SP 2

Real-Time Analysis of Genome Data using In-Memory Database Technology

The SMART consortium addresses the acquisition and assessment of risk factors, which might lead to irreversible cardiac failure, in a holistic way. Amongst other, it covers the integration of mathematical models, which incorporate the importance of genetic dispositions and markers. Results of all involved SMART partners can only be used as additional input for decision taking by clinicians once they are combined in a single application, which allows doctors the interactive exploration of the result.
The given project addresses the combination and integration of relevant data into a holistic IT-aided data processing and analysis software system. This includes newest technologies, such as web and in-memory database technology, enabling combination and exploration of selected data in real time. All project partners will have a unified access to results via a scalable cloud platform enabling the linking of data and the real-time analysis of results in a convenient way without involving a database or IT expert. It includes the processing and analysis of genetic data, which are combined with results driven from the mathematical models and linked to existing international knowledge bases.
In the course of the project, we model specific analysis pipelines, which can keep pace with the steadily increasing amount of generated medical data. These analysis pipelines allow automatic processing and the interactive assessment of acquired medical data in a productive environment dealing with a high number of patient cases daily. For the first time, clinical experts are able to classify each patient based on her/his characteristics and to derive required individual therapeutics using a broad spectrum of additional diagnostic data. Our incorporated in‐memory database technology builds the foundation for integration of heterogeneous data formats, for linking data with relevant sources, and for  analyzing the data in an interactive way without involving additional IT personnel.

Keywords: In Memory Technology, Real-time Data Analytics, Genome Data, Cloud Platform