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All issues Volume 7 / No 1 (2012) Math. Model. Nat. Phenom., 7 1 (2012) 245-260 References
Free Access
Issue
Math. Model. Nat. Phenom.
Volume 7, Number 1, 2012
Cancer modeling
Page(s) 245 - 260
DOI https://doi.org/10.1051/mmnp/20127111
Published online 25 January 2012
  1. A. Marciniak-Czochra, M. Kimmel. Reaction-difusion model of early carcinogenesis : The effects of influx of mutated cells. Mathematical Modelling of Natural Phenomena, 3 (2008), No. 7, 90–114. [CrossRef] [Google Scholar]
  2. A. Marciniak-Czochra, M. Kimmel. Dynamics of growth and signaling along linear and surface structures in very early tumors. Computational & Mathematical Methods in Medicine, 7 (2006), No. 2/3, 189–213. [CrossRef] [Google Scholar]
  3. A. Marciniak-Czochra, M. Kimmel. Modelling of early lung cancer progression : Influence of growth factor production and cooperation between partially transformed cells. Math. Mod. Meth. Appl. Sci., 17S (2007), 1693–1719. [CrossRef] [Google Scholar]
  4. A. Marciniak-Czochra, M. Kimmel. Reaction–diffusion approach to modeling of the spread of early tumors along linear or tubular structures. Journal of Theoretical Biology, 244 (2006), No. 3, 375–387. [CrossRef] [PubMed] [Google Scholar]
  5. A. Marciniak-Czochra, M. Ptashnyk. Derivation of a macroscopic receptor-based model using homogenization techniques. SIAM J. Math. Anal., 40 (2008), No. 1, 215–237. [CrossRef] [MathSciNet] [Google Scholar]
  6. A. Marciniak-Czochra, G. Karch, K. Suzuki. Unstable patterns in reaction-diffusion model of early carcinogenesis. arXiv :1104.3592v1, (2011). [Google Scholar]
  7. R. Bertolusso. Computational models of signaling processes in cells with applications : Influence of stochastic and spatial effects. PhD thesis (2011), Rice University, Houston, TX. [Google Scholar]
  8. R. Erban, S. J. Chapman, P. Maini. A practical guide to stochastic simulations of reaction-diffusion processes. ArXiv e-prints, (2007), April. [Google Scholar]
  9. S. A. Isaacson, C. S. Peskin. Incorporating diffusion in complex geometries into stochastic chemical kinetics simulations. SIAM J. Scientific Computing, 28 (2006), No. 1, 47–74. [CrossRef] [Google Scholar]
  10. A. Slepoy, A. P. Thompson, S. J. Plimpton. A constant-time kinetic monte carlo algorithm for simulation of large biochemical reaction networks. J. Chem. Phys., 128 (2008), May, 205101. [CrossRef] [PubMed] [Google Scholar]
  11. J. Paulsson, O. G. Berg, M. Ehrenberg. Stochastic focusing : fluctuation-enhanced sensitivity of intracellular regulation. Proc. Natl. Acad. Sci. U.S.A., 97 (2000), June, 7148–53. [Google Scholar]

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