Contribution to collective works (Parts of books)
Computational modeling under uncertainty: challenges and opportunities
Gomez-Cabrero, David; Tegner, Jesper; Geris, Liesbet
2015In Modeling under uncertainty: a computational modeling approach
Peer reviewed
 

Files


Full Text
C18_Computational modeling_future_2015_03_v24_FINAL.pdf
Author preprint (145.02 kB)
Download

All documents in ORBi are protected by a user license.

Send to



Details



Abstract :
[en] Computational Biology has increasingly become an important tool for biomedical and translational research. In particular, when generating novel hypothesis despite fundamental uncertainties in data and mechanistic understanding of biological processes underpinning diseases. While in the present book, we have reviewed the necessary background and existing novel methodologies that set the basis for dealing with uncertainty, there are still many “grey”, or less well-defined, areas of investigations offering both challenges and opportunities. This final chapter in the book provides some reflections on those areas, namely: (1) the need for novel robust mathematical and statistical methodologies to generate hypothesis under uncertainty; (2) the challenge of aligning those methodologies in a context that requires larger computational resources; (3) the accessibility of modeling tools for less mathematical literate researchers; and (4) the integration of models with –omics data and its application in clinical environments.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Gomez-Cabrero, David
Tegner, Jesper
Geris, Liesbet  ;  Université de Liège - ULiège > Département d'aérospatiale et mécanique > Génie biomécanique
Language :
English
Title :
Computational modeling under uncertainty: challenges and opportunities
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

Statistics


Number of views
101 (0 by ULiège)
Number of downloads
590 (0 by ULiège)

Scopus citations®
 
0
Scopus citations®
without self-citations
0

Bibliography


Similar publications



Contact ORBi