Source:http://linkedlifedata.com/resource/pubmed/id/10891285
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| Predicate | Object |
|---|---|
| rdf:type | |
| lifeskim:mentions | |
| pubmed:issue |
4
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| pubmed:dateCreated |
2000-8-15
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| pubmed:abstractText |
A neural network-based tool, TargetP, for large-scale subcellular location prediction of newly identified proteins has been developed. Using N-terminal sequence information only, it discriminates between proteins destined for the mitochondrion, the chloroplast, the secretory pathway, and "other" localizations with a success rate of 85% (plant) or 90% (non-plant) on redundancy-reduced test sets. From a TargetP analysis of the recently sequenced Arabidopsis thaliana chromosomes 2 and 4 and the Ensembl Homo sapiens protein set, we estimate that 10% of all plant proteins are mitochondrial and 14% chloroplastic, and that the abundance of secretory proteins, in both Arabidopsis and Homo, is around 10%. TargetP also predicts cleavage sites with levels of correctly predicted sites ranging from approximately 40% to 50% (chloroplastic and mitochondrial presequences) to above 70% (secretory signal peptides). TargetP is available as a web-server at http://www.cbs.dtu.dk/services/TargetP/.
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| pubmed:language |
eng
|
| pubmed:journal | |
| pubmed:citationSubset |
IM
|
| pubmed:chemical | |
| pubmed:status |
MEDLINE
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| pubmed:month |
Jul
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| pubmed:issn |
0022-2836
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| pubmed:author | |
| pubmed:copyrightInfo |
Copyright 2000 Academic Press.
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| pubmed:issnType |
Print
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| pubmed:day |
21
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| pubmed:volume |
300
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| pubmed:owner |
NLM
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| pubmed:authorsComplete |
Y
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| pubmed:pagination |
1005-16
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| pubmed:dateRevised |
2006-11-15
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| pubmed:meshHeading |
pubmed-meshheading:10891285-Amino Acid Sequence,
pubmed-meshheading:10891285-Arabidopsis,
pubmed-meshheading:10891285-Biological Transport,
pubmed-meshheading:10891285-Chloroplasts,
pubmed-meshheading:10891285-Cytoplasm,
pubmed-meshheading:10891285-Databases, Factual,
pubmed-meshheading:10891285-Humans,
pubmed-meshheading:10891285-Internet,
pubmed-meshheading:10891285-Mitochondria,
pubmed-meshheading:10891285-Molecular Sequence Data,
pubmed-meshheading:10891285-Neural Networks (Computer),
pubmed-meshheading:10891285-Nuclear Proteins,
pubmed-meshheading:10891285-Plant Proteins,
pubmed-meshheading:10891285-Protein Processing, Post-Translational,
pubmed-meshheading:10891285-Protein Sorting Signals,
pubmed-meshheading:10891285-Proteins,
pubmed-meshheading:10891285-Reproducibility of Results,
pubmed-meshheading:10891285-Sensitivity and Specificity,
pubmed-meshheading:10891285-Software
|
| pubmed:year |
2000
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| pubmed:articleTitle |
Predicting subcellular localization of proteins based on their N-terminal amino acid sequence.
|
| pubmed:affiliation |
Stockholm Bioinformatics Center, Department of Biochemistry, Stockholm University, Stockholm, S-106 91, Sweden.
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| pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't
|