@inproceedings{e7d86a6969df435d9697788fdc3b107d,
title = "Hosting of ProteomicsDB at the HPI",
abstract = "ProteomicsDB1 is a protein-centric in-memory database for the exploration of large collections of quantitative mass spectrometry-based proteomics data. To date, it contains quantitative data from over 19k LC-MS/MS experiments covering more than 200 tissues, body fluids and cell lines. We extended the data model to enable the storage and integrated visualization of other quantitative omics data. This includes transcriptomics data from e. g. NCBI GEO, protein-protein interaction information from STRING, functional annotations from KEGG, drug-sensitivity/selectivity data from several public sources and reference mass spectra from the ProteomeTools project. The extended functionality transforms ProteomicsDB into a multipurpose resource connecting quantification and meta-data for each protein. The rich user interface helps researchers to navigate all data sources in either a protein-centric or multi-protein-centric manner.",
author = "Mathias Wilhelm and Bernhard Kuster",
note = "Publisher Copyright: {\textcopyright} 2019 Universitatsverlag Potsdam. All rights reserved.; HPI Future SOC Lab 2017 ; Conference date: 15-11-2017",
year = "2019",
language = "English",
series = "Technische Berichte des Hasso-Plattner-Instituts fur Softwaresystemtechnik an der Universitat Potsdam",
publisher = "Universitatsverlag Potsdam",
pages = "223--229",
editor = "Christoph Meinel and Andreas Polze and Karsten Beins and Rolf Strotmann and Ulrich Seibold and Kurt Rodszus and Jurgen Muller",
booktitle = "HPI Future SOC Lab - Proceedings 2017",
}