Masashi Kuroda
- Physiology top 10%
- Molecular Biology
- Epidemiology
- Cancer Research
- Cardiology and Cardiovascular Medicine
- Co-authors
- Hiroshi SakaueRie TsutsumiVictoria H. MellerKazuhiro KimuraMasayuki SaitoAyumi TsubotaYuko Okamatsu‐OguraYihai Cao
- Topics
- Adipose Tissue and Metabolism (9 papers)Biochemical Analysis and Sensing Techniques (6 papers)Adipokines, Inflammation, and Metabolic Diseases (5 papers)
- Cited by
- PhysiologyAgingRehabilitation
- Partner nations
- JapanUnited KingdomUnited States
In The Last Decade
Masashi Kuroda
37 papers receiving 580 citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Physiology 235
- Molecular Biology 204
- Epidemiology 146
- Cancer Research 69
- Cardiology and Cardiovascular Medicine 64
Countries citing papers authored by Masashi Kuroda
This map shows the geographic impact of Masashi Kuroda'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 Masashi Kuroda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masashi Kuroda more than expected).
Fields of papers citing papers by Masashi Kuroda
This network shows the impact of papers produced by Masashi Kuroda. 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 Masashi Kuroda. The network helps show where Masashi Kuroda may publish in the future.
Co-authorship network of co-authors of Masashi Kuroda
This figure shows the co-authorship network connecting the top 25 collaborators of Masashi Kuroda. A scholar is included among the top collaborators of Masashi Kuroda based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Masashi Kuroda. Masashi Kuroda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | Brown-fat-mediated tumour suppression by cold-altered global metabolismbreakdown → | 148 |
| 5 | 2 | |
| 6 | 15 | |
| 7 | 41 | |
| 8 | 2 | |
| 9 | 74 | |
| 10 | 16 | |
| 11 | 7 | |
| 12 | 5 | |
| 13 | 13 | |
| 14 | 83 | |
| 15 | [Role of vitamin D and calcium in obesity and type 2 diabetes]. | 7 |
| 16 | 3 | |
| 17 | 9 | |
| 18 | 40 | |
| 19 | 18 | |
| 20 | CLINICAL OBSERVATIONS AND HLA ANALYSES OF PATIENTS WITH LUPUS NEPHRITIS IN CHILDREN | 2 |
About Masashi Kuroda
Masashi Kuroda is a scholar working on Sensory Systems, Hepatology and Physiology, having authored 38 papers that have together received 595 indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (9 papers), Biochemical Analysis and Sensing Techniques (6 papers) and Adipokines, Inflammation, and Metabolic Diseases (5 papers). The work is most often cited by research in Physiology (235 citations), Aging (10 citations) and Rehabilitation (38 citations). Masashi Kuroda has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Hiroshi Sakaue, Rie Tsutsumi, Victoria H. Meller, Kazuhiro Kimura, Masayuki Saito, Ayumi Tsubota, Yuko Okamatsu‐Ogura, Yihai Cao, Jing Xu and Sisi Xie. Their work appears in journals such as Nature, SHILAP Revista de lepidopterología and PLoS ONE.
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.