Eiji Watanabe
- Molecular Biology top 10%
- Cellular and Molecular Neuroscience top 5%
- Cell Biology top 2%
- Social Psychology top 5%
- Epidemiology
- Co-authors
- Masaharu NodaTakeshi Y. HiyamaNobuaki MaedaF. MatsuiFumiko MatsuiAkihiro FujikawaYoichi KushimaHaruo Okado
- Topics
- Proteoglycans and glycosaminoglycans research (11 papers)Glycosylation and Glycoproteins Research (10 papers)Neural Networks and Applications (7 papers)
- Partner nations
- JapanUnited StatesItaly
In The Last Decade
Eiji Watanabe
85 papers receiving 2.3k citations
Peers
Comparison fields: 5 of 142
- Molecular Biology 929
- Cellular and Molecular Neuroscience 559
- Cell Biology 556
- Social Psychology 228
- Epidemiology 192
Countries citing papers authored by Eiji Watanabe
This map shows the geographic impact of Eiji Watanabe'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 Eiji Watanabe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eiji Watanabe more than expected).
Fields of papers citing papers by Eiji Watanabe
This network shows the impact of papers produced by Eiji Watanabe. 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 Eiji Watanabe. The network helps show where Eiji Watanabe may publish in the future.
Co-authorship network of co-authors of Eiji Watanabe
This figure shows the co-authorship network connecting the top 25 collaborators of Eiji Watanabe. A scholar is included among the top collaborators of Eiji Watanabe 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 Eiji Watanabe. Eiji Watanabe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 4 | |
| 6 | 44 | |
| 7 | 26 | |
| 8 | Analysis of Behaviors by Students in e-Learning -- Discrimination between reading and writing behaviors by image processing | 1 |
| 9 | Analysis of movements of students in e-Learning -- Relations between eyes movements and understanding | 0 |
| 10 | 157 | |
| 11 | 81 | |
| 12 | Wide-field Monitoring of the Galactic Plane in the K- and the H-band | 1 |
| 13 | 8 | |
| 14 | 39 | |
| 15 | 134 | |
| 16 | A Prediction Method of Non-Stationary Time Series Data by Using a Modular Structured Neural Network (Special Section on Signal Processing for Nonstationary Processes Based on Modelling) | 6 |
| 17 | 2 | |
| 18 | 10 | |
| 19 | 59 | |
| 20 | 20 |
About Eiji Watanabe
Eiji Watanabe is a scholar working on Immunology and Allergy, Cell Biology and Developmental Neuroscience, having authored 93 papers that have together received 2.3k indexed citations. Recurring topics across this work include Proteoglycans and glycosaminoglycans research (11 papers), Glycosylation and Glycoproteins Research (10 papers) and Neural Networks and Applications (7 papers). The work is most often cited by research in Developmental Neuroscience (177 citations), Cell Biology (556 citations) and Cellular and Molecular Neuroscience (559 citations). Eiji Watanabe has collaborated with scholars based in Japan, United States and Italy. Frequent co-authors include Masaharu Noda, Takeshi Y. Hiyama, Nobuaki Maeda, F. Matsui, Fumiko Matsui, Akihiro Fujikawa, Yoichi Kushima, Haruo Okado, Atsuhiko Oohira and Fujio Murakami. Their work appears in journals such as Journal of Biological Chemistry, Nature Communications and Neuron.
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.