SAP and Technical University Munich Decode Human Proteome and Make Data Available for Biomedical Research
SAP and the Technical University of Munich (TUM) Decode and Analyze Human Proteome in ProteomicsDB With the Help of SAP HANA
WALLDORF, Germany - SAP AG (NYSE: SAP) and Technical University Munich (TUM) today announced ProteomicsDB, a new offering based on the SAP HANA platform that stores protein and peptide identifications from mass spectrometry-based experiments. The proteomic data assembled in the new offering resulted in the identification of proteins mapping to over 18,000 human genes. This represents 90 percent coverage of the human proteome. Data stored and analyzed within ProteomicsDB can be used in basic and biomedical research for discovering therapeutic targets and developing new drugs as well as enhanced diagnosis methods.
As personalized medicine is on the rise, the healthcare field is discovering the opportunities of big data analysis. The result of a joint project between the TUM Chair of Proteomics and Bioanalytics, SAP and the SAP Innovation Center, ProteomicsDB is a major step forward in human proteomics. It currently contains more than 11,000 datasets from human cancer cell lines, tissues and body fluids and enables real-time analysis of this highly dimensional data and creates instant value by allowing to test analytical hypothesis.
ProteomicsDB will be available free of charge. The database will be a valuable asset for researchers in the field of life sciences as well as for the pharmaceutical and biotechnology industry. Insights from analyzing the inherent datasets can be used in biomedical research and for example in developing new drugs that operate in a more targeted way without adversely influencing other cellular processes, helping to reduce side effects.
“The vast amounts of molecular data generated in biomedical research increasingly challenge the ability of scientists to see ‘the forest for the trees,” said Prof. Dr. Bernhard Kuster of TUM. “ProteomicsDB is a significant step ahead in our research aiming at a better understanding of human disease and more informed future treatments. The software helps us and others to store, integrate and analyze experimental data in real time, allowing us to study more complex biological systems at greater depth than previously possible.”
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Technische Universität München (TUM) is one of Europe’s leading universities. It has roughly 500 professors, 9,000 academic and non-academic staff, and 32,000 students. It focuses on the engineering sciences, natural sciences, life sciences, medicine, and economic sciences. After winning numerous awards, it was selected as an “Excellence University” in 2006 and 2012 by the Science Council (Wissenschaftsrat) and the German Research Foundation (DFG). In both international and national rankings, TUM is rated as one of Germany’s top universities and is dedicated to the ideal of a top-level research-oriented entrepreneurial university. The university's global presence includes offices in Beijing (China), Brussels (Belgium), Cairo (Egypt), Mumbai (India) and São Paulo (Brazil). The German Institute of Science and Technology (GIST - TUM Asia), founded in 2002 in Singapore, is the first research campus of a German university abroad. www.tum.de
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