Nucleic Acids Research Advance Access originally published online on November 7, 2006
Nucleic Acids Research 2007 35(Database issue):D771-D779; doi:10.1093/nar/gkl784
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Nucleic Acids Research, 2007, Vol. 35, Database issue D771-D779
© 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.
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MAPU: Max-Planck Unified database of organellar, cellular, tissue and body fluid proteomes
niewski11 Department of Proteomics and Signal Transduction, Max-Planck-Institute of Biochemistry Am Klopferspitz 18, 82152 Martinsried, Germany 2 Beijing Institute of Genomics, Chinese Academy of Sciences Beijing 101300, China 3 Graduate School of Global Environmental Studi, Kyoto University Yoshida-Honmachi Sakyo-Ku, Kyoto 606-8501, Japan 4 Biomedical Primate Research Centre, Lange Kleiweg 139 2288 GJ Rijswijk, The Netherlands 5 Department of Biochemistry and Molecular Biology, Centre for Proteomics, University of British Columbia Vancouver, BC V6T 1Z4, USA 6 Department of Biochemistry and Molecular Biology, University of Southern Denmark DK-5230 Odense M, Denmark
*To whom correspondence should be addressed. Tel: +49 89 8578; Fax: +49 89 8578 2219; Email: mmann{at}biochem.mpg.de
Received August 15, 2006. Revised September 22, 2006. Accepted September 29, 2006.
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 http://www.mapuproteome.com 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.
The authors wish it to be known that, in their opinion, the first two authors should be regarded as joined first Authors
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