Linked Life Data

17406631

Source:http://linkedlifedata.com/resource/pubmed/id/17406631

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
3
pubmed:dateCreated
2007-4-4
pubmed:abstractText
We here describe the MetaNetwork protocol to reconstruct metabolic networks using metabolite abundance data from segregating populations. MetaNetwork maps metabolite quantitative trait loci (mQTLs) underlying variation in metabolite abundance in individuals of a segregating population using a two-part model to account for the often observed spike in the distribution of metabolite abundance data. MetaNetwork predicts and visualizes potential associations between metabolites using correlations of mQTL profiles, rather than of abundance profiles. Simulation and permutation procedures are used to assess statistical significance. Analysis of about 20 metabolite mass peaks from a mass spectrometer takes a few minutes on a desktop computer. Analysis of 2,000 mass peaks will take up to 4 days. In addition, MetaNetwork is able to integrate high-throughput data from subsequent metabolomics, transcriptomics and proteomics experiments in conjunction with traditional phenotypic data. This way MetaNetwork will contribute to a better integration of such data into systems biology.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1750-2799
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
2
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
685-94
pubmed:dateRevised
2008-11-21
pubmed:meshHeading
pubmed:year
2007
pubmed:articleTitle
MetaNetwork: a computational protocol for the genetic study of metabolic networks.
pubmed:affiliation
Groningen Bioinformatics Centre, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Kerklaan 30, NL-9751 NN Haren, The Netherlands.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't