Uncertainty in Biology

By: Liesbet Geris and David Gomez-Cabrero

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Synopsis: 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.

Book Quality:: Publisher Quality
ISBN-13:: 9783319212968
Publisher:: Springer International Publishing, Cham
Date of Addition:: 11/15/16
Copyrighted By:: Springer
Adult content:: No
Language:: English
Has Image Descriptions:: No
Categories:: Nonfiction, Science, Computers and Internet, Mathematics and Statistics, Medicine
Submitted By:: Bookshare Staff
Usage Restrictions:: This is a copyrighted book.