Shinji Maeda
- Immunology top 5%
- Immune Cell Function and Interaction 8
- T-cell and B-cell Immunology 7
- Immunotherapy and Immune Responses 3
- Rheumatology top 5%
- Hematology top 5%
- Autoimmune and Inflammatory Disorders Research 7
- Dermatology top 5%
- Physiology top 10%
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- Tuberculosis Research and Epidemiology 5
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- Infectious Diseases and Tuberculosis 5
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- Systemic Sclerosis and Related Diseases 4
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- Mycobacterium research and diagnosis 3
- Co-authors
- Shimon SakaguchiMotomu HashimotoNoriko SakaguchiKeiji HirotaHiroyuki YoshitomiTakashi NomuraHiromu ItoTomoyuki Yamaguchi
- Cited by
- ImmunologyRheumatologyHematology
- Journals
- Modern Rheumatology (9 papers)The Journal of Experimental Medicine (2 papers)PLoS ONE (2 papers)
- Partner nations
- JapanUnited StatesSweden
In The Last Decade
Shinji Maeda
36 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 97
- Immunology 901
- Rheumatology 288
- Hematology 152
- Dermatology 85
- Physiology 37
Countries citing papers authored by Shinji Maeda
This map shows the geographic impact of Shinji Maeda'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 Shinji Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shinji Maeda more than expected).
Fields of papers citing papers by Shinji Maeda
This network shows the impact of papers produced by Shinji Maeda. 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 Shinji Maeda. The network helps show where Shinji Maeda may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Shinji Maeda, 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 | 2023 | 6 | |
| 2 | 2022 | 3 | |
| 3 | 2019 | 16 | |
| 4 | 2019 | 22 | |
| 5 | 2018 | 7 | |
| 6 | 2017 | 12 | |
| 7 | 2014 | 27 | |
| 8 | 2014 | 13 | |
| 9 | 2013 | 6 | |
| 10 | 2011 | 12 | |
| 11 | 2011 | 15 | |
| 12 | 2010 | 165 | |
| 13 | 2010 | 20 | |
| 14 | 2009 | 12 | |
| 15 | Preferential recruitment of CCR6-expressing Th17 cells to inflamed joints via CCL20 in rheumatoid arthritis and its animal modelbreakdown → | 2007 | 749 |
| 16 | 2007 | 78 | |
| 17 | 2007 | 6 | |
| 18 | 2007 | 19 | |
| 19 | 2005 | 9 | |
| 20 | Chronic morphine administration and in vivo pertussis toxin treatment induce hyperalgesia and enhance 3H-nitrendipine binding. | 1990 | 12 |
About Shinji Maeda
Shinji Maeda is a scholar working on Hematology, Immunology and Rheumatology, having authored 37 papers that have together received 1.4k indexed citations. Recurring topics across this work include Immune Cell Function and Interaction (8 papers), Autoimmune and Inflammatory Disorders Research (7 papers), T-cell and B-cell Immunology (7 papers), Tuberculosis Research and Epidemiology (5 papers), Infectious Diseases and Tuberculosis (5 papers), Systemic Sclerosis and Related Diseases (4 papers), Mycobacterium research and diagnosis (3 papers) and Immunotherapy and Immune Responses (3 papers). The work is most often cited by research in Immunology (901 citations), Rheumatology (288 citations) and Hematology (152 citations). Shinji Maeda has collaborated with scholars based in Japan, United States and Sweden. Frequent co-authors include Shimon Sakaguchi, Motomu Hashimoto, Noriko Sakaguchi, Keiji Hirota, Hiroyuki Yoshitomi, Takashi Nomura, Hiromu Ito, Tomoyuki Yamaguchi, Naoshi Sugimoto and Takashi Nakamura. Their work appears in journals such as Modern Rheumatology, The Journal of Experimental Medicine, PLoS ONE, Scientific Reports and Neuroscience.
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.