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PCAS – a precomputed proteome annotation database resource
BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification o...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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BioMed Central
2003
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC293463/ https://www.ncbi.nlm.nih.gov/pubmed/14594458 http://dx.doi.org/10.1186/1471-2164-4-42 |
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author | Zhang, Yong Yin, Yanbin Chen, Yunjia Gao, Ge Yu, Peng Luo, Jingchu Jiang, Ying |
author_facet | Zhang, Yong Yin, Yanbin Chen, Yunjia Gao, Ge Yu, Peng Luo, Jingchu Jiang, Ying |
author_sort | Zhang, Yong |
collection | PubMed |
description | BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome. PCAS is available at CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified. |
format | Text |
id | pubmed-293463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2003 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-2934632003-12-16 PCAS – a precomputed proteome annotation database resource Zhang, Yong Yin, Yanbin Chen, Yunjia Gao, Ge Yu, Peng Luo, Jingchu Jiang, Ying BMC Genomics Database BACKGROUND: Many model proteomes or "complete" sets of proteins of given organisms are now publicly available. Much effort has been invested in computational annotation of those "draft" proteomes. Motif or domain based algorithms play a pivotal role in functional classification of proteins. Employing most available computational algorithms, mainly motif or domain recognition algorithms, we set up to develop an online proteome annotation system with integrated proteome annotation data to complement existing resources. RESULTS: We report here the development of PCAS (ProteinCentric Annotation System) as an online resource of pre-computed proteome annotation data. We applied most available motif or domain databases and their analysis methods, including hmmpfam search of HMMs in Pfam, SMART and TIGRFAM, RPS-PSIBLAST search of PSSMs in CDD, pfscan of PROSITE patterns and profiles, as well as PSI-BLAST search of SUPERFAMILY PSSMs. In addition, signal peptide and TM are predicted using SignalP and TMHMM respectively. We mapped SUPERFAMILY and COGs to InterPro, so the motif or domain databases are integrated through InterPro. PCAS displays table summaries of pre-computed data and a graphical presentation of motifs or domains relative to the protein. As of now, PCAS contains human IPI, mouse IPI, and rat IPI, A. thaliana, C. elegans, D. melanogaster, S. cerevisiae, and S. pombe proteome. PCAS is available at CONCLUSION: PCAS gives better annotation coverage for model proteomes by employing a wider collection of available algorithms. Besides presenting the most confident annotation data, PCAS also allows customized query so users can inspect statistically less significant boundary information as well. Therefore, besides providing general annotation information, PCAS could be used as a discovery platform. We plan to update PCAS twice a year. We will upgrade PCAS when new proteome annotation algorithms identified. BioMed Central 2003-11-01 /pmc/articles/PMC293463/ /pubmed/14594458 http://dx.doi.org/10.1186/1471-2164-4-42 Text en Copyright © 2003 Zhang et al; licensee BioMed Central Ltd. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose, provided this notice is preserved along with the article's original URL. |
spellingShingle | Database Zhang, Yong Yin, Yanbin Chen, Yunjia Gao, Ge Yu, Peng Luo, Jingchu Jiang, Ying PCAS – a precomputed proteome annotation database resource |
title | PCAS – a precomputed proteome annotation database resource |
title_full | PCAS – a precomputed proteome annotation database resource |
title_fullStr | PCAS – a precomputed proteome annotation database resource |
title_full_unstemmed | PCAS – a precomputed proteome annotation database resource |
title_short | PCAS – a precomputed proteome annotation database resource |
title_sort | pcas – a precomputed proteome annotation database resource |
topic | Database |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC293463/ https://www.ncbi.nlm.nih.gov/pubmed/14594458 http://dx.doi.org/10.1186/1471-2164-4-42 |
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