Kevin J. Painter

7.0k total citations · 1 hit paper
81 papers, 4.7k citations indexed

About

Kevin J. Painter is a scholar working on Modeling and Simulation, Cell Biology and Molecular Biology. According to data from OpenAlex, Kevin J. Painter has authored 81 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Modeling and Simulation, 39 papers in Cell Biology and 36 papers in Molecular Biology. Recurrent topics in Kevin J. Painter's work include Mathematical Biology Tumor Growth (47 papers), Cellular Mechanics and Interactions (30 papers) and Gene Regulatory Network Analysis (22 papers). Kevin J. Painter is often cited by papers focused on Mathematical Biology Tumor Growth (47 papers), Cellular Mechanics and Interactions (30 papers) and Gene Regulatory Network Analysis (22 papers). Kevin J. Painter collaborates with scholars based in United Kingdom, Italy and Germany. Kevin J. Painter's co-authors include Thomas Hillen, Jonathan A. Sherratt, Philip K. Maini, Nicola J. Armstrong, Hans G. Othmer, Michael Winkler, Denis J. Headon, Alf Gerisch, William Ho and Jeanette A. Johansson and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Angewandte Chemie International Edition and Nature Communications.

In The Last Decade

Kevin J. Painter

78 papers receiving 4.5k citations

Hit Papers

A user’s guide to PDE models for chemotaxis 2008 2026 2014 2020 2008 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin J. Painter United Kingdom 32 3.1k 2.1k 1.6k 874 674 81 4.7k
Jonathan A. Sherratt United Kingdom 48 2.3k 0.8× 1.4k 0.7× 1.8k 1.1× 1.7k 1.9× 406 0.6× 169 6.8k
Hans G. Othmer United States 47 2.3k 0.8× 4.0k 2.0× 1.9k 1.2× 717 0.8× 524 0.8× 139 8.2k
Ruth E. Baker United Kingdom 37 1.1k 0.3× 2.6k 1.3× 1.9k 1.1× 493 0.6× 234 0.3× 207 5.9k
Leah Edelstein‐Keshet Canada 41 1.2k 0.4× 1.8k 0.9× 2.0k 1.2× 1.0k 1.1× 378 0.6× 110 7.8k
Mark A. J. Chaplain United Kingdom 57 6.5k 2.1× 3.5k 1.7× 3.3k 2.0× 1.1k 1.3× 1.1k 1.6× 221 10.4k
Andreas Deutsch Germany 35 1.2k 0.4× 1.4k 0.7× 1.1k 0.7× 163 0.2× 236 0.4× 127 4.4k
Thomas S. Deisboeck United States 35 2.0k 0.7× 1.8k 0.9× 1.0k 0.6× 150 0.2× 264 0.4× 88 4.4k
András Czirók Hungary 39 573 0.2× 2.4k 1.2× 1.2k 0.8× 708 0.8× 126 0.2× 119 9.6k
Eamonn A. Gaffney United Kingdom 38 429 0.1× 1.2k 0.6× 553 0.3× 889 1.0× 217 0.3× 182 5.2k
Hans Meinhardt Germany 42 453 0.1× 4.6k 2.3× 1.8k 1.1× 655 0.7× 476 0.7× 78 9.2k

Countries citing papers authored by Kevin J. Painter

Since Specialization
Citations

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

Fields of papers citing papers by Kevin J. Painter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin J. Painter. 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 Kevin J. Painter. The network helps show where Kevin J. Painter may publish in the future.

Co-authorship network of co-authors of Kevin J. Painter

This figure shows the co-authorship network connecting the top 25 collaborators of Kevin J. Painter. A scholar is included among the top collaborators of Kevin J. Painter 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 Kevin J. Painter. Kevin J. Painter 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.
Simmchen, Juliane, Daniel Gordon, J.A. Mackenzie, et al.. (2025). Perspective on Interdisciplinary Approaches on Chemotaxis. Angewandte Chemie International Edition. 64(47). e202504790–e202504790.
2.
Lorenzi, Tommaso, et al.. (2025). Phenotype structuring in collective cell migration: a tutorial of mathematical models and methods. Journal of Mathematical Biology. 90(6). 61–61. 1 indexed citations
3.
Painter, Kevin J., et al.. (2024). A biased random walk approach for modeling the collective chemotaxis of neural crest cells. Journal of Mathematical Biology. 88(3). 32–32. 1 indexed citations
4.
Painter, Kevin J., et al.. (2024). Variations in non-local interaction range lead to emergent chase-and-run in heterogeneous populations. Journal of The Royal Society Interface. 21(219). 20240409–20240409. 2 indexed citations
5.
Potts, Jonathan R. & Kevin J. Painter. (2024). Distinguishing Between Long-Transient and Asymptotic States in a Biological Aggregation Model. Bulletin of Mathematical Biology. 86(3). 28–28. 3 indexed citations
6.
Johnston, Stuart T. & Kevin J. Painter. (2024). Avoidance, confusion or solitude? Modelling how noise pollution affects whale migration. Movement Ecology. 12(1). 17–17.
7.
Hillen, Thomas, et al.. (2023). Modelling microtube driven invasion of glioma. Journal of Mathematical Biology. 88(1). 4–4. 2 indexed citations
8.
Goddard, Benjamin D., et al.. (2023). On the study of slow–fast dynamics, when the fast process has multiple invariant measures. Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences. 479(2278). 1 indexed citations
9.
Scianna, Marco, et al.. (2019). Modelling chase-and-run migration in heterogeneous populations. Journal of Mathematical Biology. 80(1-2). 423–456. 6 indexed citations
10.
Grima, Ramon, et al.. (2018). A stochastic model of corneal epithelium maintenance and recovery following perturbation. Journal of Mathematical Biology. 78(5). 1245–1276. 2 indexed citations
11.
Hillen, Thomas, et al.. (2017). A space-jump derivation for non-local models of cell–cell adhesion and non-local chemotaxis. Journal of Mathematical Biology. 76(1-2). 429–456. 24 indexed citations
12.
Glover, James D., Kirsty L. Wells, Franziska Matthäus, et al.. (2017). Hierarchical patterning modes orchestrate hair follicle morphogenesis. PLoS Biology. 15(7). e2002117–e2002117. 102 indexed citations
13.
Mort, Richard L., Margaret Keighren, Gabriel Landini, et al.. (2016). Reconciling diverse mammalian pigmentation patterns with a fundamental mathematical model. Nature Communications. 7(1). 10288–10288. 41 indexed citations
14.
Xue, Chuan, Hyung Ju Hwang, Kevin J. Painter, & Radek Erban. (2010). Travelling Waves in Hyperbolic Chemotaxis Equations. Bulletin of Mathematical Biology. 73(8). 1695–1733. 29 indexed citations
15.
Painter, Kevin J., et al.. (2010). How Does Cellular Contact Affect Differentiation Mediated Pattern Formation?. Bulletin of Mathematical Biology. 73(7). 1529–1558. 7 indexed citations
16.
Othmer, Hans G., Kevin J. Painter, David M. Umulis, & Chunyan Xue. (2009). The Intersection of Theory and Application in Elucidating Pattern Formation in Developmental Biology. Mathematical Modelling of Natural Phenomena. 4(4). 3–82. 50 indexed citations
17.
Painter, Kevin J.. (2008). Modelling cell migration strategies in the extracellular matrix. Journal of Mathematical Biology. 58(4-5). 511–43. 82 indexed citations
18.
Hillen, Thomas & Kevin J. Painter. (2008). A user’s guide to PDE models for chemotaxis. Journal of Mathematical Biology. 58(1-2). 183–217. 1135 indexed citations breakdown →
19.
Painter, Kevin J. & Thomas Hillen. (2002). Volume-filling and quorum-sensing in models for chemosensitive movement. 10(4). 501–544. 370 indexed citations
20.
Hillen, Thomas & Kevin J. Painter. (2001). Global Existence for a Parabolic Chemotaxis Model with Prevention of Overcrowding. Advances in Applied Mathematics. 26(4). 280–301. 249 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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