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PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea
The subcellular localization (SCL) of a microbial protein provides clues about its function, its suitability as a drug, vaccine or diagnostic target and aids experimental design. The first version of PSORTdb provided a valuable resource comprising a data set of proteins of known SCL (ePSORTdb) as we...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2011
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013690/ https://www.ncbi.nlm.nih.gov/pubmed/21071402 http://dx.doi.org/10.1093/nar/gkq1093 |
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author | Yu, Nancy Y. Laird, Matthew R. Spencer, Cory Brinkman, Fiona S.L. |
author_facet | Yu, Nancy Y. Laird, Matthew R. Spencer, Cory Brinkman, Fiona S.L. |
author_sort | Yu, Nancy Y. |
collection | PubMed |
description | The subcellular localization (SCL) of a microbial protein provides clues about its function, its suitability as a drug, vaccine or diagnostic target and aids experimental design. The first version of PSORTdb provided a valuable resource comprising a data set of proteins of known SCL (ePSORTdb) as well as pre-computed SCL predictions for proteomes derived from complete bacterial genomes (cPSORTdb). PSORTdb 2.0 (http://db.psort.org) extends user-friendly functionalities, significantly expands ePSORTdb and now contains pre-computed SCL predictions for all prokaryotes—including Archaea and Bacteria with atypical cell wall/membrane structures. cPSORTdb uses the latest version of the SCL predictor PSORTb (version 3.0), with higher genome prediction coverage and functional improvements over PSORTb 2.0, which has been the most precise bacterial SCL predictor available. PSORTdb 2.0 is the first microbial protein SCL database reported to have an automatic updating mechanism to regularly generate SCL predictions for deduced proteomes of newly sequenced prokaryotic organisms. This updating approach uses a novel sequence analysis we developed that detects whether the microbe being analyzed has an outer membrane. This identification of membrane structure permits appropriate SCL prediction in an auto-updated fashion and allows PSORTdb to serve as a practical resource for genome annotation and prokaryotic research. |
format | Text |
id | pubmed-3013690 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-30136902011-01-03 PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea Yu, Nancy Y. Laird, Matthew R. Spencer, Cory Brinkman, Fiona S.L. Nucleic Acids Res Articles The subcellular localization (SCL) of a microbial protein provides clues about its function, its suitability as a drug, vaccine or diagnostic target and aids experimental design. The first version of PSORTdb provided a valuable resource comprising a data set of proteins of known SCL (ePSORTdb) as well as pre-computed SCL predictions for proteomes derived from complete bacterial genomes (cPSORTdb). PSORTdb 2.0 (http://db.psort.org) extends user-friendly functionalities, significantly expands ePSORTdb and now contains pre-computed SCL predictions for all prokaryotes—including Archaea and Bacteria with atypical cell wall/membrane structures. cPSORTdb uses the latest version of the SCL predictor PSORTb (version 3.0), with higher genome prediction coverage and functional improvements over PSORTb 2.0, which has been the most precise bacterial SCL predictor available. PSORTdb 2.0 is the first microbial protein SCL database reported to have an automatic updating mechanism to regularly generate SCL predictions for deduced proteomes of newly sequenced prokaryotic organisms. This updating approach uses a novel sequence analysis we developed that detects whether the microbe being analyzed has an outer membrane. This identification of membrane structure permits appropriate SCL prediction in an auto-updated fashion and allows PSORTdb to serve as a practical resource for genome annotation and prokaryotic research. Oxford University Press 2011-01 2010-11-10 /pmc/articles/PMC3013690/ /pubmed/21071402 http://dx.doi.org/10.1093/nar/gkq1093 Text en © The Author(s) 2010. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/2.5 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Yu, Nancy Y. Laird, Matthew R. Spencer, Cory Brinkman, Fiona S.L. PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title | PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title_full | PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title_fullStr | PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title_full_unstemmed | PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title_short | PSORTdb—an expanded, auto-updated, user-friendly protein subcellular localization database for Bacteria and Archaea |
title_sort | psortdb—an expanded, auto-updated, user-friendly protein subcellular localization database for bacteria and archaea |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3013690/ https://www.ncbi.nlm.nih.gov/pubmed/21071402 http://dx.doi.org/10.1093/nar/gkq1093 |
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