Linked Life Data

19045834

Source:http://linkedlifedata.com/resource/pubmed/id/19045834

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2008-12-2
pubmed:abstractText
One of the main aims of system biology is to understand the structure and dynamics of genomic systems. A computational approach, facilitated by new technologies for high-throughput quantitative experimental data, is put forward to investigate the regulatory system of dynamic interaction among genes in Kaposi's sarcoma-associated herpesvirus network after induction of lytic replication. A reconstruction of transcription factor activity and gene-regulatory kinetics using data from a time-course microarray experiment is proposed. The computational approach uses nonlinear differential equations. In particular, the quantitative Michaelis-Menten model of gene-regulatory kinetics is extended to allow for post-transcriptional modifications and synergic interactions between target genes and the Rta transcription factor. The kinetic method is developed within a Bayesian inferential framework using Markov chain Monte Carlo. The profile of the Rta transcriptional regulator, other post-transcriptional regulatory genes and gene-specific kinetic parameters are inferred from the gene expression data of the target genes. The method described here provides an example of a principled approach to handle a wide range of transcriptional network architectures and regulatory activation mechanisms to reconstruct the activity of several transcription factors and activation kinetic parameters in a single regulatory network.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
1751-8849
pubmed:author
pubmed:issnType
Print
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
385-96
pubmed:meshHeading
pubmed:year
2008
pubmed:articleTitle
Computational inference of replication and transcription activator regulator activity in herpesvirus from gene expression data.
pubmed:affiliation
University of Groningen (RUG), Institute of Mathematics and Computing Science, Groningen, Netherlands.
pubmed:publicationType
Journal Article