| Literature DB >> 24870543 |
Mathias Wilhelm1, Judith Schlegl2, Hannes Hahne3, Amin Moghaddas Gholami3, Marcus Lieberenz4, Mikhail M Savitski5, Emanuel Ziegler4, Lars Butzmann4, Siegfried Gessulat4, Harald Marx6, Toby Mathieson5, Simone Lemeer6, Karsten Schnatbaum7, Ulf Reimer7, Holger Wenschuh7, Martin Mollenhauer8, Julia Slotta-Huspenina8, Joos-Hendrik Boese4, Marcus Bantscheff5, Anja Gerstmair4, Franz Faerber4, Bernhard Kuster9.
Abstract
Proteomes are characterized by large protein-abundance differences, cell-type- and time-dependent expression patterns and post-translational modifications, all of which carry biological information that is not accessible by genomics or transcriptomics. Here we present a mass-spectrometry-based draft of the human proteome and a public, high-performance, in-memory database for real-time analysis of terabytes of big data, called ProteomicsDB. The information assembled from human tissues, cell lines and body fluids enabled estimation of the size of the protein-coding genome, and identified organ-specific proteins and a large number of translated lincRNAs (long intergenic non-coding RNAs). Analysis of messenger RNA and protein-expression profiles of human tissues revealed conserved control of protein abundance, and integration of drug-sensitivity data enabled the identification of proteins predicting resistance or sensitivity. The proteome profiles also hold considerable promise for analysing the composition and stoichiometry of protein complexes. ProteomicsDB thus enables navigation of proteomes, provides biological insight and fosters the development of proteomic technology.Entities:
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Year: 2014 PMID: 24870543 DOI: 10.1038/nature13319
Source DB: PubMed Journal: Nature ISSN: 0028-0836 Impact factor: 49.962