Linked Life Data

12547764

Source:http://linkedlifedata.com/resource/pubmed/id/12547764

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
2 Pt 1
pubmed:dateCreated
2003-1-27
pubmed:abstractText
It is now possible to construct genome-scale metabolic networks for particular microorganisms. Extreme pathway analysis is a useful method for analyzing the phenotypic capabilities of these networks. Many extreme pathways are needed to fully describe the functional capabilities of genome-scale metabolic networks, and therefore, a need exists to develop methods to study these large sets of extreme pathways. Singular value decomposition (SVD) of matrices of extreme pathways was used to develop a conceptual framework for the interpretation of large sets of extreme pathways and the steady-state flux solution space they define. The key results of this study were: 1), convex steady-state solution cones describing the potential functions of biochemical networks can be studied using the modes generated by SVD; 2), Helicobacter pylori has a more rigid metabolic network (i.e., a lower dimensional solution space and a more dominant first singular value) than Haemophilus influenzae for the production of amino acids; and 3), SVD allows for direct comparison of different solution cones resulting from the production of different amino acids. SVD was used to identify key network branch points that may identify key control points for regulation. Therefore, SVD of matrices of extreme pathways has proved to be a useful method for analyzing the steady-state solution space of genome-scale metabolic networks.
pubmed:grant
pubmed:commentsCorrections
http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-10364169, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-10700151, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-10716907, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-10716908, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-10963673, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-11246024, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-11881832, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-11983907, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-11997342, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12051985, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12080101, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12115428, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12124266, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12142428, http://linkedlifedata.com/resource/pubmed/commentcorrection/12547764-12466293
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
0006-3495
pubmed:author
pubmed:issnType
Print
pubmed:volume
84
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
794-804
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
Analysis of metabolic capabilities using singular value decomposition of extreme pathway matrices.
pubmed:affiliation
Department of Bioengineering, University of California/San Diego, La Jolla, California 92093-0412, USA.
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't, Evaluation Studies, Validation Studies