By Marcello Delitala, Giulia Ajmone Marsan
ISBN-10: 3319037587
ISBN-13: 9783319037585
ISBN-10: 3319037595
ISBN-13: 9783319037592
”Managing Complexity, decreasing Perplexity” is dedicated to an summary of the prestige of the paintings within the examine of advanced structures, with specific specialise in the research of structures bearing on dwelling topic. either senior scientists and younger researchers from varied and prestigious associations with a intentionally interdisciplinary minimize have been invited, as a way to evaluate methods and difficulties from various disciplines. the typical goal of the contributions used to be to research the complexity of dwelling structures via new mathematical paradigms which are extra adherent to truth and that are in a position to generate either exploratory and predictive types which are able to attaining a deeper perception into lifestyles technology phenomena.
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Additional resources for Managing Complexity, Reducing Perplexity: Modeling Biological Systems
Example text
By considering the processes which affect the cells on the lattice (proliferation, movement, phenotypic switching and death), and by assuming independence of the lattice sites we can derive master equations for the occupation probabilities of P- and M-cells. By taking the appropriate continuum limit we arrive at the following system of coupled PDEs which describe the density of P- and M-cells respectively: β ∂2 p ∂p = (1 − p − m) 2 + βp(1 − p − m) − (qm + μ) p + q p m ∂t 2 ∂x (1) ∂2 p v ∂ 2m ∂m = ((1 − p) 2 + m 2 ) − (q p + μ)m + qm p.
29(1), 49–65 (2012) 7. E. Khain, M. Katakowski, S. Hopkins, A. Szalad, X. Zheng, F. Jiang, M. Chopp, Collective behavior of brain tumor cells: the role of hypoxia. Phys. Rev. E 83(3), 031920 (2011). doi:10. 031920 8. D. Murray, Mathematical Biology II: Spatial Models and Biomedical Applications (Springer, Verlag, 1989) 9. R. C. D. Murray, A quantitative model for differential motility of gliomas in grey and white matter. Cell Prolif 33(5), 317–330 (2000) A Hybrid Model for E. coli Chemotaxis: From Signaling Pathway to Pattern Formation Franziska Matthäus Abstract In this article a hybrid model for the chemotactic motion of E.
Anderson, Hybrid models of tumor growth. WIREs Syst. Biol. Med. 3, 115–125 (2011) 57. E. Renshaw, Modelling Biological Populations in Space and Time (Cambridge University Press, Cambridge, 1991) 58. N. Shigesada, K. Kawasaki, Biological Invasions: Theory and Practice (Oxford University Press, Oxford, 1997) 59. G. Skellam, Random dispersal in theoretical populations. Biometrika 38, 196–218 (1951) 60. H. Smith, The Theory of the Chemostat (Cambridge University Press, Cambridge, 1995) 61. A. V. Stavrev, B.