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SPD—a web-based secreted protein database
With the improved secreted protein prediction approach and comprehensive data sources, including Swiss-Prot, TrEMBL, RefSeq, Ensembl and CBI-Gene, we have constructed secretomes of human, mouse and rat, with a total of 18 152 secreted proteins. All the entries are ranked according to the prediction...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2005
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540047/ https://www.ncbi.nlm.nih.gov/pubmed/15608170 http://dx.doi.org/10.1093/nar/gki093 |
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author | Chen, Yunjia Zhang, Yong Yin, Yanbin Gao, Ge Li, Songgang Jiang, Ying Gu, Xiaocheng Luo, Jingchu |
author_facet | Chen, Yunjia Zhang, Yong Yin, Yanbin Gao, Ge Li, Songgang Jiang, Ying Gu, Xiaocheng Luo, Jingchu |
author_sort | Chen, Yunjia |
collection | PubMed |
description | With the improved secreted protein prediction approach and comprehensive data sources, including Swiss-Prot, TrEMBL, RefSeq, Ensembl and CBI-Gene, we have constructed secretomes of human, mouse and rat, with a total of 18 152 secreted proteins. All the entries are ranked according to the prediction confidence. They were further annotated via a proteome annotation pipeline that we developed. We also set up a secreted protein classification pipeline and classified our predicted secreted proteins into different functional categories. To make the dataset more convincing and comprehensive, nine reference datasets are also integrated, such as the secreted proteins from the Gene Ontology Annotation (GOA) system at the European Bioinformatics Institute, and the vertebrate secreted proteins from Swiss-Prot. All these entries were grouped via a TribeMCL based clustering pipeline. We have constructed a web-based secreted protein database, which has been publicly available at http://spd.cbi.pku.edu.cn. Users can browse the database via a GO assignment or chromosomal-location-based interface. Moreover, text query and sequence similarity search are also provided, and the sequence and annotation data can be downloaded freely from the SPD website. |
format | Text |
id | pubmed-540047 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2005 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-5400472005-01-04 SPD—a web-based secreted protein database Chen, Yunjia Zhang, Yong Yin, Yanbin Gao, Ge Li, Songgang Jiang, Ying Gu, Xiaocheng Luo, Jingchu Nucleic Acids Res Articles With the improved secreted protein prediction approach and comprehensive data sources, including Swiss-Prot, TrEMBL, RefSeq, Ensembl and CBI-Gene, we have constructed secretomes of human, mouse and rat, with a total of 18 152 secreted proteins. All the entries are ranked according to the prediction confidence. They were further annotated via a proteome annotation pipeline that we developed. We also set up a secreted protein classification pipeline and classified our predicted secreted proteins into different functional categories. To make the dataset more convincing and comprehensive, nine reference datasets are also integrated, such as the secreted proteins from the Gene Ontology Annotation (GOA) system at the European Bioinformatics Institute, and the vertebrate secreted proteins from Swiss-Prot. All these entries were grouped via a TribeMCL based clustering pipeline. We have constructed a web-based secreted protein database, which has been publicly available at http://spd.cbi.pku.edu.cn. Users can browse the database via a GO assignment or chromosomal-location-based interface. Moreover, text query and sequence similarity search are also provided, and the sequence and annotation data can be downloaded freely from the SPD website. Oxford University Press 2005-01-01 2004-12-17 /pmc/articles/PMC540047/ /pubmed/15608170 http://dx.doi.org/10.1093/nar/gki093 Text en Copyright © 2005 Oxford University Press |
spellingShingle | Articles Chen, Yunjia Zhang, Yong Yin, Yanbin Gao, Ge Li, Songgang Jiang, Ying Gu, Xiaocheng Luo, Jingchu SPD—a web-based secreted protein database |
title | SPD—a web-based secreted protein database |
title_full | SPD—a web-based secreted protein database |
title_fullStr | SPD—a web-based secreted protein database |
title_full_unstemmed | SPD—a web-based secreted protein database |
title_short | SPD—a web-based secreted protein database |
title_sort | spd—a web-based secreted protein database |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC540047/ https://www.ncbi.nlm.nih.gov/pubmed/15608170 http://dx.doi.org/10.1093/nar/gki093 |
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