Jin Gohda
Impact in
- Immunology top 2%
- Immune Response and Inflammation
- interferon and immune responses
- Cancer Research top 2%
- NF-κB Signaling Pathways
Papers in
-
- NF-κB Signaling Pathways 23
- Immunology 23
- Immune Response and Inflammation 12
- interferon and immune responses 11
- T-cell and Retrovirus Studies 4
- Co-authors
- Jun‐ichiro Inoue (41 shared papers)Taishin Akiyama (13 shared papers)Kentaro Semba (10 shared papers)Takayuki Matsumura (3 shared papers)Takako Koga (2 shared papers)Hiroshi Takayanagi (2 shared papers)Mizuki Yamamoto (9 shared papers)Hiroyasu Nakano (3 shared papers)
- Journals
- Biochemical and Biophysical Research Communications (5 papers)Scientific Reports (4 papers)PLoS ONE (4 papers)Genes to Cells (3 papers)The Journal of Biochemistry (2 papers)
- Partner nations
- JapanUnited StatesChina
In The Last Decade
Jin Gohda
48 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 111
- Immunology 919
- Cancer Research 629
- Infectious Diseases 296
- Molecular Biology 1.1k
- Oncology 347
Countries citing papers authored by Jin Gohda
This map shows the geographic impact of Jin Gohda'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 Jin Gohda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jin Gohda more than expected).
Fields of papers citing papers by Jin Gohda
This network shows the impact of papers produced by Jin Gohda. 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 Jin Gohda. The network helps show where Jin Gohda may publish in the future.
Co-authors
The 25 scholars most cited alongside Jin Gohda, 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 48 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2004 | 254 | |
| 2 | 2007 | 201 | |
| 3 | 2005 | 192 | |
| 4 | 2005 | 189 | |
| 5 | 2020 | 181 | |
| 6 | 2012 | 142 | |
| 7 | 2009 | 112 | |
| 8 | 2009 | 103 | |
| 9 | 2010 | 101 | |
| 10 | 2007 | 92 | |
| 11 | 2003 | 79 | |
| 12 | 2015 | 78 | |
| 13 | 2012 | 54 | |
| 14 | 2021 | 50 | |
| 15 | 2017 | 44 | |
| 16 | 2003 | 41 | |
| 17 | 2008 | 37 | |
| 18 | 2017 | 35 | |
| 19 | 2009 | 35 | |
| 20 | 2021 | 32 |
About Jin Gohda
Jin Gohda is a scholar working on Cancer Research, Immunology, Molecular Biology, Infectious Diseases and Oncology, having authored 48 papers that have together received 2.5k indexed citations. Recurring topics across this work include NF-κB Signaling Pathways (23 papers), Immune Response and Inflammation (12 papers), interferon and immune responses (11 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Bone Metabolism and Diseases (6 papers), Cytokine Signaling Pathways and Interactions (5 papers), Cell death mechanisms and regulation (5 papers) and T-cell and Retrovirus Studies (4 papers). The work is most often cited by research in Immunology (919 citations), Cancer Research (629 citations), Infectious Diseases (296 citations), Molecular Biology (1.1k citations) and Oncology (347 citations). Jin Gohda has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Jun‐ichiro Inoue, Taishin Akiyama, Kentaro Semba, Takayuki Matsumura, Takako Koga, Hiroshi Takayanagi, Mizuki Yamamoto, Hiroyasu Nakano, T. Akiyama and Sakae Tanaka. Their work appears in journals such as Biochemical and Biophysical Research Communications, Scientific Reports, PLoS ONE, Genes to Cells 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.