Linked Life Data

17239859

Source:http://linkedlifedata.com/resource/pubmed/id/17239859

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2007-1-30
pubmed:abstractText
Parameters often are tuned with metabolite concentration time series data to build a dynamic model of metabolism. However, such tuning may reduce the extrapolation ability (generalization capability) of the model. In this study, we determined detailed kinetic parameters of three purified Escherichia coli glycolytic enzymes using the initial velocity method for individual enzymes; i.e., the parameters were determined independently from metabolite concentration time series data. The metabolite concentration time series calculated by the model using the parameters matched the experimental data obtained in an actual multi-enzyme system consisting of the three purified E. coli glycolytic enzymes. Thus, the results indicate that kinetic parameters can be determined without using an undesirable tuning process.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0014-5793
pubmed:author
pubmed:issnType
Print
pubmed:day
6
pubmed:volume
581
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
413-20
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
Dynamic simulation of an in vitro multi-enzyme system.
pubmed:affiliation
Institute for Advanced Biosciences, Keio University, Tsuruoka 997-0035, Japan.
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't