All publications are ordered alphabetically within each year, with authors from the StAMBio group in bold.


  1. Katsaounis, D., Chaplain, M.A.J. & Sfakianakis, N. (2023) “Stochastic differential equation modelling of cancer cell migration and tissue invasion.” Journal of Mathematical Biology 87, 8.
  2. Stewart A.J., Acevedo, S., (2023). “Eco-evolutionary tradeoffs in the dynamics of prion strain competition.” Proceedings of the Royal Society of London Series B: Biological Sciences.
  3. Cimpeanu T., Santos F.C., Han T.A. (2023) “Does spending more always ensure higher cooperation? An analysis of institutional incentives on heterogeneous networks.” Dynamic Games and Applications, First Online.
  4. Cimpeanu T., Di Stefano A., Perret C., Han T. A. (2023). “Social diversity reduces the complexity and cost of fostering fairness.” Chaos, Solitons and Fractals, 167.
  5. Stewart A.J., Raihani N., (2023). “Group reciprocity and the evolution of stereotyping.” Proceedings of the Royal Society of London Series B: Biological Sciences, 290(1991).
  6. Cortez M.J., Akil A.E., Josić K., Stewart A.J. (2023) “Incorporating Computational Challenges into a Multidisciplinary Course on Stochastic Processes.” SIAM Review.
  7. 2022

  8. Bellomo, N., Brezzi, F., Chaplain, M.A.J. (2022) “New trends of mathematical sciences towards modeling virus pandemics in a globally connected world” In: Mathematical Models and Methods in Applied Sciences. Online Ready, 1-7.
  9. Dietrich, A., Kolbe, N., Sfakianakis, N., Surulescu, C. (2022) “Multiscale modeling of glioma invasion: from receptor binding to flux-limited macroscopic pdes”. Multiscale Modeling & Simulation, 20(2), pp.685-713.
  10. Guo, N., Minas, G., Synowsky, S.A., Dunne, M.R., Ahmed, H., McShane, R., Bhardwaj, A., Donlon, N.E., Lorton, C., O’Sullivan, J. and Reynolds, J.V. (2022) “Identification of plasma proteins associated with oesophageal cancer chemotherapeutic treatment outcomes using SWATH-MS”. J. Proteomics, 266, p.104684.
  11. Kolbe, N. and Sfakianakis, N. (2022) “An adaptive rectangular mesh administration and refinement technique with application in cancer invasion models”. J. Comput. Appl. Math., 416, p.114442.
  12. Macfarlane, F.R., Chaplain, M.A.J., Eftimie, R. (2022) “Modelling rheumatoid arthritis: A hybrid modelling framework to describe pannus formation in a small joint” ImmunoInform. 100014.
  13. Macfarlane, F.R., Lorenzi, T., Painter, K.J. (2022) “The Impact of Phenotypic Heterogeneity on Chemotactic Self-Organisation” Bull. Math. Biol. 84, 143. doi: 10.1007/s11538-022-01099-z
  14. Macfarlane, F.R., Ruan, X., Lorenzi, T. (2022) “Individual-based and continuum models of phenotypically heterogeneous growing cell populations” AIMS Bioeng. 9(1), 68-92.
  15. Soto, X., Burton, J., Manning, C.S., Minchington, T., Lea, R., Lee, J., Kursawe, J., Rattray, M. and Papalopulu, N. (2022) “Sequential and additive expression of miR-9 precursors control timing of neurogenesis”. Development, 149(19), p.dev200474.
  16. Stewart, A.J. , Raihani, N. (2022) “Group reciprocity and the evolution of stereotyping”. Proceedings of the Royal Society B. 10.1098/rspb.2022.1834
  17. Villa, C., Gerish, A.,Chaplain, M.A.J. (2022) “A novel nonlocal partial differential equation model of endothelial progenitor cell cluster formation during the early stages of vasculogenesis” J. Theor. Biol. 534, 110963.
  18. 2021

  19. Franssen, L.C., Sfakianakis, N., Chaplain, M.A.J. (2021) “A novel 3D atomistic-continuum cancer invasion model: In silico simulations of an in vitro organotypic invasion assay” J. Theor. Biol. In press, doi:10.1016/j.jtbi.2021.110677.
  20. Hamis, S.J, Macfarlane, F.R. (2021) “A single-cell mathematical model of SARS-CoV-2 induced pyroptosis and the effects of anti-inflammatory intervention” AIMS Math. 6(6), 6050-6086.
  21. Liu, R., Higley, K., Swat, M., Chaplain, M.A.J., Powathil, G., Glazier, J. (2021) “Development of a coupled simulation toolkit for computational radiation biology based on Geant4 and CompuCell3D” Phys. Med. Biol. 66(4), 045026.
  22. Macnamara, C.K. (2021) “Biomechanical modelling of cancer: Agent-based force-based models of solid tumours within the context of the tumour microenvironment” Comp. Sys. Onco. 1(2),
  23. Stewart, A.J., Plotkin, J.B. (2021) “The natural selection of good science” Nature Human Behaviour
  24. Stewart, A.J., Plotkin, J.B., McCarty, N. (2021) “Inequality, Identity, and Partisanship: How redistribution can stem the tide of mass polarization”. Proceedings of the National Academy of Sciences of the United States of America (PNAS).
  25. Villa, C., Chaplain, M.A.J., Gerisch, A. et al. (2021) “Mechanical Models of Pattern and Form in Biological Tissues: The Role of Stress–Strain Constitutive Equations” Bull. Math. Biol. 83, 80.
  26. Villa, C., Chaplain, M.A.J., Lorenzi, T. et al. (2021) “Modelling phenotypic heterogeneity in vascularised tumours” SIAM Journal on Applied Mathematics, 81, 434–453.
  27. Xiao, Y., Thomas, L., Chaplain, M.A.J. (2021) “Calibrating models of cancer invasion: Parameter estimation using approximate Bayesian computation and gradient matching” R. Soc. Open Sci. 8: 202237.
  28. 2020

  29. Ardaševa, A., Gatenby, R.A., Anderson, A.R.A., Byrne, H.M., Maini, P.K., Lorenzi, T. (2020) “A Mathematical Dissection of the Adaptation of Cell Populations to Fluctuating Oxygen Levels” Bull. Math. Biol., 82,81.
  30. Bubba F., Lorenzi, T., Macfarlane, F.R. (2020) “From a discrete model of chemotaxis with volume-filling to a generalized Patlak–Keller–Segel model” Proc. R. Soc. A. 476, 20190871.
  31. Bellomo, N., Bingham, R., Chaplain, M.A.J., Dosi, G., Forni, G., Knopoff, D. A., Lowengrub, J., Twarock, R., Virgillito, M. E. (2020) “A multiscale model of virus pandemic: heterogeneous interactive entities in a globally connected world” Math. Mod. Meth. 30 (8), 1591-1651.
  32. Chaplain, M.A.J. (2020) “Multiscale Modelling of Cancer: Micro-, Meso- and Macro-scales of Growth and Spread” In: Bizzarri M. (eds) Approaching Complex Diseases. Human Perspectives in Health Sciences and Technology, vol 2. Springer, Cham.
  33. Chaplain, M.A.J., Kirschner, D., Iwasa, Y. (2020) “JTB Editorial Malpractice: A Case Report” J. Theor. Biol. 488, 110171.
  34. Cooper, F.R., Baker, R.E., Bernabeu, M.O., Bordas, R., Bowler, L., Bueno-Orovio, A., … , Kursawe, J., et. al. (2020) “Chaste: Cancer, Heart and Soft Tissue Environment” J. Open Source Softw., 5(47), 1848.
  35. Franssen, L.C., Chaplain, M.A.J. (2020) “A mathematical multi-organ model for bidirectional epithelial–mesenchymal transitions in the metastatic spread of cancer” IMA J. Appl. Math. 85(5), 724-761.
  36. Hamis, S.J., Kohandel, M., Dubois, L.J., Yaromina, A., Lambin, P., et al. (2020) “Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape” PLOS Comput. Biol. 16(8), e1008041.
  37. Hamis, S.J., Stratiev, S., Powathil, G. (2020) “Uncertainty and sensitivity analyses methods for agent-based mathematical models: An introductory review” In: The Physics of Cancer. p. 1-37
  38. Hamis, S.J., Powathil, G. (2020) “Can we Crack Cancer?” In: Matthäus F., Matthäus S., Harris S., Hillen T. (eds) The Art of Theoretical Biology. Springer, Cham
  39. Lorenzi, T., Macfarlane, F.R., Villa, C. (2020) “Discrete and Continuum Models for the Evolutionary and Spatial Dynamics of Cancer: A Very Short Introduction Through Two Case Studies” In: Mondaini R. (eds) Trends in Biomathematics: Modeling Cells, Flows, Epidemics, and the Environment. BIOMAT 2019. Springer, Cham.
  40. Macfarlane, F.R., Chaplain, M.A.J., Lorenzi, T. (2020) “A hybrid discrete-continuum approach to model Turing pattern formation” Math. Biosci. Eng., 17(6), 7442-7479.
  41. Minas, G., Woodcock, D.J., Ashall, L., Harper, C.V., White, M.R.H., et al. (2020) “Multiplexing information flow through dynamic signalling systems” PLOS Comput. Biol. 16(8), e1008076.
  42. Pitcher, M.J., Bowness, R., Dobson, S., Eftimie, R., Gillespie, S.H. (2020) “Modelling the effects of environmental heterogeneity within the lung on the tuberculosis life-cycle” J. Theor. Biol. 506, 110381.
  43. Pitcher, M.J., Dobson, S.A., Kelsey, T., Chaplain, M.A.J., Sloan, D.J., Gillespie, S.H., Bowness, R. (2020) “How mechanistic in silico modelling can improve our understanding of TB disease and treatment” Int. J. Tuberc. Lung Dis. 24(11), 1145-1150.
  44. Preedy, K.F., Chaplain, M.A.J., Leybourne, D.J., Marion, G., Karley, A.J. (2020) “Learning‐induced switching costs in a parasitoid can maintain diversity of host aphid phenotypes although biocontrol is destabilized under abiotic stress” J. Anim. Ecol., 89(5), 1216-1229.
  45. Ruske, L.J., Kursawe, J., Tsakiridis, A., Wilson, V., Fletcher, A.G., Blythe, R.A., Schumacher, L.J. (2020) “Coupled differentiation and division of embryonic stem cells inferred from clonal snapshots” Phys. Biol. 17 (6), 65009.
  46. Sabiiti, W., Azam, K., Farmer, E.C. W., Kuchaka, D., Mtafya, B., Bowness, R., et. al. (2020) “Tuberculosis bacillary load, an early marker of disease severity and treatment response: the utility of tuberculosis Molecular Bacterial Load Assay” Thorax. Online First, 3 p.
  47. Sfakianakis, N., Madzvamuse, A., Chaplain, M.A.J. (2020) “A hybrid multiscale model for cancer invasion of the extracellular matrix” Multiscale Model. Sim. 18(2), 824-850.
  48. Soto, X., Biga, V., Kursawe, J., Lea, R., Doostdar, P., Thomas, R., & Papalopulu, N. (2020) “Dynamic properties of noise and Her6 levels are optimized by miR‐9, allowing the decoding of the Her6 oscillator” EMBO J., e103558.
  49. Stace, R.E., Stiehl, T., Chaplain, M.A.J., Marciniak-Czochra, A., Lorenzi, T. (2020) “Discrete and continuum phenotype-structured models for the evolution of cancer cell populations under chemotherapy” Math. Model. Nat. Phenom., 15, 14.
  50. Villa, C., Chaplain, M.A.J., Lorenzi, T. (2020) “Evolutionary Dynamics in Vascularised Tumours under Chemotherapy: Mathematical Modelling, Asymptotic Analysis and Numerical Simulations” Vietnam J. Math.
  51. 2019

  52. Almeida, L., Bagnerini, P., Fabrini, G., Hughes, B.D., Lorenzi, T. (2019) “Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: Insight from a phenotype-strutured model” ESAIM Math. Model. Numer. Anal., 53(4), 1157-1190.
  53. Ardaševa, A., Gatenby, R.A., Anderson, A.R.A., Byrne, H.M., Maini, P.K., Lorenzi, T. (2019) “Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments.” J. Math. Biol., 80, 775–807.
  54. Bowman, C., Chaplain, M.A.J., Matzavinos, A. (2019) “Dissipative particle dynamics simulation of critical pore size in a lipid bilayer membrane” Royal Soc. Open Sci., 6(3), 181657.
  55. Chaplain, M.A.J., Giverso, C., Lorenzi, T., Preziosi, L. (2019) “Derivation and application of effective interface conditions for continuum mechanical models of cell invasion through thin membranes” SIAM J. Appl. Math., 79, 2011–2031.
  56. Chaplain, M.A.J., Lorenzi, T., Macfarlane, F.R. (2019) “Bridging the gap between individual-based and continuum models of growing cell populations” J Math Biol. 80, 343–371.
  57. Franssen, L.C., Lorenzi, T., Burgess, A., Chaplain, M.A.J. (2019) “A mathematical framework for modelling the metastatic spread of cancer” Bull. Math. Biol., 81(6), 1965–2010.
  58. Hamis, S.J., Powathil, G.G., Chaplain, M.A.J. (2019) “Blackboard to bedside: A mathematical modeling bottom-up approach towards personalized cancer treatments ” JCO Clin. Cancer Inform., 3, 1-11.
  59. Lorenzi, T. Marciniak-Czochra, A., Stiehl, T. (2019) “A structured population model of clonal selection in acute leukemias with multiple maturation stages” J. Math. Biol., 79, 1587-1621.
  60. Macfarlane, F.R., Chaplain. M.A.J., Eftimie, R. (2019) “Quantitative Predictive Modelling Approaches to Understanding Rheumatoid Arthritis: A Brief Review” Cells , 9(1), 74.
  61. Macfarlane, F.R., Chaplain, M.A.J., Lorenzi, T. (2019) “A stochastic individual-based model to explore the role of spatial interactions and antigen recognition in the immune response against solid tumours” J. Theor. Biol., 480, 43–55.
  62. Macnamara, C.K., Caiazzo, A., Ramis-Conde, I., Chaplain. M.A.J. (2019) “Computational modelling and simulation of cancer growth and migration within a 3D heterogeneous tissue: the effects of fibre and vascular structure” J. Comp. Sci. , 40(1), 101067.
  63. Macnamara, C.K., Mitchell, E.I., Chaplain, M.A.J. (2019) “Spatial-stochastic modelling of synthetic gene regulatory networks” J. Theor. Biol., 468, 27-44.
  64. Minas, G., Rand, D.A. (2019) “Parameter sensitivity analysis for biochemical reaction networks” Math. Biosci. Eng., 16(5), 3965-3987.
  65. 2018

  66. Bitsouni, V., Trucu, D., Chaplain, M.A.J., Eftimie, R. (2018) “Aggregation and travelling wave dynamics in a two-population model of cancer cell growth and invasion” Math. Med. Biol., 35(4), 541-577.
  67. Bowness, R., Chaplain, M.A.J., Powathil, G.G., Gillespie, S.H. (2018) “Modelling the effects of bacterial cell state and spatial location on tuberculosis treatment: Insights from a hybrid multiscale cellular automaton model” J. Theor. Biol., 446, 87-100.
  68. Brueningk, S., Powathil, G., Ziegenhein, P., Jannat, I., Rivens, Chaplain, M.A.J. , Oelfke, U., ter Haar, G. (2018) “Combining radiation with hyperthermia: A multiscale model informed by in vitro experiments” J.R. Soc. Interface, 15, 20170681.
  69. Franssen, L.C. (2018) “Using mathematics to outsmart cancer” Math. Today, 54(4), 135-137.
  70. Hodgkinson, A., Chaplain, M. A. J., Domschke, P., Trucu, D. (2018) “Computational approaches and analysis for a spatio-structural-temporal invasive carcinoma model” Bull. Math. Biol., 80(4), 701-737.
  71. Kim, Y., Kang, H., Powathil, G.G., Kim, H., Trucu, D., Lee, W., Lawler, S., Chaplain, M. A. J. (2018) “Role of extracellular matrix and microenvironement in regulation of tumor growth and LAR-mediated invasion in glioblastoma” PLoS one, 13(10), e0204865.
  72. Lorenzi, T., Venkataraman, C., Lorz, A., Chaplain, M.A.J. (2018) “The role of spatial variations of abiotic factors in mediating intratumour phenotypic heterogeneity” J. Theor. Biol., 451, 101-110.
  73. Macfarlane, F.R., Lorenzi, T., Chaplain, M.A.J. (2018) “Modelling the immune response to cancer: An individual-based approach accounting for the difference in movement between inactive and activated T cells” Bull. Math. Biol., 80, 1539-1562.
  74. Murphy, L., Venkataraman, C., Madzvamuse, A. (2018) “Parameter identification through mode isolation for reaction-diffusion systems on arbitrary geometries” Int J Biomath, 11(4), 1850053.
  75. Pitcher, M.J., Bowness, R., Dobson, S.A., Gillespie, S.H. (2018) “A spatially heterogeneous network-based metapopulation software model applied to the simulation of a pulmonary tuberculosis infection” Applied Network Science, 3, 33.
  76. Szymanska, Z., Cytowski, M., Mitchell, E., Macnamara, C. K., Chaplain, M. A. J. (2018) “Computational modelling of cancer development and growth: Modelling at multiple scales and multiscale modelling” Bull. Math. Biol. 80(5),1366-1403.
  77. 2017

  78. Bitsouni, V., Chaplain, M.A.J., Eftimie, R. (2017) “Mathematical modelling of cancer invasion: The multiple roles of TGF-beta pathway on tumour proliferation and adhesion” Math. Mod. Meth. Appl. Sci., 27,1929-1962.
  79. Burgess, A.E.F., Lorenzi, T., Schofield, P.G., Hubbard, S.F., Chaplain, M.A.J. (2017) “Examining the role of individual movement in promoting coexistence in a spatially explicit prisoner’s dilemma”, J. Theor. Biol., 419, 323-332.
  80. Delitala, M., Lorenzi, T. (2017) “Emergence of spatial patterns in a mathematical model for the co-culture dynamics of epithelial-like and mesenchymal-like cells”, Math. Biosci. Engin., 14, 79-93.
  81. Domschke, P., Trucu, D., Gerisch, A., Chaplain, M.A.J. (2017) “Structured models of cell migration incorporating molecular binding processes” J. Math. Biol., 75, 1517-1561
  82. Donald, I., Meyer, K., Brengman, J., Gillespie, SH., Bowness, R. (2017) “Project Sanitarium: Playing tuberculosis to its end game” Journal of Computing in Higher Education, 29(3), 599-617.
  83. Elliott, C. M., Ranner, T., Venkataraman, C. (2017) “Coupled bulk-surface free boundary problems arising from a mathematical model of receptor-ligand dynamics” SIAM J. Math. Anal., 49(1), 360-397.
  84. Frittelli, M., Madzvamuse, A., Sgura, I., Venkataraman, C. (2017) “Lumped finite elements for reaction–cross-diffusion systems on stationary surfaces” Comput. Math. Appl., 74(12), 3008-3023.
  85. Hill, L., Chaplain, M.A.J., Wolf, R., Kapelyukh, Y. (2017) “The usage of a three-compartment model to investigate the metabolic differences between hepatic reductase null and wild-type mice” Math. Med. Biol., 34, 1-13.
  86. Lorenzi, T., Lorz, A., Perthame, B. (2017) “On interfaces between cell populations with different mobilities” Kinet. Relat. Models, 10, 299-311.
  87. Macnamara, C.K., Chaplain, M.A.J. (2017) “Spatio-temporal models of synthetic genetic oscillators” Math. Biosci. Eng., 14(1),249-262.
  88. Peng, L., Trucu, D., Lin, P., Thompson, A., Chaplain, M.A.J. (2017) “A multiscale mathematical model of tumour invasive growth” Bull. Math. Biol., 79, 389-429.
  89. Sekimura, T., Venkataraman, C. (2017) “Spatial variation in boundary condition can govern selection and location of eyespots in butterfly wings” In Diversity and Evolution of Butterfly Wing Patterns (pp. 107-118), Springer, Singapore.
  90. Yang, F. W., Venkataraman, C., Styles, V., Madzvamuse, A. (2017) “A robust and efficient adaptive multigrid solver for the optimal control of phase field formulations of geometric evolution laws” Commun. Comput. Phys., 21(1), 65-92.
  91. 2016

  92. Boujelben, A., Watson, M., McDougall, S.R., Yen, Y-F, Gerstner, E.R., Catana, C., Deisboeck, T., Batchelor, T.T., Boas, D., Rosen, B., Kalpathy-Cramer, J., Chaplain, M.A.J. (2016) “Multimodality imaging and mathematical modelling of drug delivery to glioblastomas” Interface Focus 20160039,
  93. Bowness, R. (2016) “Systems medicine and infection” in Schmitz U. and Wolkenhauer O. (eds), “Systems Medicine. Methods in Molecular Biology” vol. 1386, Springer, 107-118
  94. Burgess, A.E.F., Schofield, P.G., Hubbard, S.F., Chaplain, M.A.J., Lorenzi, T., (2016) “Dynamical patterns of coexisting strategies in a hybrid discrete-continuum spatial evolutionary game model” Math. Mod. Nat. Phen., 11, 49-64.
  95. Chaplain, M.A.J., Tello, J.I. (2016) “On the stability of homogeneous steady states of a chemotaxis system with logistic growth term” Appl. Math. Lett., 57, 1-6. doi: 10.1016/j.aml.2015.12.001
  96. Chisholm, R.H., Lorenzi, T., Clairambault, J., (2016) “Cell population heterogeneity and evolution towards drug resistance in cancer: Biological and mathematical assessment, theoretical treatment optimisation” Biochim. Biophys. Acta – General Subjects, 1860, 2627-2645
  97. Chisholm, R.H., Lorenzi, T., Desvillettes, L., Hughes, B.D., (2016) “Evolutionary dynamics of phenotype-structured populations: From individual-level mechanisms to population-level consequences” Z. angew. Math. Phys., 67, 1-34
  98. Chisholm, R.H., Lorenzi, T., Lorz, A., (2016) “Effects of an advection term in nonlocal Lotka-Volterra equations” Commun. Math. Sci., 14, 1181-1188
  99. Delitala, M., Lorenzi, T., (2016) “Emergence of spatial patterns in a mathematical model for the co-culture dynamics of epithelial-like and mesenchymal-like cells” Math. Biosci. Eng., 14(1), 79-93.
  100. Eftimie, R., Macnamara, C.K., Dushoff, J., Bramson, J.L., Earn, D.J.D. (2016) “Bifurcations and chaotic dynamics in a tumour-immune-virus system” Math. Mod. Nat. Phen., 11(5), 135-155.
  101. Elliott, C.M., Ranner, T., Venkataraman, C. (2016) ” Coupled bulk-surface free boundary problems arising from a mathematical model of receptor-ligand dynamics ” SIAM J. Math. Anal., 49 (1), 360-397.
  102. Lorenzi, T., Chisholm, R.H., Clairambault, J., (2016) “Tracking the evolution of cancer cell populations through the mathematical lens of phenotype-structured equations” Biol. Direct, 11(1),43
  103. Macnamara, C.K., Chaplain, M.A.J. (2016) “Diffusion driven oscillations in gene regulatory networks” J. Theor. Biol., 407, 51-70.
  104. Powathil, G., Munro, A.J., Chaplain, M.A.J., Swat, M. (2016) “Bystander effects and their implications for clinical radiation therapy: Insights from multiscale in silico experiments” J. Theor. Biol., 401, 1-14.
  105. Upadhyay, R., Roy, P., Venkataraman, C., Madzvamuse, A. (2016) “Wave of chaos in a spatial eco-epidemiological system: Generating realistic patterns of patchiness in rabbit-lynx dynamics” Math. Biosci., 281, 98-119.
  106. Wei Yang, F., Venkataraman, C., Styles, V., Kuttenberger, V., Horn, E., von Guttenberg, Z., Madzvamuse, A., (2016) “A computational framework for particle and whole cell tracking applied to a real biological dataset” J. Biomech., 49, 1290-1304
  107. Wei Yang, F., Venkataraman, C., Styles, V., Madzvamuse, A., (2016) “A robust and efficient adaptive multigrid solver for the optimal control of phase field formulations of geometric evolution laws ” CiCP, 21(1), 65-92.
  108. 2015

  109. Blazakis, K. N., Madzvamuse, A., Reyes-Aldasoro, C. C., Styles, V., Venkataraman, C., (2015) “Whole cell tracking through the optimal control of geometric evolution laws” J. Comp. Phys., 297, 495-514
  110. Bowness, R., Boeree, M.J., Aarnoutse, R., Dawson, R., Diacon, A., Mangu, C., Heinrich, N., Ntinginya, N.E., Kohlenberg, A., Mtafya, B., Phillips, P.P.J., Rachow, A., Plemper van Balen, G., Gillespie, S.H., (2015) “The relationship between Mycobacterium tuberculosis MGIT time to positivity and cfu in sputum samples demonstrates changing bacterial phenotypes potentially reflecting the impact of chemotherapy on critical sub-populations” J. Antimicrob. Chemother., 70, 448-455
  111. Chaplain, M.A.J., Ptashnyk, M., Sturrock, M., (2015) “Hopf Bifurcation in a Gene Regulatory Network Model: Molecular Movement Causes Oscillations” Math. Mod. Meth. Appl. Sci., 25, 1179-1215
  112. Chaplain, M.A.J., Powathil, G.G., (2015) “Multiscale modelling of cancer progression and treatment control: The role of intracellular heterogeneities in chemotherapy treatment” Biophys. Rev. Lett., 10(2), 97-114.
  113. Chisholm, R.H., Lorenzi, T., Lorz, A., Larsen, A.K., Neves de Almeida, L., Escargueil, A., Clairambault, J., (2015) “Emergence of drug tolerance in cancer cell populations: An evolutionary outcome of selection, non-genetic instability and stress-induced adaptation”, Cancer Res., 75, 930-939
  114. Croft, W., Elliott, C. M., Ladds, G., Stinner, B., Venkataraman, C., Weston, C., (2015) “Parameter identification problems in the modelling of cell motility” J. Math. Biol., 71, 399-436
  115. Donald, I., Meyer, K., Gillespie, S.H., Bowness, R., Brengman, J., (2015) “Project Sanitarium: Gaming TB – A serious game for a serious problem” IEEE, Seventh International Conference on Virtual Worlds and Games for Serious Applications: VS-Games 2015, University of Skövde, Sweden, 16-18 September
  116. Elliott, C. M., Venkataraman, C., (2015) “Error analysis for an ALE evolving surface finite element method” Num. Meth. PDE, 31, 459-499
  117. Hill, L., Chaplain, M.A.J., Wolf, R., Kapelyukh, Y., (2015) “The usage of a three-compartment model to investigate the metabolic differences between hepatic reductase null and wild-type mice” Math. Med. Biol., 34(1), 1-13
  118. Kim, Y., Powathil, G.G., Kang, H., Trucu, D., Kim, H., Lawler, S., Chaplain, M.A.J., (2015) “Strategies of eradicating glioma cells: A multi-scale mathematical model with miR-451-AMPK-mTOR control” PLoS ONE 10(1): e0114370. doi:10.1371/journal.pone.0114370
  119. Lorenzi, T., Chisholm, R.H., Desvillettes, L., Hughes, B.D., (2015) “Dissecting the dynamics of epigenetic changes in phenotype-structured populations exposed to fluctuating environments”, J. Theor. Biol., 386, 166-76
  120. Lorenzi, T., Chisholm, R.H., Melensi, M., Lorz, A., Delitala, M., (2015) “Mathematical model reveals how regulating the three phases of T-cell response could counteract immune evasion”, Immunology, 46, 271-280.
  121. Macnamara, C.K., Eftimie, R. (2015) “Memory versus effector immune responses in oncolytic virotherapies ” J. Theor. Biol., 377, 1-9
  122. Madzvamuse, A., Chung, A.W., Venkataraman, C., (2015) “Stability analysis and simulations of coupled bulk-surface reaction-diffusion systems” Proc. Roy Soc. A, 471(2175)
  123. Powathil, G.G., Swat, M, Chaplain, M.A.J., (2015) “Systems oncology: Towards patient-specific treatment regimes informed by multiscale mathematical modelling” Sem. Cancer Biol., 30, 13-20
  124. Schlüeter, D.K., Ramis-Conde, I., Chaplain, M.A.J., (2015) “Multi-scale modelling of the dynamics of cell colonies: Insights into cell adhesion forces and cancer invasion from in silico simulations” J. R. Soc. Interface, 12: 20141080
  125. Sekimura T., Venkataraman, C., Madzvamuse, A., (2015) “A model for selection of eyespots on butterfly wings” PLoS ONE, 10(11):e0141434, 11
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The Group at a Glance

Contact us

Mathematical Biology group 
School of Mathematics and Statistics
University of St Andrews
Mathematical Institute
North Haugh
St Andrews
KY16 9SS

Phone: +44 (0)1334 46 3744