Jonathan Dawes

1.9k total citations
59 papers, 1.3k citations indexed

About

Jonathan Dawes is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Condensed Matter Physics. According to data from OpenAlex, Jonathan Dawes has authored 59 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Networks and Communications, 16 papers in Statistical and Nonlinear Physics and 11 papers in Condensed Matter Physics. Recurrent topics in Jonathan Dawes's work include Nonlinear Dynamics and Pattern Formation (26 papers), Theoretical and Computational Physics (11 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (7 papers). Jonathan Dawes is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (26 papers), Theoretical and Computational Physics (11 papers) and Mathematical and Theoretical Epidemiology and Ecology Models (7 papers). Jonathan Dawes collaborates with scholars based in United Kingdom, United States and France. Jonathan Dawes's co-authors include Max O. Souza, Thibaut Putelat, J.R. Willis, Julia R. Gog, Claire Postlethwaite, John Burke, Robert N. Kelsh, John R. Lister, Neil M. Ribe and Stephen W. Morris and has published in prestigious journals such as Nature Communications, Development and Journal of Fluid Mechanics.

In The Last Decade

Jonathan Dawes

58 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jonathan Dawes United Kingdom 21 405 228 219 149 137 59 1.3k
Annick Dhooge Belgium 8 441 1.1× 498 2.2× 294 1.3× 244 1.6× 104 0.8× 10 1.7k
Yao-Li Chuang United States 16 359 0.9× 145 0.6× 149 0.7× 76 0.5× 122 0.9× 28 1.9k
Fabio Dercole Italy 21 517 1.3× 663 2.9× 636 2.9× 657 4.4× 135 1.0× 68 2.7k
J. Grasman Netherlands 19 304 0.8× 415 1.8× 305 1.4× 199 1.3× 227 1.7× 72 1.5k
A. M. Rucklidge United Kingdom 21 418 1.0× 439 1.9× 253 1.2× 286 1.9× 98 0.7× 76 1.7k
Younghae Do South Korea 28 383 0.9× 1.0k 4.6× 218 1.0× 172 1.2× 96 0.7× 114 2.7k
Stéphane Blanco France 18 234 0.6× 139 0.6× 58 0.3× 291 2.0× 225 1.6× 57 1.5k
Sébastien Motsch United States 12 418 1.0× 370 1.6× 131 0.6× 39 0.3× 47 0.3× 35 1.2k
Denis Boyer Mexico 24 104 0.3× 448 2.0× 167 0.8× 133 0.9× 80 0.6× 81 1.8k
Rachel Kuske United States 22 304 0.8× 351 1.5× 66 0.3× 45 0.3× 101 0.7× 73 1.2k

Countries citing papers authored by Jonathan Dawes

Since Specialization
Citations

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

Fields of papers citing papers by Jonathan Dawes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Dawes

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Dawes. A scholar is included among the top collaborators of Jonathan Dawes 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 Jonathan Dawes. Jonathan Dawes 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.
Subkhankulova, Tatiana, Л. А. Урошлев, Masataka Nikaido, et al.. (2023). Zebrafish pigment cells develop directly from persistent highly multipotent progenitors. Nature Communications. 14(1). 1258–1258. 26 indexed citations
2.
Dawes, Jonathan, Xin Zhou, & Mustafa Moinuddin. (2022). System-level consequences of synergies and trade-offs between SDGs: quantitative analysis of interlinkage networks at country level. Sustainability Science. 17(4). 1435–1457. 10 indexed citations
3.
Kelsh, Robert N., et al.. (2021). Cyclical fate restriction: a new view of neural crest cell fate specification. Development. 148(22). 28 indexed citations
4.
Wagener, Thorsten, Dragan Savić, David Butler, et al.. (2021). Hydroinformatics education – the Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training. Hydrology and earth system sciences. 25(5). 2721–2738. 5 indexed citations
5.
Dawes, Jonathan, et al.. (2021). Novel Generic Models for Differentiating Stem Cells Reveal Oscillatory Mechanisms. arXiv (Cornell University). 11 indexed citations
6.
Dawes, Jonathan, et al.. (2020). Embedding and approximation theorems for echo state networks. Neural Networks. 128. 234–247. 73 indexed citations
7.
Dawes, Jonathan. (2019). Are the Sustainable Development Goals self‐consistent and mutually achievable?. Sustainable Development. 28(1). 101–117. 83 indexed citations
8.
Putelat, Thibaut, Jonathan Dawes, & Alan Champneys. (2017). A phase-plane analysis of localized frictional waves. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 473(2203). 20160606–20160606. 18 indexed citations
9.
Dawes, Jonathan, et al.. (2017). Invasions Slow Down or Collapse in the Presence of Reactive Boundaries. Bulletin of Mathematical Biology. 79(10). 2197–2214. 2 indexed citations
10.
Yang, Qian, Tim Rogers, & Jonathan Dawes. (2017). Demographic noise slows down cycles of dominance. Journal of Theoretical Biology. 432. 157–168. 4 indexed citations
11.
Dawes, Jonathan & Jennifer L. Williams. (2015). Localised pattern formation in a model for dryland vegetation. Journal of Mathematical Biology. 73(1). 63–90. 18 indexed citations
12.
Dawes, Jonathan. (2015). After 1952: The later development of Alan Turing's ideas on the mathematics of pattern formation. Historia Mathematica. 43(1). 49–64. 21 indexed citations
13.
Dawes, Jonathan & Max O. Souza. (2013). A derivation of Holling's type I, II and III functional responses in predator–prey systems. Journal of Theoretical Biology. 327. 11–22. 137 indexed citations
14.
Dawes, Jonathan, et al.. (2013). The Swift–Hohenberg equation with a nonlocal nonlinearity. Physica D Nonlinear Phenomena. 270. 60–80. 15 indexed citations
15.
Dawes, Jonathan. (2010). The emergence of a coherent structure for coherent structures: localized states in nonlinear systems. Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences. 368(1924). 3519–3534. 55 indexed citations
16.
Dawes, Jonathan. (2009). Modulated and Localized States in a Finite Domain. SIAM Journal on Applied Dynamical Systems. 8(3). 909–930. 30 indexed citations
17.
Putelat, Thibaut, J.R. Willis, & Jonathan Dawes. (2008). On the seismic cycle seen as a relaxation oscillation. The Philosophical Magazine A Journal of Theoretical Experimental and Applied Physics. 88(28-29). 3219–3243. 10 indexed citations
18.
Dawes, Jonathan. (2007). Atrial fibrillation and flutter: Is it better to be informed?. British Journal of Cardiac Nursing. 2(10). 476–478.
19.
Dawes, Jonathan, et al.. (2006). Frequency locking and complex dynamics near a periodically forced robust heteroclinic cycle. Physical Review E. 74(5). 55201–55201. 11 indexed citations
20.
Dawes, Jonathan & Julia R. Gog. (2002). The onset of oscillatory dynamics in models of multiple disease strains. Journal of Mathematical Biology. 45(6). 471–510. 55 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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