KEIICHI MATSUO
- Endocrinology, Diabetes and Metabolism top 2%
- Oncology top 5%
- Molecular Biology
- Genetics top 10%
- Pathology and Forensic Medicine top 10%
- Co-authors
- James A. FaginShanhong TangH. Phillip KoefflerD.L. ChenHiroyuki NambaR. GutmanShigenobu NagatakiPablo V. Gejman
- Topics
- Thyroid Cancer Diagnosis and Treatment (7 papers)Growth Hormone and Insulin-like Growth Factors (5 papers)Cancer-related Molecular Pathways (5 papers)
- Journals
- Journal of Clinical InvestigationThe Journal of Clinical Endocrinology & MetabolismEndocrinology
- Partner nations
- United StatesJapanArgentina
In The Last Decade
KEIICHI MATSUO
15 papers receiving 1.0k citations
Hit Papers
Peers
Comparison fields: 5 of 60
- Endocrinology, Diabetes and Metabolism 737
- Oncology 507
- Molecular Biology 405
- Genetics 221
- Pathology and Forensic Medicine 216
Countries citing papers authored by KEIICHI MATSUO
This map shows the geographic impact of KEIICHI MATSUO'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 KEIICHI MATSUO with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites KEIICHI MATSUO more than expected).
Fields of papers citing papers by KEIICHI MATSUO
This network shows the impact of papers produced by KEIICHI MATSUO. 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 KEIICHI MATSUO. The network helps show where KEIICHI MATSUO may publish in the future.
Co-authorship network of co-authors of KEIICHI MATSUO
This figure shows the co-authorship network connecting the top 25 collaborators of KEIICHI MATSUO. A scholar is included among the top collaborators of KEIICHI MATSUO 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 KEIICHI MATSUO. KEIICHI MATSUO is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 20 | |
| 2 | 2 | |
| 3 | 23 | |
| 4 | 64 | |
| 5 | 23 | |
| 6 | High prevalence of mutations of the p53 gene in poorly differentiated human thyroid carcinomas.breakdown → | 534 |
| 7 | Lack of expression of tumor-suppressor genes in human malignant glioma cell lines. | 33 |
| 8 | 63 | |
| 9 | 117 | |
| 10 | 87 | |
| 11 | 16 | |
| 12 | 34 | |
| 13 | 24 | |
| 14 | 23 | |
| 15 | 7 |
About KEIICHI MATSUO
KEIICHI MATSUO is a scholar working on Endocrinology, Diabetes and Metabolism, Cancer Research and Oncology, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (7 papers), Growth Hormone and Insulin-like Growth Factors (5 papers) and Cancer-related Molecular Pathways (5 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (737 citations), Oncology (507 citations) and Pathology and Forensic Medicine (216 citations). KEIICHI MATSUO has collaborated with scholars based in United States, Japan and Argentina. Frequent co-authors include James A. Fagin, Shanhong Tang, H. Phillip Koeffler, D.L. Chen, Hiroyuki Namba, R. Gutman, Shigenobu Nagataki, Pablo V. Gejman, Eitan Friedman and Shunichi Yamashita. Their work appears in journals such as Journal of Clinical Investigation, The Journal of Clinical Endocrinology & Metabolism and Endocrinology.
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.