Hideki Murakawa

457 total citations
28 papers, 285 citations indexed

About

Hideki Murakawa is a scholar working on Computational Theory and Mathematics, Numerical Analysis and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Hideki Murakawa has authored 28 papers receiving a total of 285 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computational Theory and Mathematics, 10 papers in Numerical Analysis and 10 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Hideki Murakawa's work include Advanced Mathematical Modeling in Engineering (13 papers), Differential Equations and Numerical Methods (10 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (10 papers). Hideki Murakawa is often cited by papers focused on Advanced Mathematical Modeling in Engineering (13 papers), Differential Equations and Numerical Methods (10 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (10 papers). Hideki Murakawa collaborates with scholars based in Japan, United Kingdom and France. Hideki Murakawa's co-authors include Hideru Togashi, Hirokazu Ninomiya, José A. Carrillo, Makoto Sato, Yuki Matsunaga, Mariko Noda, Kanehiro Hayashi, Takashi Miura, Ken‐ichiro Kubo and Kazunori Nakajima and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Neuroscience and Journal of Theoretical Biology.

In The Last Decade

Hideki Murakawa

24 papers receiving 263 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Hideki Murakawa Japan 10 105 85 66 56 55 28 285
Nicole Cusimano Spain 9 92 0.9× 19 0.2× 25 0.4× 12 0.2× 84 1.5× 17 269
Hartmut Schwetlick United Kingdom 10 51 0.5× 30 0.4× 58 0.9× 43 0.8× 67 1.2× 24 316
Jingyu Li China 13 180 1.7× 41 0.5× 129 2.0× 64 1.1× 102 1.9× 40 473
Dietmar Oelz Austria 12 93 0.9× 12 0.1× 46 0.7× 176 3.1× 98 1.8× 36 365
Je-Chiang Tsai Taiwan 11 85 0.8× 159 1.9× 17 0.3× 7 0.1× 33 0.6× 33 309
Etsushi Nakaguchi Japan 9 151 1.4× 30 0.4× 46 0.7× 101 1.8× 245 4.5× 18 363
Ritu Agarwal India 12 189 1.8× 25 0.3× 11 0.2× 111 2.0× 154 2.8× 44 450
Maya Mincheva United States 10 20 0.2× 20 0.2× 36 0.5× 17 0.3× 238 4.3× 21 317
Cristian Morales-Rodrigo Spain 12 341 3.2× 62 0.7× 167 2.5× 174 3.1× 152 2.8× 31 475

Countries citing papers authored by Hideki Murakawa

Since Specialization
Citations

This map shows the geographic impact of Hideki Murakawa'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 Hideki Murakawa with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hideki Murakawa more than expected).

Fields of papers citing papers by Hideki Murakawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hideki Murakawa. 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 Hideki Murakawa. The network helps show where Hideki Murakawa may publish in the future.

Co-authorship network of co-authors of Hideki Murakawa

This figure shows the co-authorship network connecting the top 25 collaborators of Hideki Murakawa. A scholar is included among the top collaborators of Hideki Murakawa 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 Hideki Murakawa. Hideki Murakawa is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Carrillo, José A., et al.. (2025). A new paradigm considering multicellular adhesion, repulsion and attraction represent diverse cellular tile patterns. PLoS Computational Biology. 21(4). e1011909–e1011909.
2.
Murakawa, Hideki, et al.. (2025). Keller–Segel type approximation for nonlocal Fokker–Planck equations in one-dimensional bounded domain. European Journal of Applied Mathematics. 1–37.
3.
Murakawa, Hideki, et al.. (2022). A numerical algorithm for modeling cellular rearrangements in tissue morphogenesis. Communications Biology. 5(1). 239–239. 2 indexed citations
4.
Carrillo, José A., et al.. (2019). A population dynamics model of cell-cell adhesion incorporating population pressure and density saturation. Oxford University Research Archive (ORA) (University of Oxford). 46 indexed citations
5.
Nakai, Yasuhiro, Rie Takayama, Hideki Murakawa, et al.. (2019). N-Cadherin Orchestrates Self-Organization of Neurons within a Columnar Unit in the Drosophila Medulla. Journal of Neuroscience. 39(30). 5861–5880. 22 indexed citations
6.
Murakawa, Hideki, et al.. (2018). Exact solutions of nonlinear diffusion-convection-reaction equation: A Lie symmetry analysis approach. Communications in Nonlinear Science and Numerical Simulation. 67. 253–263. 10 indexed citations
7.
Iida, Masato, et al.. (2017). Vanishing, moving and immovable interfaces in fast reaction limits. Journal of Differential Equations. 263(5). 2715–2735. 9 indexed citations
8.
Mainini, Edoardo, et al.. (2017). Carbon-Nanotube Geometries as Optimal Configurations. Multiscale Modeling and Simulation. 15(4). 1448–1471. 6 indexed citations
9.
Matsunaga, Yuki, Mariko Noda, Hideki Murakawa, et al.. (2017). Reelin transiently promotes N-cadherin–dependent neuronal adhesion during mouse cortical development. Proceedings of the National Academy of Sciences. 114(8). 2048–2053. 43 indexed citations
10.
Murakawa, Hideki. (2017). An efficient linear scheme to approximate nonlinear diffusion problems. Japan Journal of Industrial and Applied Mathematics. 35(1). 71–101. 2 indexed citations
11.
Murakawa, Hideki. (2016). A linear finite volume method for nonlinear cross-diffusion systems. Numerische Mathematik. 136(1). 1–26. 12 indexed citations
12.
Murakawa, Hideki & Hideru Togashi. (2015). Continuous models for cell–cell adhesion. Journal of Theoretical Biology. 374. 1–12. 47 indexed citations
13.
Hilhorst, Danielle, et al.. (2014). Singular limit analysis of a reaction-diffusion system with precipitation and dissolution in a porous medium. Networks and Heterogeneous Media. 9(4). 669–682. 2 indexed citations
14.
Murakawa, Hideki. (2014). Error Estimates for Discrete-Time Approximations of Nonlinear Cross-Diffusion Systems. SIAM Journal on Numerical Analysis. 52(2). 955–974. 2 indexed citations
15.
Murakawa, Hideki. (2011). A linear scheme to approximate nonlinear cross-diffusion systems. ESAIM Mathematical Modelling and Numerical Analysis. 45(6). 1141–1161. 10 indexed citations
16.
Murakawa, Hideki & Hirokazu Ninomiya. (2010). Fast reaction limit of a three-component reaction–diffusion system. Journal of Mathematical Analysis and Applications. 379(1). 150–170. 20 indexed citations
17.
Eymard, Robert, et al.. (2010). Numerical approximation of a reaction-diffusion system with fast reversible reaction. Chinese Annals of Mathematics Series B. 31(5). 631–654. 7 indexed citations
18.
Murakawa, Hideki. (2009). A solution of nonlinear diffusion problems by semilinear reaction-diffusion systems. Kybernetika. 45(4). 580–590. 1 indexed citations
19.
Asano, Hitoshi, et al.. (2006). Visualization of a self-vibration heat pipe by neutron radiography. 43. 1 indexed citations
20.
Murakawa, Hideki, et al.. (2003). A Singular Limit Approach to Moving Boundary Problems and Its Applications. Theoretical and applied mechanics Japan. 52. 255–260. 1 indexed citations

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.

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