Masayoshi Yada
- Molecular Biology top 5%
- Oncology top 5%
- Epidemiology top 5%
- Cell Biology top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Co-authors
- Shigetsugu HatakeyamaN. IshidaKeiichi I. NakayamaMasaki MatsumotoKei-ichi NakayamaTakumi KamuraKeiko NakayamaHiroyuki Imaki
- Topics
- Liver Disease Diagnosis and Treatment (18 papers)Ubiquitin and proteasome pathways (10 papers)Hepatocellular Carcinoma Treatment and Prognosis (10 papers)
- Cited by
- AgingOncologyMolecular Biology
- Journals
- Proceedings of the National Academy of SciencesJournal of Biological ChemistryThe EMBO Journal
- Partner nations
- JapanUnited StatesFrance
In The Last Decade
Masayoshi Yada
41 papers receiving 3.1k citations
Hit Papers
Peers
Comparison fields: 5 of 96
- Molecular Biology 2.1k
- Oncology 863
- Epidemiology 861
- Cell Biology 446
- Endocrinology, Diabetes and Metabolism 308
Countries citing papers authored by Masayoshi Yada
This map shows the geographic impact of Masayoshi Yada'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 Masayoshi Yada with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masayoshi Yada more than expected).
Fields of papers citing papers by Masayoshi Yada
This network shows the impact of papers produced by Masayoshi Yada. 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 Masayoshi Yada. The network helps show where Masayoshi Yada may publish in the future.
Co-authorship network of co-authors of Masayoshi Yada
This figure shows the co-authorship network connecting the top 25 collaborators of Masayoshi Yada. A scholar is included among the top collaborators of Masayoshi Yada 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 Masayoshi Yada. Masayoshi Yada is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 14 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 4 | |
| 9 | 1 | |
| 10 | 31 | |
| 11 | 1 | |
| 12 | 14 | |
| 13 | 2 | |
| 14 | 35 | |
| 15 | Phosphorylation‐dependent degradation of c‐Myc is mediated by the F‐box protein Fbw7breakdown → | 660 |
| 16 | 250 | |
| 17 | 54 | |
| 18 | 63 | |
| 19 | 471 | |
| 20 | [A case of multiple myeloma associated with gastric cancer, rectal cancer and myelomatous pleural effusion in the terminal stage]. | 2 |
About Masayoshi Yada
Masayoshi Yada is a scholar working on Hepatology, Epidemiology and Aging, having authored 45 papers that have together received 3.1k indexed citations. Recurring topics across this work include Liver Disease Diagnosis and Treatment (18 papers), Ubiquitin and proteasome pathways (10 papers) and Hepatocellular Carcinoma Treatment and Prognosis (10 papers). The work is most often cited by research in Aging (61 citations), Oncology (863 citations) and Molecular Biology (2.1k citations). Masayoshi Yada has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Shigetsugu Hatakeyama, N. Ishida, Keiichi I. Nakayama, Masaki Matsumoto, Kei-ichi Nakayama, Takumi Kamura, Keiko Nakayama, Hiroyuki Imaki, Ryosuke Tsunematsu and Masaaki Nishiyama. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The EMBO Journal.
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.