Research Publications
Avoidance, confusion or solitude? Modelling how noise pollution affects whale migration
Johnston, S. T., and Painter, K. J., 2024, Movement Ecology, 12 (1), 17.
https://doi.org/10.1186/s40462-024-00458-w
TRPV4 is expressed by enteric glia and muscularis macrophages of the colon but does not play a prominent role in colonic motility
Rajasehkar P., et al., 2024, bioRxiv, 2024.01.09.574831.
https://doi.org/10.1101/2024.01.09.574831
Thermodynamically-consistent, reduced models of gene regulatory networks
Pan, M., Gawthrop, P. J., Faria, M., and Johnston, S. T., 2023, bioRxiv, 20 (207), 20230356.
https://doi.org/10.1101/2023.11.13.566770
Intent matters: how flow and forms of information impact collective navigation
Hodgson, T. M., Johnston, S. T., Ottobre, M., and Painter, K. J., 2023, Journal of the Royal Society Interface, 20 (207), 20230356.
https://doi.org/10.1098/rsif.2023.0356
Exact solutions for diffusive transport on heterogeneous growing domains
Johnston, S. T., and Simpson, M. J., 2023, Proceedings of the Royal Society A, 479 (2276), 20230263.
https://doi.org/10.1098/rspa.2023.0263
Frontiers of mathematical biology: A workshop honouring Professor Edmund Crampin
Araujo, R., et al., 2023, Mathematical Biosciences, 359, 109007.
https://doi.org/10.1016/j.mbs.2023.109007
Analysis of molecular communication systems employing receivers covered by heterogeneous receptors
Huang, X., Fang, Y., Johnston, S. T., Faria, M., Yang, N., and Schober, R., 2023, IEEE Transactions on Molecular, Biological and Multi-Scale Communications, 9 (1), 63-78.
https://doi.org/10.1109/TMBMC.2023.3234807
Capturing and quantifying particle transcytosis with microphysiological intestine‐on‐chip models
Delon, L. C., Faria, M., Jia, Z., , Johnston, S. T., Gibson, R., Prestidge, C. A., and Thierry, B., 2023, Small Methods, 7 (1), 2200989.
https://doi.org/10.1002/smtd.202200989
Free and interfacial boundaries in individual-based models of multicellular biological systems
Germano, D. P. J., Zanca, A., Johnston, S. T., Flegg, J. A., and Osborne, J. M., 2023, Bulletin of Mathematical Biology, 85 (11), 111.
https://doi.org/10.1007/s11538-023-01214-8
Equation learning to identify nano-engineered particle–cell interactions: an interpretable machine learning approach
Johnston, S. T., and Faria, M., 2022, Nanoscale, 14 (44), 16502-16515.
https://doi.org/10.1039/D2NR04668G
Modelling realistic 3D deformations of simple epithelia in dynamic homeostasis
Germano, D. P. J., Johnston, S. T., Crampin, E. J., and Osborne, J. M., 2022, Mathematical Biosciences, 352, 108895
https://doi.org/10.1016/j.mbs.2022.108895
Analysis of Receiver Covered by Heterogeneous Receptors in Molecular Communications
Huang, X., Fang, Y., Johnston, S. T., Faria, M., Yang, N., and Schober, R., 2022, IEEE International Conference on Communications.
https://doi.org/10.1109/ICC45855.2022.9839114
Extinction of bistable populations is affected by the shape of their initial spatial distribution
Li, Y., Johnston, S. T., Buenzli, P. R., van Heijster, P., and Simpson, M. J., 2022, Bulletin of Mathematical Biology 84, 21.
Spatio-temporal analysis of nanoparticles in live tumor spheroids impacted by cell origin and density
Ahmed-Cox, A., Pandzic, E., Johnston, S. T., Heu, C., McGhee, J. B., Mansfeld, F. M., Crampin, E. J., Davis, T. P., Whan, R. M., and Kavallaris, M., 2022, Journal of Controlled Release 341, 661-675.
Bio-nano science: better metrics would accelerate progress
Faria, M., Johnston, S. T., Mitchell, A. J., Crampin, E. J., and Caruso, F., 2021, Chemistry of Materials 33 (19), 7613-7619.
Modelling collective navigation via nonlocal communication
Johnston, S. T., and Painter, K. J., 2021, Journal of the Royal Society Interface 18 (182), 20210383.
Understanding nano-engineered particle-cell interactions: biological insights from mathematical models
Johnston, S. T., Faria, M., and Crampin, E. J., 2021, Nanoscale Advances 3 (8), 2139-2156.
Unpacking the Allee effect: determining individual-level mechanisms that drive global population dynamics
Fadai, N. T., Johnston, S. T., and Simpson, M. J., 2020, Proceedings of the Royal Society A 476 (2241), 20200350.
Predicting population extinction in lattice-based birth-death-movement models
Johnston, S. T., Simpson, M. J., and Crampin, E. J., 2020, Proceedings of the Royal Society A 476 (2238), 20200089.
Isolating the sources of heterogeneity in nano-engineered particle-cell interactions
Johnston, S. T., Faria, M., and Crampin, E. J., 2020, Journal of the Royal Society Interface 17 (166), 20200221.
Accurate particle-based reaction algorithms for fixed timestep simulators
Johnston, S. T., Angstmann, C. N., Arjunan, S. N. V., Beentjes, C. H. L., Coulier, A., Isaacson, S. A., Khan, A. A., Lipkow, K., Andrews, S. S., 2020, MATRIX Annals, 149-164.
Revisiting cell-particle association in vitro: a quantitative method to compare particle performance
Faria, M., Noi, K. F., Dai, Q., Bjornmalm, M., Johnston, S. T., Kempe, K., Caruso, F., Crampin, E. J., 2019, Journal of Controlled Release 307, 355-367.
Selective metal-phenolic assembly from complex multicomponent mixtures
Lin, G., Rahim, M. A., Leeming, M. G., Cortez-Jugo, C., Besford, Q. A., Ju, Y., Zhong, Q.-Z., Johnston, S. T., Zhou, J., Caruso, F., 2019, ACS Applied Materials & Interface 11 (19), 17714-17721.
Corrected pair correlation functions for environments with obstacles
Johnston, S. T., and Crampin, E. J., 2019, Physical Review E 99 (3), 032124.
The impact of short- and long-range perception on population movements
Johnston, S. T., and Painter, K. J., 2019, Journal of Theoretical Biology 460, 227-242.
Self-assembly of nano-to-macroscopic metal-phenolic materials
Yun, G., Besford, Q. A., Johnston, S. T., Richardson, J. J., Pan, S., Biviano, M., and Caruso, F., 2018, Chemistry of Materials 30 (16), 5750-5758.
An analytical approach for quantifying the influence of nanoparticle polydispersity on cellular delivered dose
Johnston S. T., Faria M. and Crampin, E. J., 2018, Journal of the Royal Society Interface 15 (144), 20180364.
A new and accurate continuum description of moving fronts
Johnston, S. T., Baker, R. E., and Simpson, M. J., 2017, New Journal of Physics 19 (3), 033010.
Co-operation, competition and crowding: a discrete framework linking Allee kinetics, nonlinear diffusion, shocks and sharp-fronted travelling waves
Johnston, S. T., Baker, R. E., McElwain, D. L. S., and Simpson, M. J., 2017, Scientific Reports 7, 41234.
Quantifying the effect of experimental design choices for in vitro scratch assays
Johnston S. T., Ross, J. V., Binder, B. J., McElwain, D. L. S., Haridas, P., and Simpson, M. J., 2016, Journal of Theoretical Biology 400, 19-31.
Filling the gaps: a robust description of adhesive birth-death-movement processes
Johnston, S. T., Baker, R. E., and Simpson, M. J., 2016, Physical Review E 93 (4), 042413.
Modelling the movement of interacting cell populations: a moment dynamics approach
Johnston, S. T., Baker, R. E., and Simpson, M. J., 2015, Journal of Theoretical Biology 370, 81-92.
Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM assay data using the Fisher-Kolmogorov model
Johnston S. T., Shah, E. T., Chopin, L. K., McElwain, D. L. S., and Simpson, M. J., 2015, BMC Systems Biology 9 (38) 400, 19-31.
Interpreting scratch assays using pair density dynamics and approximate Bayesian computation
Johnston, S. T., Simpson, M. J., McElwain, D. L. S., Binder, B. J., and Ross, J. V., 2014, Open Biology 4 (9), 140097.
How much information can be obtained from tracking the position of the leading edge in a scratch assay?
Johnston, S. T., Simpson, M. J., and Baker, R. E., 2014, Journal of the Royal Society Interface 11 (97), 20140325.
Lattice-free descriptions of collective motion with crowding and adhesion
Johnston, S. T., Simpson, M. J., and Plank, M. J., 2013, Physical Review E 88 (6), 062720.
Mean-field descriptions of collective migration with strong adhesion
Johnston, S. T., Simpson, M. J., and Baker, R. E., 2012, Physical Review E 85 (5), 051922.