Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
11
pubmed:dateCreated
2006-12-14
pubmed:abstractText
The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and Caenorhabditis elegans. Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context.
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-11333967, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-11752246, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-11988575, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-12140549, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-12529635, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-12727512, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-14325149, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-14562095, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-14704431, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15066418, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15145574, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15369668, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15520792, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15608221, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-15616139, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-16701391, http://linkedlifedata.com/resource/pubmed/commentcorrection/17015299-9108003
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Dec
pubmed:issn
1742-5689
pubmed:author
pubmed:issnType
Print
pubmed:day
22
pubmed:volume
3
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
843-50
pubmed:dateRevised
2010-9-16
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
An entropic characterization of protein interaction networks and cellular robustness.
pubmed:affiliation
Max Planck Institute for Molecular Genetics, Ihnestr. 73, 14195 Berlin, Germany. manke@molgen.mpg.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't