Linked Life Data

9790834

Source:http://linkedlifedata.com/resource/pubmed/id/9790834

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
1998-12-15
pubmed:abstractText
Predicting function from sequence using computational tools is a highly complicated procedure that is generally done for each gene individually. This review focuses on the added value that is provided by completely sequenced genomes in function prediction. Various levels of sequence annotation and function prediction are discussed, ranging from genomic sequence to that of complex cellular processes. Protein function is currently best described in the context of molecular interactions. In the near future it will be possible to predict protein function in the context of higher order processes such as the regulation of gene expression, metabolic pathways and signalling cascades. The analysis of such higher levels of function description uses, besides the information from completely sequenced genomes, also the additional information from proteomics and expression data. The final goal will be to elucidate the mapping between genotype and phenotype.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Nov
pubmed:issn
0022-2836
pubmed:author
pubmed:copyrightInfo
Copyright 1998 Academic Press.
pubmed:issnType
Print
pubmed:day
6
pubmed:volume
283
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
707-25
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
1998
pubmed:articleTitle
Predicting function: from genes to genomes and back.
pubmed:affiliation
European Molecular Biology Laboratory, Meyerhofstr. 1, Heidelberg, PF 10.2209, Germany. Bork@EMBL-Heidelberg.de
pubmed:publicationType
Journal Article, Review, Research Support, Non-U.S. Gov't