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Wiley Interdisciplinary Reviews Systems Biology and Medicine
Article . 2011 . Peer-reviewed
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Integrative physical oncology

Authors: Hatzikirou, H.; Chauviere, A.; Bauer, A.L.; Leier, A.; Lewis, Michael T.; Macklin, Paul; Marquez-Lago, Tatiana T.; +2 Authors

Integrative physical oncology

Abstract

AbstractCancer is arguably the ultimate complex biological system. Solid tumors are microstructured soft matter that evolves as a consequence of spatio‐temporal events at the intracellular (e.g., signaling pathways, macromolecular trafficking), intercellular (e.g., cell–cell adhesion/communication), and tissue (e.g., cell–extracellular matrix interactions, mechanical forces) scales. To gain insight, tumor and developmental biologists have gathered a wealth of molecular, cellular, and genetic data, including immunohistochemical measurements of cell type‐specific division and death rates, lineage tracing, and gain‐of‐function/loss‐of‐function mutational analyses. These data are empirically extrapolated to a diagnosis/prognosis of tissue‐scale behavior, e.g., for clinical decision. Integrative physical oncology (IPO) is the science that develops physically consistent mathematical approaches to address the significant challenge of bridging the nano (nm)–micro (µm) to macro (mm, cm) scales with respect to tumor development and progression. In the current literature, such approaches are referred to as multiscale modeling. In the present article, we attempt to assess recent modeling approaches on each separate scale and critically evaluate the current ‘hybrid‐multiscale’ models used to investigate tumor growth in the context of brain and breast cancers. Finally, we provide our perspective on the further development and the impact of IPO. WIREs Syst Biol Med 2012, 4:1–14. doi: 10.1002/wsbm.158This article is categorized under: Analytical and Computational Methods > Computational Methods

Country
United Kingdom
Keywords

Male, 570, Brain Neoplasms, 610, Calcinosis, Cell Polarity, Breast Neoplasms, Medical Oncology, Models, Biological, Cell Hypoxia, Mutation, Neoplastic Stem Cells, Humans, Computer Simulation, Female, Neoplasm Invasiveness

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    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    22
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
22
Average
Top 10%
Top 10%
bronze
Related to Research communities
Cancer Research