Cancer is a complex disease process that spans multiple scales in space and time. Driven by cutting-edge mathematical and computational techniques, in silico biology provides powerful tools to investigate the mechanistic relationships of genes, cells, and tissues. It enables the creation of experimentally testable hypotheses, the integration of data across scales, and the prediction of tumor progression and treatment outcome (in silico oncology).
Drawing on an interdisciplinary group of distinguished international experts, Multiscale Cancer Modeling discusses the scientific and technical expertise necessary to conduct innovative cancer modeling research across scales. It presents contributions from some of the top in silico modeling groups in the United States and Europe.
The ultimate goal of multiscale modeling and simulation approaches is their use in clinical practice, such as supporting patient-specific treatment optimization. This volume covers state-of-the-art methods of multiscale cancer modeling and addresses the field’s potential as well as future challenges. It encourages collaborations among researchers in various disciplines to achieve breakthroughs in cancer modeling.
"This volume covers state-of-the-art methods of multiscale cancer modeling and addresses the field's potential as well as future challenges … It presents contributions from some of the top in silico modeling groups in the United States and Europe."
Evolution, Regulation and Disruption of Homeostasis and Its Role in Carcinogenesis, A.R.A. Anderson, D. Basanta, P. Gerlee, and K.A. Rejniak
Cancer Cell: Linking Oncogenic Signaling to Molecular Structure, J.E. Purvis, A.J. Shih, Y. Liu, and R. Radhakrishnan
Has Cancer Sculpted the Genome? Modeling Linkage and the Role of Tetraploidy in Neoplastic Progression, C.C. Maley, W. Lewis, and B.J. Reid
Catastrophes and Complex Networks in Genomically Unstable Tumorigenesis, R. Sole
A Stochastic Multiscale Model Framework for Intestinal Stem Cell Homeostasis, L.W. Jean and E.G. Luebeck
Multiscale Modeling of Colonic Crypts and Early Colorectal Cancer, A.G. Fletcher, G.R. Mirams, P.J. Murray, A. Walter, J.-W. Kang, K.-H. Cho, P.K. Maini, and H.M. Byrne
The Physical Microenvironment in Somatic Evolution of Cancer, R.A. Gatenby
Multiscale Modeling of Cell Motion in Three-Dimensional Environments, D. Harjanto and M.H. Zaman
Simulating Cancer Growth with Agent-Based Models, Z. Wang, V. Bordas, J. Sagotsky, and T.S. Deisboeck
Diffusional Instability as a Mechanism of Tumor Invasion, H.B. Frieboes, J. Lowengrub, and V. Cristini
Continuum Models of Mesenchymal Cell Migration and Sprouting Angiogenesis, M. Bergdorf, F. Milde, and P. Koumoutsakos
Do Tumor Invasion Strategies Follow Basic Physical Laws?, C. Guiot, P.P. Delsanto, and A.S. Gliozzi
Multiscale Mathematical Modeling of Vascular Tumor Growth: An Exercise in Transatlantic Cooperation, M.A.J. Chaplain, P. Macklin, S. McDougall, A.R.A. Anderson, V. Cristini, and J. Lowengrub
A Multiscale Simulation Framework for Modeling Solid Tumor Growth with an Explicit Vessel Network, S. Hirsch, B. Lloyd, D. Szczerba, and G. Székely
Building Stochastic Models for Cancer Growth and Treatment, N.L. Komarova
Bridging from Multiscale Modeling to Practical Clinical Applications in the Study of Human Gliomas, G. Chakraborty, R. Sodt, S. Massey, S. Gu, R. Rockne, E.C. Alvord, Jr., and K.R. Swanson
Personalization of Reaction-Diffusion Tumor Growth Models in MR Images: Application to Brain Gliomas Characterization and Radiotherapy Planning, E. Konukoglu, O. Clatz, H. Delingette, and N. Ayache
In Silico Oncology Part I: Clinically Oriented Cancer Multilevel Modeling Based on Discrete Event Simulation, G.S. Stamatakos
In Silico Oncology Part II: Clinical Requirements, N. Graf