Linked Life Data

17085845

Source:http://linkedlifedata.com/resource/pubmed/id/17085845

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2006-11-6
pubmed:abstractText
The classic view of metabolism as a collection of metabolic pathways is being questioned with the currently available possibility of studying whole networks. Novel ways of decomposing the network into modules and motifs that could be considered as the building blocks of a network are being suggested. In this work, we introduce a new definition of motif in the context of metabolic networks. Unlike in previous works on (other) biochemical networks, this definition is not based only on topological features. We propose instead to use an alternative definition based on the functional nature of the components that form the motif, which we call a reaction motif. After introducing a formal framework motivated by biological considerations, we present complexity results on the problem of searching for all occurrences of a reaction motif in a network and introduce an algorithm that is fast in practice in most situations. We then show an initial application to the study of pathway evolution. Finally, we give some general features of the observed number of occurrences in order to highlight some structural features of metabolic networks.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:issn
1545-5963
pubmed:author
pubmed:issnType
Print
pubmed:volume
3
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
360-8
pubmed:meshHeading
pubmed:articleTitle
Motif search in graphs: application to metabolic networks.
pubmed:affiliation
Equipe BAOBAB, Laboratoire de Biométrie et Biologie Evolutive, CNRS, Univ. Lyon, Villeurbanne, France. lacroix@biomserv.univ-lyon1.fr
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't