Uncertainty in Biology - A Computational Modeling Approach (Hardcover, 1st ed. 2016)

Computational modeling allows to reduce, refine and replace animal experimentation as well as to translate findings obtained in these experiments to the human background. However these biomedical problems are inherently complex with a myriad of influencing factors, which strongly complicates the model building and validation process. This book wants to address four main issues related to the building and validation of computational models of biomedical processes: 1. Modeling establishment under uncertainty 2. Model selection and parameter fitting 3. Sensitivity analysis and model adaptation 4. Model predictions under uncertainty In each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples. This book is intended for graduate students and researchers active in the field of computational modeling of biomedical processes who seek to acquaint themselves with the different ways in which to study the parameter space of their model as well as its overall behavior.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Mechanobiology, Tissue Engineering and Biomaterials, 17
Release date:	November 2015
First published:	2016
Editors:	Liesbet Geris • David Gomez-Cabrero
Dimensions:	235 x 155 x 27mm (L x W x T)
Format:	Hardcover
Pages:	478
Edition:	1st ed. 2016
ISBN-13:	978-3-319-21295-1
Categories:	Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Medicine > Nursing & ancillary services > Biomedical engineering > General Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematics for scientists & engineers Books > Science & Mathematics > Biology, life sciences > Life sciences: general issues > General
LSN:	3-319-21295-8
Barcode:	9783319212951

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