Linked Life Data

21823754

Source:http://linkedlifedata.com/resource/pubmed/id/21823754

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2011-8-9
pubmed:abstractText
Robustness, the ability of a system to function correctly in the presence of both internal and external uncertainty, has emerged as a key organising principle in many biological systems. Biological robustness has thus become a major focus of research in Systems Biology, particularly on the engineering-biology interface, since the concept of robustness was first rigorously defined in the context of engineering control systems. This review focuses on one particularly important aspect of robustness in Systems Biology, that is, the use of robustness analysis methods for the validation or invalidation of models of biological systems. With the explosive growth in quantitative modelling brought about by Systems Biology, the problem of validating, invalidating and discriminating between competing models of a biological system has become an increasingly important one. In this review, the authors provide a comprehensive overview of the tools and methods that are available for this task, and illustrate the wide range of biological systems to which this approach has been successfully applied.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Jul
pubmed:issn
1751-8849
pubmed:author
pubmed:issnType
Print
pubmed:volume
5
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
229-44
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Validation and invalidation of systems biology models using robustness analysis.
pubmed:affiliation
University of Exeter, College of Engineering, Mathematics and Physical Sciences, Exeter, UK. D.G.Bates@exeter.ac.uk
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't