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MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes
Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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Oxford University Press
2007
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1781136/ https://www.ncbi.nlm.nih.gov/pubmed/17090601 http://dx.doi.org/10.1093/nar/gkl784 |
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author | Zhang, Yanling Zhang, Yong Adachi, Jun Olsen, Jesper V. Shi, Rong de Souza, Gustavo Pasini, Erica Foster, Leonard J. Macek, Boris Zougman, Alexandre Kumar, Chanchal Wiśniewski, Jacek R. Jun, Wang Mann, Matthias |
author_facet | Zhang, Yanling Zhang, Yong Adachi, Jun Olsen, Jesper V. Shi, Rong de Souza, Gustavo Pasini, Erica Foster, Leonard J. Macek, Boris Zougman, Alexandre Kumar, Chanchal Wiśniewski, Jacek R. Jun, Wang Mann, Matthias |
author_sort | Zhang, Yanling |
collection | PubMed |
description | Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. |
format | Text |
id | pubmed-1781136 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2007 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-17811362007-02-22 MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes Zhang, Yanling Zhang, Yong Adachi, Jun Olsen, Jesper V. Shi, Rong de Souza, Gustavo Pasini, Erica Foster, Leonard J. Macek, Boris Zougman, Alexandre Kumar, Chanchal Wiśniewski, Jacek R. Jun, Wang Mann, Matthias Nucleic Acids Res Articles Mass spectrometry (MS)-based proteomics has become a powerful technology to map the protein composition of organelles, cell types and tissues. In our department, a large-scale effort to map these proteomes is complemented by the Max-Planck Unified (MAPU) proteome database. MAPU contains several body fluid proteomes; including plasma, urine, and cerebrospinal fluid. Cell lines have been mapped to a depth of several thousand proteins and the red blood cell proteome has also been analyzed in depth. The liver proteome is represented with 3200 proteins. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:1000. Thus MAPU datasets can serve as reference proteomes in biomarker discovery. MAPU contains the peptides identifying each protein, measured masses, scores and intensities and is freely available at using a clickable interface of cell or body parts. Proteome data can be queried across proteomes by protein name, accession number, sequence similarity, peptide sequence and annotation information. More than 4500 mouse and 2500 human proteins have already been identified in at least one proteome. Basic annotation information and links to other public databases are provided in MAPU and we plan to add further analysis tools. Oxford University Press 2007-01 2006-11-07 /pmc/articles/PMC1781136/ /pubmed/17090601 http://dx.doi.org/10.1093/nar/gkl784 Text en © 2006 The Author(s) This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Articles Zhang, Yanling Zhang, Yong Adachi, Jun Olsen, Jesper V. Shi, Rong de Souza, Gustavo Pasini, Erica Foster, Leonard J. Macek, Boris Zougman, Alexandre Kumar, Chanchal Wiśniewski, Jacek R. Jun, Wang Mann, Matthias MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title | MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title_full | MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title_fullStr | MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title_full_unstemmed | MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title_short | MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes |
title_sort | mapu: max-planck unified database of organellar, cellular, tissue and body fluid proteomes |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1781136/ https://www.ncbi.nlm.nih.gov/pubmed/17090601 http://dx.doi.org/10.1093/nar/gkl784 |
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