira, Toshio Hirano, Masashi Narazaki, Kiyoshi Yasukawa, Masahiko Hibi, Kinichi Nakashima, Shizuo Akira, Tadamitsu Kishimoto and Masaaki Murakami. Their work appears in journals such as Blood, Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine, Genes to Cells and The Journal of 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.