David Iron

843 total citations
33 papers, 639 citations indexed

About

David Iron is a scholar working on Computer Networks and Communications, Public Health, Environmental and Occupational Health and Molecular Biology. According to data from OpenAlex, David Iron has authored 33 papers receiving a total of 639 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Networks and Communications, 9 papers in Public Health, Environmental and Occupational Health and 6 papers in Molecular Biology. Recurrent topics in David Iron's work include Nonlinear Dynamics and Pattern Formation (13 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers) and Theoretical and Computational Physics (5 papers). David Iron is often cited by papers focused on Nonlinear Dynamics and Pattern Formation (13 papers), Mathematical and Theoretical Epidemiology and Ecology Models (8 papers) and Theoretical and Computational Physics (5 papers). David Iron collaborates with scholars based in Canada, Netherlands and Hong Kong. David Iron's co-authors include Michael J. Ward, Juncheng Wei, Théodore Kolokolnikov, Matthias Winter, Johan A. Westerhuis, Hans F. M. Boelens, Gadi Rothenberg, Sina M. Adl, Adriana T. Dawes and Arjen Doelman and has published in prestigious journals such as PLoS ONE, Analytical Chemistry and The Science of The Total Environment.

In The Last Decade

David Iron

31 papers receiving 584 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David Iron Canada 13 341 214 151 135 108 33 639
Razvan A. Satnoianu United Kingdom 14 357 1.0× 204 1.0× 110 0.7× 72 0.5× 61 0.6× 29 518
Maria Carmela Lombardo Italy 15 293 0.9× 341 1.6× 144 1.0× 219 1.6× 73 0.7× 39 792
Andrew L. Krause United Kingdom 16 261 0.8× 166 0.8× 79 0.5× 108 0.8× 118 1.1× 45 1.2k
Yoshihisa Morita Japan 16 228 0.7× 432 2.0× 99 0.7× 159 1.2× 38 0.4× 63 919
Peter van Heijster Australia 13 204 0.6× 146 0.7× 137 0.9× 99 0.7× 41 0.4× 34 379
J. F. G. Auchmuty United States 11 273 0.8× 97 0.5× 136 0.9× 58 0.4× 70 0.6× 15 462
David Uminsky United States 12 77 0.2× 94 0.4× 106 0.7× 144 1.1× 53 0.5× 25 481
M. J. Ward United States 10 129 0.4× 66 0.3× 138 0.9× 23 0.2× 209 1.9× 17 461
Manjun Ma China 13 96 0.3× 299 1.4× 110 0.7× 215 1.6× 59 0.5× 55 637
Tiejun Zhou China 11 174 0.5× 59 0.3× 100 0.7× 45 0.3× 44 0.4× 57 386

Countries citing papers authored by David Iron

Since Specialization
Citations

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

Fields of papers citing papers by David Iron

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Iron

This figure shows the co-authorship network connecting the top 25 collaborators of David Iron. A scholar is included among the top collaborators of David Iron 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 David Iron. David Iron 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.
Kolokolnikov, Théodore, et al.. (2024). Stripe patterns for Gierer–Meinhard model in spatially varying thin domains. Physica D Nonlinear Phenomena. 472. 134480–134480.
2.
Iron, David, et al.. (2020). Localized outbreaks in an S-I-R model with diffusion. Journal of Mathematical Biology. 80(5). 1389–1411. 24 indexed citations
3.
Kolokolnikov, Théodore & David Iron. (2020). Law of mass action and saturation in SIR model with application to Coronavirus modelling. Infectious Disease Modelling. 6. 91–97. 24 indexed citations
4.
Iron, David, et al.. (2017). A model of cell surface receptor aggregation. Journal of Mathematical Biology. 75(3). 705–731. 7 indexed citations
5.
Iron, David, et al.. (2017). Agent-based model of the effect of globalization on inequality and class mobility. Physica D Nonlinear Phenomena. 361. 35–41. 1 indexed citations
6.
Dawes, Adriana T. & David Iron. (2013). Cortical geometry may influence placement of interface between Par protein domains in early Caenorhabditis elegans embryos. Journal of Theoretical Biology. 333. 27–37. 12 indexed citations
7.
Iron, David, et al.. (2012). Dynamics and stability of a three-dimensional model of cell signal transduction. Journal of Mathematical Biology. 67(6-7). 1691–1728. 6 indexed citations
8.
Iron, David, et al.. (2012). A handbook for uncovering the complete energetic budget in insects: the van Handel's method (1985) revisited. 1 indexed citations
9.
Iron, David, et al.. (2011). Model of cell signal transduction in a three-dimensional domain. Journal of Mathematical Biology. 63(5). 831–854. 4 indexed citations
10.
Adl, Sina M., David Iron, & Théodore Kolokolnikov. (2011). A threshold area ratio of organic to conventional agriculture causes recurrent pathogen outbreaks in organic agriculture. The Science of The Total Environment. 409(11). 2192–2197. 26 indexed citations
11.
Kolokolnikov, Théodore, et al.. (2011). Instability thresholds in the microwave heating model with exponential non-linearity. European Journal of Applied Mathematics. 22(3). 187–216. 4 indexed citations
12.
Iron, David, Adeela Syed, Heidi Theisen, et al.. (2008). The role of feedback in the formation of morphogen territories. Mathematical Biosciences & Engineering. 5(2). 277–298. 1 indexed citations
13.
Theisen, Heidi, Adeela Syed, Tamás Lukácsovich, et al.. (2007). Wingless Directly Represses DPP Morphogen Expression via an Armadillo/TCF/Brinker Complex. PLoS ONE. 2(1). e142–e142. 35 indexed citations
14.
Iron, David, et al.. (2007). Stability of asymmetric spike solutions to the Gierer-Meinhardt system. Chaos An Interdisciplinary Journal of Nonlinear Science. 17(3). 37105–37105. 5 indexed citations
15.
Iron, David, Juncheng Wei, & Matthias Winter. (2004). Stability analysis of Turing patterns generated by the Schnakenberg model. Journal of Mathematical Biology. 49(4). 358–390. 75 indexed citations
16.
Westerhuis, Johan A., Hans F. M. Boelens, David Iron, & Gadi Rothenberg. (2004). Model Selection and Optimal Sampling in High-Throughput Experimentation. Analytical Chemistry. 76(11). 3171–3178. 8 indexed citations
17.
Rothenberg, Gadi, Hans F. M. Boelens, David Iron, & Johan A. Westerhuis. (2003). Monitoring the future of chemical reactions. UvA-DARE (University of Amsterdam). 21(6). 80–83. 5 indexed citations
18.
Boelens, Hans F. M., David Iron, Johan A. Westerhuis, & Gadi Rothenberg. (2003). Tracking Chemical Kinetics in High‐Throughput Systems. Chemistry - A European Journal. 9(16). 3876–3881. 14 indexed citations
19.
Iron, David & Michael J. Ward. (2001). Spike pinning for the Gierer–Meinhardt model. Mathematics and Computers in Simulation. 55(4-6). 419–431. 12 indexed citations
20.
Iron, David & Michael J. Ward. (2000). A Metastable Spike Solution for a Nonlocal Reaction-Diffusion Model. SIAM Journal on Applied Mathematics. 60(3). 778–802. 45 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Razvan A. Satnoianu Breakdown of academic impact, for papers by Maria Carmela Lombardo Breakdown of academic impact, for papers by Andrew L. Krause Breakdown of academic impact, for papers by Yoshihisa Morita Breakdown of academic impact, for papers by Peter van Heijster Breakdown of academic impact, for papers by J. F. G. Auchmuty Breakdown of academic impact, for papers by David Uminsky Breakdown of academic impact, for papers by M. J. Ward Breakdown of academic impact, for papers by Manjun Ma Breakdown of academic impact, for papers by Tiejun Zhou
Rankless by CCL
2026