Kanako Suzuki
- Modeling and Simulation top 5%
- Mathematical Biology Tumor Growth 5
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- Nonlinear Dynamics and Pattern Formation 14
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- Advanced Mathematical Modeling in Engineering 5
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- Chaos control and synchronization 3
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- Differential Equations and Numerical Methods 3
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- Mathematical and Theoretical Epidemiology and Ecology Models 5
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- Gene Regulatory Network Analysis 3
- Lipid Membrane Structure and Behavior 2
- Co-authors
- Grzegorz KarchAnna Marciniak‐CzochraYoh ImaiIzumi TakagiWei‐Ming NiMiwa MisawaHiroyasu SakaiYoshihiko Chiba
- Cited by
- Modeling and SimulationComputer Networks and CommunicationsComputational Theory and Mathematics
In The Last Decade
Kanako Suzuki
30 papers receiving 280 citations
Peers
Comparison fields: 5 of 67
- Modeling and Simulation 59
- Computer Networks and Communications 104
- Computational Theory and Mathematics 55
- Statistical and Nonlinear Physics 41
- Numerical Analysis 15
Countries citing papers authored by Kanako Suzuki
This map shows the geographic impact of Kanako Suzuki'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 Kanako Suzuki with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanako Suzuki more than expected).
Fields of papers citing papers by Kanako Suzuki
This network shows the impact of papers produced by Kanako Suzuki. 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 Kanako Suzuki. The network helps show where Kanako Suzuki may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Kanako Suzuki, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 5 | |
| 2 | 2022 | 6 | |
| 3 | 2021 | 4 | |
| 4 | 2019 | 0 | |
| 5 | 2018 | 10 | |
| 6 | 2016 | 41 | |
| 7 | 2015 | 3 | |
| 8 | Unstable patterns in autocatalytic reaction-diffusion-ODE systems | 2013 | 2 |
| 9 | 2012 | 24 | |
| 10 | 2011 | 14 | |
| 11 | 2011 | 2 | |
| 12 | 2011 | 4 | |
| 13 | 2010 | 23 | |
| 14 | 2010 | 21 | |
| 15 | 2009 | 4 | |
| 16 | 2007 | 1 | |
| 17 | 2006 | 29 | |
| 18 | 2006 | 1 | |
| 19 | 2001 | 27 | |
| 20 | 1992 | 2 |
About Kanako Suzuki
Kanako Suzuki is a scholar working on Modeling and Simulation, Computer Networks and Communications and Numerical Analysis, having authored 31 papers that have together received 294 indexed citations. Recurring topics across this work include Nonlinear Dynamics and Pattern Formation (14 papers), Mathematical Biology Tumor Growth (5 papers), Advanced Mathematical Modeling in Engineering (5 papers), Mathematical and Theoretical Epidemiology and Ecology Models (5 papers), Differential Equations and Numerical Methods (3 papers), Gene Regulatory Network Analysis (3 papers), Chaos control and synchronization (3 papers) and Lipid Membrane Structure and Behavior (2 papers). The work is most often cited by research in Modeling and Simulation (59 citations), Computer Networks and Communications (104 citations) and Computational Theory and Mathematics (55 citations). Kanako Suzuki has collaborated with scholars based in Japan, Poland and Germany. Frequent co-authors include Grzegorz Karch, Anna Marciniak‐Czochra, Yoh Imai, Izumi Takagi, Wei‐Ming Ni, Miwa Misawa, Hiroyasu Sakai, Yoshihiko Chiba, Masaya Maeda and Yutaka Maruyama. Their work appears in journals such as Journal of Mathematical Analysis and Applications, Pharmacological Research and Optics Communications.
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.