Gen Kudo
Impact in
- Pharmacology top 5%
- Pharmacogenetics and Drug Metabolism
- Biochemistry top 10%
- Eicosanoids and Hypertension Pharmacology
Papers in
-
- Neuroinflammation and Neurodegeneration Mechanisms 3
- Traumatic Brain Injury and Neurovascular Disturbances 2
- Co-authors
- Frank J. GonzalezShioko KimuraHiroshi YokotaHarry V. GelboinYing‐Hue LeeTian J. YangMasaaki MiyataPedro M. Fernández‐Salguero
- Journals
- NeuroImage (3 papers)Annals of Nuclear Medicine (2 papers)Advances in experimental medicine and biology (1 paper)IEEE Robotics and Automation Letters (1 paper)Biochemical Pharmacology (1 paper)
- Partner nations
- JapanUnited StatesCanada
In The Last Decade
Gen Kudo
22 papers receiving 583 citations
Peers
Comparison fields: 5 of 99
- Pharmacology 103
- Biochemistry 59
- Immunology and Allergy 35
- Cellular and Molecular Neuroscience 90
- Neurology 40
Countries citing papers authored by Gen Kudo
This map shows the geographic impact of Gen Kudo'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 Gen Kudo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gen Kudo more than expected).
Fields of papers citing papers by Gen Kudo
This network shows the impact of papers produced by Gen Kudo. 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 Gen Kudo. The network helps show where Gen Kudo may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Gen Kudo, 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 | 2013 | 33 | |
| 3 | 2011 | 24 | |
| 4 | 2010 | 16 | |
| 5 | 2010 | 32 | |
| 6 | 2010 | 68 | |
| 7 | 2010 | 5 | |
| 8 | 2008 | 3 | |
| 9 | 2006 | 1 | |
| 10 | 2003 | 66 | |
| 11 | 2002 | 9 | |
| 12 | 2001 | 101 | |
| 13 | 1999 | 161 | |
| 14 | 1998 | 6 | |
| 15 | 1994 | 2 | |
| 16 | 1993 | 5 | |
| 17 | 1990 | 11 | |
| 18 | 1988 | 4 | |
| 19 | 1988 | 11 | |
| 20 | [Cancer of the breast implanted with foreign materials used for cosmetic and plastic surgery]. | 1971 | 1 |
About Gen Kudo
Gen Kudo is a scholar working on Developmental Neuroscience, Neurology, Cellular and Molecular Neuroscience, Hematology and Rheumatology, having authored 24 papers that have together received 596 indexed citations. Recurring topics across this work include Neuroscience and Neuropharmacology Research (4 papers), Folate and B Vitamins Research (4 papers), Neuroinflammation and Neurodegeneration Mechanisms (3 papers), Blood Coagulation and Thrombosis Mechanisms (3 papers), Pharmacogenetics and Drug Metabolism (2 papers), Traumatic Brain Injury and Neurovascular Disturbances (2 papers), Hemophilia Treatment and Research (2 papers) and S100 Proteins and Annexins (2 papers). The work is most often cited by research in Pharmacology (103 citations), Biochemistry (59 citations), Immunology and Allergy (35 citations), Cellular and Molecular Neuroscience (90 citations) and Neurology (40 citations). Gen Kudo has collaborated with scholars based in Japan, United States and Canada. Frequent co-authors include Frank J. Gonzalez, Shioko Kimura, Hiroshi Yokota, Harry V. Gelboin, Ying‐Hue Lee, Tian J. Yang, Masaaki Miyata, Pedro M. Fernández‐Salguero, Connie Cheung and Taro E. Akiyama. Their work appears in journals such as NeuroImage, Annals of Nuclear Medicine, Advances in experimental medicine and biology, IEEE Robotics and Automation Letters and Biochemical Pharmacology.
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.