| pubmed-article:10891285 | rdf:type | pubmed:Citation | lld:pubmed |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C0033684 | lld:lifeskim |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C0002518 | lld:lifeskim |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C0475264 | lld:lifeskim |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C1705938 | lld:lifeskim |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C1527178 | lld:lifeskim |
| pubmed-article:10891285 | lifeskim:mentions | umls-concept:C1706793 | lld:lifeskim |
| pubmed-article:10891285 | pubmed:issue | 4 | lld:pubmed |
| pubmed-article:10891285 | pubmed:dateCreated | 2000-8-15 | lld:pubmed |
| pubmed-article:10891285 | 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/. | lld:pubmed |
| pubmed-article:10891285 | pubmed:language | eng | lld:pubmed |
| pubmed-article:10891285 | pubmed:journal | http://linkedlifedata.com/r... | lld:pubmed |
| pubmed-article:10891285 | pubmed:citationSubset | IM | lld:pubmed |
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| pubmed-article:10891285 | pubmed:status | MEDLINE | lld:pubmed |
| pubmed-article:10891285 | pubmed:month | Jul | lld:pubmed |
| pubmed-article:10891285 | pubmed:issn | 0022-2836 | lld:pubmed |
| pubmed-article:10891285 | pubmed:author | pubmed-author:NielsenHH | lld:pubmed |
| pubmed-article:10891285 | pubmed:author | pubmed-author:von HeijneGG | lld:pubmed |
| pubmed-article:10891285 | pubmed:author | pubmed-author:BrunakSS | lld:pubmed |
| pubmed-article:10891285 | pubmed:author | pubmed-author:EmanuelssonOO | lld:pubmed |
| pubmed-article:10891285 | pubmed:copyrightInfo | Copyright 2000 Academic Press. | lld:pubmed |
| pubmed-article:10891285 | pubmed:issnType | Print | lld:pubmed |
| pubmed-article:10891285 | pubmed:day | 21 | lld:pubmed |
| pubmed-article:10891285 | pubmed:volume | 300 | lld:pubmed |
| pubmed-article:10891285 | pubmed:owner | NLM | lld:pubmed |
| pubmed-article:10891285 | pubmed:authorsComplete | Y | lld:pubmed |
| pubmed-article:10891285 | pubmed:pagination | 1005-16 | lld:pubmed |
| pubmed-article:10891285 | pubmed:dateRevised | 2006-11-15 | lld:pubmed |
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| pubmed-article:10891285 | pubmed:year | 2000 | lld:pubmed |
| pubmed-article:10891285 | pubmed:articleTitle | Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. | lld:pubmed |
| pubmed-article:10891285 | pubmed:affiliation | Stockholm Bioinformatics Center, Department of Biochemistry, Stockholm University, Stockholm, S-106 91, Sweden. | lld:pubmed |
| pubmed-article:10891285 | pubmed:publicationType | Journal Article | lld:pubmed |
| pubmed-article:10891285 | pubmed:publicationType | Research Support, Non-U.S. Gov't | lld:pubmed |
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