Uncertainty in Biology

A Computational Modeling Approach

Nonfiction, Computers, Advanced Computing, Computer Science, Science & Nature, Technology, Engineering, Health & Well Being, Medical
Cover of the book Uncertainty in Biology by , Springer International Publishing
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: ISBN: 9783319212968
Publisher: Springer International Publishing Publication: October 26, 2015
Imprint: Springer Language: English
Author:
ISBN: 9783319212968
Publisher: Springer International Publishing
Publication: October 26, 2015
Imprint: Springer
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Springer International Publishing

Cover of the book Sociality and Normativity for Robots by
Cover of the book Tourist Behavior by
Cover of the book Information Systems Architecture and Technology: Proceedings of 37th International Conference on Information Systems Architecture and Technology – ISAT 2016 – Part II by
Cover of the book Heat Shock Protein Inhibitors by
Cover of the book Redox-Active Therapeutics by
Cover of the book Assistive Technologies for the Interaction of the Elderly by
Cover of the book Love and Sex with Robots by
Cover of the book Descent of the Testis by
Cover of the book Artificial Life and Intelligent Agents by
Cover of the book Asbestos and Mesothelioma by
Cover of the book Real-time Monitoring and Operational Control of Drinking-Water Systems by
Cover of the book Public International Law of Cyberspace by
Cover of the book Advances in Heat Transfer Enhancement by
Cover of the book Animals and the Fukushima Nuclear Disaster by
Cover of the book Advanced Concepts for Intelligent Vision Systems by
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy