An introduction to uncertainty in the development of computational models of biological processes

Geris, Liesbet; Gomez-Cabrero, David

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An introduction to uncertainty in the development of computational models of biological processes

Geris, Liesbet; Gomez-Cabrero, David

2015 • In Modeling under uncertainty: a computational modeling approach

Peer reviewed

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https://hdl.handle.net/2268/183862

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Abstract :

[en] This chapter aims to provide an introduction to the different ways in which uncertainty can be dealt with computational modelling of biological processes. The first step is model establishment under uncertainty. Once models have been established, data can further be used to select which of the proposed models best meets the predefined criteria. Subsequently, parameter values can be optimized for a specific model configuration. Sensitivity analyses allow to assess the influence of the previous choices on the model output. Additionally, model adaptation permits to focus on specific aspects of the model without losing its global predictive capacity. Finally, predictions with the established models should also consider the effect of uncertainty in the model development process.

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Geris, Liesbet ; Université de Liège > Département d'aérospatiale et mécanique > Génie biomécanique

Gomez-Cabrero, David

Language :

English

Title :

An introduction to uncertainty in the development of computational models of biological processes

Publication date :

2015

Main work title :

Modeling under uncertainty: a computational modeling approach

Publisher :

Springer

ISBN/EAN :

978-3-319-21295-1

Peer reviewed :

Peer reviewed

European Projects :

FP7 - 279100 - BRIDGE - Biomimetic process design for tissue regeneration: from bench to bedside via in silico modelling

Funders :

CE - Commission Européenne [BE]

Available on ORBi :

since 08 July 2015

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Bibliography

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