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Computational Models of Vascularization and Therapy in Tumor Growth

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Mechanical and Chemical Signaling in Angiogenesis

Part of the book series: Studies in Mechanobiology, Tissue Engineering and Biomaterials ((SMTEB,volume 12))

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Abstract

Computational and mathematical models are powerful tools to study the complexity in biological systems. The models, when validated with experimental evidence, can then be used to better understand the behavior of a complex system subjected to perturbations. In particular, a computational model can be used to test new hypotheses and, in the case of therapies for instance, to predict and optimize treatment outcomes in patients. Most models in biology rely on the description, using continuous or discrete mathematical tools, of the time-course of one or several biological entities. Its aim is to ‘capture’ the dynamics of a process, which by definition evolve in time. Almost all biological processes are characterized by a particular dynamic. Computational modeling relies on the premise that integrating the dynamics of a process can provide benefits in its understanding compared to a classical static analysis.

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Authors and Affiliations

  1. INRIA Grenoble—Rhône-Alpes, Innovalée, 655 avenue de l’Europe, Montbonnot, 38334, Saint Ismier Cedex, France

    Benjamin Ribba & Floriane Lignet

  2. Department of Mathematics, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129, Turin, Italy

    Luigi Preziosi

Authors
  1. Benjamin Ribba
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  2. Floriane Lignet
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  3. Luigi Preziosi
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Correspondence to Benjamin Ribba .

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Editors and Affiliations

  1. Department of Biomedical Engineering, Cornell Univesity, Ithaca, USA

    Cynthia A. Reinhart-King

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Ribba, B., Lignet, F., Preziosi, L. (2013). Computational Models of Vascularization and Therapy in Tumor Growth. In: Reinhart-King, C. (eds) Mechanical and Chemical Signaling in Angiogenesis. Studies in Mechanobiology, Tissue Engineering and Biomaterials, vol 12. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30856-7_11

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  • DOI: https://doi.org/10.1007/978-3-642-30856-7_11

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