Jun Kido
Impact in
- Clinical Biochemistry top 0.5%
- Metabolism and Genetic Disorders
- Biochemistry top 5%
- Amino Acid Enzymes and Metabolism
Papers in
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- Metabolism and Genetic Disorders 34
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- Mitochondrial Function and Pathology 9
- Co-authors
- Kimitoshi Nakamura (68 shared papers)Fumio Endo (26 shared papers)Hiroshi Mitsubuchi (21 shared papers)Shirou Matsumoto (8 shared papers)Shirou Matsumoto (32 shared papers)Johannes Häberle (8 shared papers)Keishin Sugawara (23 shared papers)Ken Momosaki (14 shared papers)
- Journals
- Journal of Inherited Metabolic Disease (6 papers)International Archives of Allergy and Immunology (4 papers)Molecular Genetics and Metabolism (3 papers)Pediatric Transplantation (3 papers)Orphanet Journal of Rare Diseases (2 papers)
- Partner nations
- JapanSwitzerlandUnited Kingdom
In The Last Decade
Jun Kido
74 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 98
- Clinical Biochemistry 452
- Biochemistry 146
- Hepatology 148
- Physiology 345
- Rheumatology 197
Countries citing papers authored by Jun Kido
This map shows the geographic impact of Jun Kido'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 Jun Kido with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kido more than expected).
Fields of papers citing papers by Jun Kido
This network shows the impact of papers produced by Jun Kido. 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 Jun Kido. The network helps show where Jun Kido may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Kido, 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 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 133 | |
| 2 | 1999 | 132 | |
| 3 | 2017 | 85 | |
| 4 | 2011 | 83 | |
| 5 | 2020 | 46 | |
| 6 | 2020 | 43 | |
| 7 | 2019 | 39 | |
| 8 | 2019 | 32 | |
| 9 | 2006 | 31 | |
| 10 | 2014 | 28 | |
| 11 | 2013 | 23 | |
| 12 | 2022 | 23 | |
| 13 | 2018 | 22 | |
| 14 | 2016 | 21 | |
| 15 | 2022 | 20 | |
| 16 | 2023 | 19 | |
| 17 | 2017 | 18 | |
| 18 | 2021 | 18 | |
| 19 | 2016 | 17 | |
| 20 | 2016 | 17 |
About Jun Kido
Jun Kido is a scholar working on Clinical Biochemistry, Molecular Biology, Physiology, Pediatrics, Perinatology and Child Health and Biochemistry, having authored 82 papers that have together received 1.2k indexed citations. Recurring topics across this work include Metabolism and Genetic Disorders (34 papers), Lysosomal Storage Disorders Research (15 papers), Neonatal Health and Biochemistry (14 papers), Amino Acid Enzymes and Metabolism (12 papers), Carbohydrate Chemistry and Synthesis (9 papers), Mitochondrial Function and Pathology (9 papers), Food Allergy and Anaphylaxis Research (9 papers) and Glycogen Storage Diseases and Myoclonus (9 papers). The work is most often cited by research in Clinical Biochemistry (452 citations), Biochemistry (146 citations), Hepatology (148 citations), Physiology (345 citations) and Rheumatology (197 citations). Jun Kido has collaborated with scholars based in Japan, Switzerland and United Kingdom. Frequent co-authors include Kimitoshi Nakamura, Fumio Endo, Hiroshi Mitsubuchi, Shirou Matsumoto, Shirou Matsumoto, Johannes Häberle, Keishin Sugawara, Ken Momosaki, José Ignacio Santos and Laura Rivera. Their work appears in journals such as Journal of Inherited Metabolic Disease, International Archives of Allergy and Immunology, Molecular Genetics and Metabolism, Pediatric Transplantation and Orphanet Journal of Rare Diseases.
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.