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Books > Science & Mathematics > Physics > Applied physics & special topics > Biophysics
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Computational Modeling in Tissue Engineering (Hardcover, 2013 ed.)
Loot Price: R3,773
Discovery Miles 37 730
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Computational Modeling in Tissue Engineering (Hardcover, 2013 ed.)
Series: Studies in Mechanobiology, Tissue Engineering and Biomaterials, 10
Expected to ship within 12 - 17 working days
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Total price: R3,793
Discovery Miles: 37 930
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One of the major challenges in tissue engineering is the
translation of biological knowledge on complex cell and tissue
behavior into a predictive and robust engineering process.
Mastering this complexity is an essential step towards clinical
applications of tissue engineering. This volume discusses
computational modeling tools that allow studying the biological
complexity in a more quantitative way. More specifically,
computational tools can help in: (i) quantifying and optimizing the
tissue engineering product, e.g. by adapting scaffold design to
optimize micro-environmental signals or by adapting selection
criteria to improve homogeneity of the selected cell population;
(ii) quantifying and optimizing the tissue engineering process,
e.g. by adapting bioreactor design to improve quality and quantity
of the final product; and (iii) assessing the influence of the in
vivo environment on the behavior of the tissue engineering product,
e.g. by investigating vascular ingrowth. The book presents examples
of each of the above mentioned areas of computational modeling. The
underlying tissue engineering applications will vary from blood
vessels over trachea to cartilage and bone. For the chapters
describing examples of the first two areas, the main focus is on
(the optimization of) mechanical signals, mass transport and fluid
flow encountered by the cells in scaffolds and bioreactors as well
as on the optimization of the cell population itself. In the
chapters describing modeling contributions in the third area, the
focus will shift towards the biology, the complex interactions
between biology and the micro-environmental signals and the ways in
which modeling might be able to assist in investigating and
mastering this complexity. The chapters cover issues related to
(multiscale/multiphysics) model building, training and validation,
but also discuss recent advances in scientific computing techniques
that are needed to implement these models as well as new tools that
can be used to experimentally validate the computational results.
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