MAPU
NAR Molecular Biology Database Collection entry number 950
Gnad, F.1, Oroshi, M.1, Birney, E.2, Mann, M.1
1Department of Proteomics and Signal Transduction, Max-Planck Institute for Biochemistry, Am Klopferspitz 18, D-82152 Martinsried, Germany.
2European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
2European Bioinformatics Institute (EMBL-EBI), Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK.
Contact mmann@biochem.mpg.de
Database 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. By employing high resolution MS and stringent validation criteria, false positive identification rates in MAPU are lower than 1:100 and usually better than 1:1000. Thus MAPU data sets can serve as reference proteomes in biomarker discovery. Proteome data can be queried by protein name, accession number, peptide sequence and annotation information.
Recent Developments
The new release addresses MS-specific problems including ambiguous peptide-to-protein assignments and it provides insight into general functional features on the protein level ranging from gene ontology classification to comprehensive SwissProt annotation. Moreover, the derived proteomic data are linked to the genomes using the Distributed Annotation Service (DAS) via Ensembl services. MAPU 2.0 is a model for a database specifically designed for high accuracy proteomics and a member of the ProteomExchange Consortium.
Acknowledgements
We thank the database group at the Beijing Genome Institute for help, discussion and providing database templates.
Category: Proteomics Resources
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