Linked Life Data

21281499

Source:http://linkedlifedata.com/resource/pubmed/id/21281499

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2011-2-15
pubmed:abstractText
With the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1752-0509
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
5
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
21
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data.
pubmed:affiliation
Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Germany.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't