Mayako Michino
- Molecular Biology top 10%
- Cellular and Molecular Neuroscience top 5%
- Computational Theory and Mathematics top 2%
- Radiology, Nuclear Medicine and Imaging top 10%
- Cell Biology top 10%
- Co-authors
- Lei ShiJonathan A. JavitchCharles L. BrooksPrashant DonthamsettiRaymond C. StevensAmy Hauck NewmanAnjana RaoJ. Aramburu
- Topics
- Receptor Mechanisms and Signaling (18 papers)Neuropeptides and Animal Physiology (9 papers)Computational Drug Discovery Methods (6 papers)
- Journals
- Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaImmunity
- Partner nations
- United StatesAustraliaGermany
In The Last Decade
Mayako Michino
32 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 100
- Molecular Biology 1.1k
- Cellular and Molecular Neuroscience 564
- Computational Theory and Mathematics 317
- Radiology, Nuclear Medicine and Imaging 145
- Cell Biology 131
Countries citing papers authored by Mayako Michino
This map shows the geographic impact of Mayako Michino'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 Mayako Michino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mayako Michino more than expected).
Fields of papers citing papers by Mayako Michino
This network shows the impact of papers produced by Mayako Michino. 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 Mayako Michino. The network helps show where Mayako Michino may publish in the future.
Co-authorship network of co-authors of Mayako Michino
This figure shows the co-authorship network connecting the top 25 collaborators of Mayako Michino. A scholar is included among the top collaborators of Mayako Michino 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 Mayako Michino. Mayako Michino 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 | 1 | |
| 3 | 3 | |
| 4 | 69 | |
| 5 | 7 | |
| 6 | 2 | |
| 7 | 17 | |
| 8 | 5 | |
| 9 | 41 | |
| 10 | 20 | |
| 11 | 17 | |
| 12 | 47 | |
| 13 | 49 | |
| 14 | 96 | |
| 15 | 92 | |
| 16 | 56 | |
| 17 | 7 | |
| 18 | 238 | |
| 19 | 23 | |
| 20 | 207 |
About Mayako Michino
Mayako Michino is a scholar working on Cellular and Molecular Neuroscience, Biochemistry and Molecular Biology, having authored 32 papers that have together received 1.4k indexed citations. Recurring topics across this work include Receptor Mechanisms and Signaling (18 papers), Neuropeptides and Animal Physiology (9 papers) and Computational Drug Discovery Methods (6 papers). The work is most often cited by research in Cellular and Molecular Neuroscience (564 citations), Computational Theory and Mathematics (317 citations) and Molecular Biology (1.1k citations). Mayako Michino has collaborated with scholars based in United States, Australia and Germany. Frequent co-authors include Lei Shi, Jonathan A. Javitch, Charles L. Brooks, Prashant Donthamsetti, Raymond C. Stevens, Amy Hauck Newman, Anjana Rao, J. Aramburu, Andrew S. Rakeman and Lei Jin. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Immunity.
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.