Masaki Ikeda
- Molecular Biology
- Artificial Intelligence
- Physiology
- Management Science and Operations Research top 10%
- Cellular and Molecular Neuroscience
- Co-authors
- Shingo OnoIssei SatoHiroshi NakagawaTakeshi KawarabayashiMikio ShojiHiroo ImuraYutaka SeinoMinoru Yoshida
- Topics
- Data Quality and Management (3 papers)Metabolism, Diabetes, and Cancer (3 papers)Alzheimer's disease research and treatments (2 papers)
- Cited by
- Management Science and Operations ResearchBiological PsychiatryEndocrinology, Diabetes and Metabolism
- Partner nations
- JapanChinaUnited States
In The Last Decade
Masaki Ikeda
20 papers receiving 319 citations
Peers
Comparison fields: 5 of 82
- Molecular Biology 104
- Artificial Intelligence 68
- Physiology 67
- Management Science and Operations Research 54
- Cellular and Molecular Neuroscience 50
Countries citing papers authored by Masaki Ikeda
This map shows the geographic impact of Masaki Ikeda'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 Masaki Ikeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Masaki Ikeda more than expected).
Fields of papers citing papers by Masaki Ikeda
This network shows the impact of papers produced by Masaki Ikeda. 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 Masaki Ikeda. The network helps show where Masaki Ikeda may publish in the future.
Co-authorship network of co-authors of Masaki Ikeda
This figure shows the co-authorship network connecting the top 25 collaborators of Masaki Ikeda. A scholar is included among the top collaborators of Masaki Ikeda 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 Masaki Ikeda. Masaki Ikeda is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 6 | |
| 2 | 1 | |
| 3 | 21 | |
| 4 | 2 | |
| 5 | 8 | |
| 6 | 17 | |
| 7 | 45 | |
| 8 | 67 | |
| 9 | Person Name Disambiguation on the Web by Two-Stage Clustering | 30 |
| 10 | Improvement Recall of Person Name Disambiguation on the Web People Search by TwoStage Clustering | 1 |
| 11 | 27 | |
| 12 | 1 | |
| 13 | 38 | |
| 14 | 13 | |
| 15 | 5 | |
| 16 | 17 | |
| 17 | 5 | |
| 18 | 3 | |
| 19 | 10 | |
| 20 | 20 |
About Masaki Ikeda
Masaki Ikeda is a scholar working on Structural Biology, Endocrine and Autonomic Systems and Management Science and Operations Research, having authored 20 papers that have together received 337 indexed citations. Recurring topics across this work include Data Quality and Management (3 papers), Metabolism, Diabetes, and Cancer (3 papers) and Alzheimer's disease research and treatments (2 papers). The work is most often cited by research in Management Science and Operations Research (54 citations), Biological Psychiatry (8 citations) and Endocrinology, Diabetes and Metabolism (49 citations). Masaki Ikeda has collaborated with scholars based in Japan, China and United States. Frequent co-authors include Shingo Ono, Issei Sato, Hiroshi Nakagawa, Takeshi Kawarabayashi, Mikio Shoji, Hiroo Imura, Yutaka Seino, Minoru Yoshida, Masato Hosokawa and Manabu Nakashima. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, Diabetes and Brain Research.
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.