Masatoshi Nomura
- Physiology top 0.5%
- Adenosine and Purinergic Signaling 12
- Reproductive Medicine top 1%
- Molecular Biology top 1%
- Mitochondrial Function and Pathology 14
- TGF-β signaling in diseases 10
- Oncology top 1%
- Clinical Biochemistry top 0.5%
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- Pituitary Gland Disorders and Treatments 16
- Hormonal Regulation and Hypertension 11
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- Estrogen and related hormone effects 14
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- Adrenal and Paraganglionic Tumors 14
- Pancreatic function and diabetes 14
Masatoshi Nomura
198 papers receiving 11.2k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Physiology 430
- Reproductive Medicine 747
- Molecular Biology 5.9k
- Oncology 2.1k
- Clinical Biochemistry 523
Countries citing papers authored by Masatoshi Nomura
This map shows the geographic impact of Masatoshi Nomura'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 Masatoshi Nomura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masatoshi Nomura more than expected).
Fields of papers citing papers by Masatoshi Nomura
This network shows the impact of papers produced by Masatoshi Nomura. 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 Masatoshi Nomura. The network helps show where Masatoshi Nomura may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Masatoshi Nomura, 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 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 1 | |
| 5 | 2023 | 9 | |
| 6 | 2021 | 21 | |
| 7 | 2021 | 1 | |
| 8 | 2020 | 10 | |
| 9 | 2020 | 0 | |
| 10 | 2019 | 5 | |
| 11 | 2017 | 90 | |
| 12 | 2017 | 15 | |
| 13 | 2016 | 48 | |
| 14 | Comparative proteomic analysis of two rice cultivars (Oryza sativa L.) contrasting in brown planthopper (BPH) stress resistance. | 2015 | 9 |
| 15 | 2015 | 3 | |
| 16 | P-047 The role of VNUT in taste translation | 2013 | 1 |
| 17 | 2013 | 62 | |
| 18 | Combination of the two ROR response elements in the Bmal1 promoter confers robustness to the mouse Bmal1 oscillation | 2005 | 1 |
| 19 | HIGH LEVEL EXPRESSION OF MAIZE C4-SPECIFIC PYRUVATE, Pi DIKINASE AND ITS LIGHT ACTIVATION IN TRANSGENIC RICE PLANTS | 1999 | 10 |
| 20 | HLA-DQB1 genotyping by a modified PCR-SSCP method combined with group-specific primers | 1991 | 101 |
About Masatoshi Nomura
Masatoshi Nomura is a scholar working on Physiology, Endocrinology, Diabetes and Metabolism and Molecular Biology, having authored 213 papers that have together received 11.4k indexed citations. Recurring topics across this work include Pituitary Gland Disorders and Treatments (16 papers), Estrogen and related hormone effects (14 papers), Adrenal and Paraganglionic Tumors (14 papers), Mitochondrial Function and Pathology (14 papers), Pancreatic function and diabetes (14 papers), Adenosine and Purinergic Signaling (12 papers), Hormonal Regulation and Hypertension (11 papers) and TGF-β signaling in diseases (10 papers). The work is most often cited by research in Physiology (430 citations), Reproductive Medicine (747 citations) and Molecular Biology (5.9k citations). Masatoshi Nomura has collaborated with scholars based in Japan, United States and China. Frequent co-authors include Ryoichi Takayanagi, Katsuyoshi Mihara, Hidetaka Morinaga, Hajime Nawata, Lin Li, Shinichi Toyooka, Takehiko Fujisawa, Joachim Herz, Jack A. Roth and J D Minna. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.
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.