Linked Life Data

17091578

Source:http://linkedlifedata.com/resource/pubmed/id/17091578

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2006-11-9
pubmed:abstractText
The activities and interactions of proteins that govern the cellular response to a signal generate a multitude of protein phosphorylation states and heterogeneous protein complexes. Here, using a computational model that accounts for 307 molecular species implied by specified interactions of four proteins involved in signalling by the immunoreceptor FcepsilonRI, we determine the relative importance of molecular species that can be generated during signalling, chemical transitions among these species, and reaction paths that lead to activation of the protein tyrosine kinase (PTK) Syk. By all of these measures and over two- and ten-fold ranges of model parameters--rate constants and initial concentrations--only a small portion of the biochemical network is active. The spectrum of active complexes, however, can be shifted dramatically, even by a change in the concentration of a single protein, which suggests that the network can produce qualitatively different responses under different cellular conditions and in response to different inputs. Reduced models that reproduce predictions of the full model for a particular set of parameters lose their predictive capacity when parameters are varied over two-fold ranges.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Mar
pubmed:issn
1741-2471
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5-15
pubmed:dateRevised
2011-11-2
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Combinatorial complexity and dynamical restriction of network flows in signal transduction.
pubmed:affiliation
Theoretical Biology and Biophysics Group, Theoretical Division, Los Alamos National Laboratory, New Mexico 87545, USA. faeder@lanl.gov
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, Non-P.H.S., Research Support, N.I.H., Extramural