Linked Life Data

15174128

Source:http://linkedlifedata.com/resource/pubmed/id/15174128

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
6
pubmed:dateCreated
2004-6-2
pubmed:abstractText
Probably more than 25% of the proteins encoded by the nuclear genomes of multicellular eukaryotes are targeted to membrane-bound compartments by N-terminal targeting signals. The major signals are those for the endoplasmic reticulum, the mitochondria, and in plants, plastids. The most abundant of these targeted proteins are well-known and well-studied, but a large proportion remain unknown, including most of those involved in regulation of organellar gene expression or regulation of biochemical pathways. The discovery and characterization of these proteins by biochemical means will be long and difficult. An alternative method is to identify candidate organellar proteins via their characteristic N-terminal targeting sequences. We have developed a neural network-based approach (Predotar--Prediction of Organelle Targeting sequences) for identifying genes encoding these proteins amongst eukaryotic genome sequences. The power of this approach for identifying and annotating novel gene families has been illustrated by the discovery of the pentatricopeptide repeat family.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Jun
pubmed:issn
1615-9853
pubmed:author
pubmed:issnType
Print
pubmed:volume
4
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
1581-90
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Predotar: A tool for rapidly screening proteomes for N-terminal targeting sequences.
pubmed:affiliation
Station de Génétique et Amélioration des Plantes, INRA, Versailles, France. small@evry.inra.fr
pubmed:publicationType
Journal Article, Comparative Study, Research Support, Non-U.S. Gov't