The continuous progress in understanding relevant genomic basics, e.g. for treatment of cancer patients, collides with the tremendous amount of data, that need to be processed. For example, the human genome consists of approx. 3.2 billion base pairs resp. 3.2 GB of data. Identifying a concrete sequence of 20 base pairs within the genome takes hours to days if performed manually. Processing and analyzing genomic data is a challenge for medical and biological research that delays progress of research projects. From a software engineering point of view, improving the analysis of genomic data is both a concrete research and engineering challenge. Combining knowledge of in-memory technology and of how to perform real-time analysis of huge amount of data with concrete research questions of medical and biological experts is the aim of the HIG project. The project was initiated in the spring 2012 in response to the overwhelming feedback about the first results of the HANA Oncolyzer project.

• Our latest research findings are published in the Springer book "High-Performance In-Memory Genome Data Analysis: How In-Memory Database Technology Accelerates Personalized Medicine".
• Hasso Plattner is invited to give a keynote lecture about "Gaining Time – Real-Time Analysis of Big Medical Data" at the World Health Summit 2013 from Oct. 20-22 in Berlin, Germany.
• We are invited to share our research results at at SAPPHIRE 2013, booth 2003 from May 14-16 in Orlando, Florida.
• Our latest research results were presented at Cebit 2013 from March 5th to March 9th in Hanover at the HPI booth.
• The HIG project was presented at the Personalized Medicine World Conference 2013 in Mountain View.
• Thanks to SAP, we are invited to SAPPHIRE to share our latest research results about the HIG project with an international audience. Find a related session in the session list.