By Marcello Delitala, Giulia Ajmone Marsan
”Managing Complexity, lowering Perplexity” is dedicated to an summary of the prestige of the artwork within the examine of advanced structures, with specific concentrate on the research of structures relating residing topic. either senior scientists and younger researchers from assorted and prestigious associations with a intentionally interdisciplinary reduce have been invited, so that it will evaluate methods and difficulties from various disciplines. the typical objective of the contributions was once to research the complexity of dwelling platforms through new mathematical paradigms which are extra adherent to fact and that are in a position to generate either exploratory and predictive versions which are able to reaching a deeper perception into existence technological know-how phenomena.
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Extra info for Managing Complexity, Reducing Perplexity: Modeling Biological Systems
It is believed that many drugs have precisely this dual impact on both proliferation and migration, and estimating the tissue-level of these perturbations effect will be difficult, if not impossible without the use of mathematical models such as this one. References 1. M. Aubert, M. Badoual, C. Christov, B. Grammaticos, A model for glioma cell migration on collagen and astrocytes. J. R. Soc. Interface 5(18), 75 (2008) 2. A. O. Suzuki, M. E. N. Bruce, P. Canoll, Transplanted glioma cells migrate and proliferate on host brain vasculature: a dynamic analysis.
Coli, coupled with a continuous description (PDE) for the dynamics of external chemical substances. The model allows to simulate movements of individual cells as well as large-scale population behavior. It provides a tool to study bacterial pattern formation processes or competition of different species under the influence of internal signaling processes. F. de M. Delitala and G. 1007/978-3-319-03759-2_4, © Springer International Publishing Switzerland 2014 37 38 F. Matthäus The choice of E. coli bacteria as a model organism is straight forward.
Neurol. Sci. 216, 110 (2003) 63. E. Weldon, Mathematical Models in Cancer Research (Adam Hilger, Philadelphia, 1988) 64. M. A. B. Frieboes, V. Cristini, Three-dimensional multispecies nonlinear tumor growth—I. J. Theor. Biol. 253, 524–543 (2008) 65. H. Youssefpour, X. D. S. Lowengrub, Multispecies model of cell lineages and feedback control in solid tumors. J. Theor. Biol. 304, 39–59 (2012) 66. M. N. Minerbo, Tumor control probability: a formulation applicable to any temporal protocol of dose delivery.