Linked Life Data

8544489

Source:http://linkedlifedata.com/resource/pubmed/id/8544489

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1-2
pubmed:dateCreated
1996-2-14
pubmed:abstractText
The measurement of individual single-channel events arising from the gating of ion channels provides a detailed data set from which the kinetic mechanism of a channel can be deduced. In many cases, the pattern of dwells in the open and closed states is very complex, and the kinetic mechanism and parameters are not easily determined. Assuming a Markov model for channel kinetics, the probability density function for open and closed time dwells should consist of a sum of decaying exponentials. One method of approaching the kinetic analysis of such a system is to determine the number of exponentials and the corresponding parameters which comprise the open and closed dwell time distributions. These can then be compared to the relaxations predicted from the kinetic model to determine, where possible, the kinetic constants. We report here the use of a linear technique, linear prediction/singular value decomposition, to determine the number of exponentials and the exponential parameters. Using simulated distributions and comparing with standard maximum-likelihood analysis, the singular value decomposition techniques provide advantages in some situations and are a useful adjunct to other single-channel analysis techniques.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0165-0270
pubmed:author
pubmed:issnType
Print
pubmed:volume
60
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
69-78
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
1995
pubmed:articleTitle
Linear prediction and single-channel recording.
pubmed:affiliation
Department of Pharmacology, College of Veterinary Medicine, Cornell University, Ithaca, NY 14853, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S.