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Predicting subcellular localization of proteins based on their N-terminal amino acid sequence.
Stockholms unviersitet.ORCID iD: 0000-0002-8879-9245
Center for Biological Sequence Analysis, Technical University of Denmark.
Center for Biological Sequence Analysis, Technical University of Denmark.
Stockholms universitet.
2000 (English)In: Journal of Molecular Biology, ISSN 0022-2836, E-ISSN 1089-8638, Vol. 300, no 4, 1005-1016 p.Article in journal (Refereed) Published
Abstract [en]

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/.

Place, publisher, year, edition, pages
2000. Vol. 300, no 4, 1005-1016 p.
Keyword [en]
protein sorting, genome annotation, neural networks, targeting sequences, cleavage sites
National Category
Bioinformatics and Systems Biology
Identifiers
URN: urn:nbn:se:kth:diva-50449DOI: 10.1006/jmbi.2000.3903ISI: 000088508500026PubMedID: 10891285OAI: oai:DiVA.org:kth-50449DiVA: diva2:461890
Available from: 2011-12-05 Created: 2011-12-05 Last updated: 2017-12-08Bibliographically approved

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Emanuelsson, Olof

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  • apa
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  • modern-language-association-8th-edition
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