With beginning of February 2013 the EU funded project High Performance, Cloud and Symbolic Computing in Big-Data Problems applied to Mathematical Modeling of Comperative Genomics (Mr. SymBioMath) has started. It runs over 36 months till January 2016 and is funded within the Maria-Curie programme of the EU 7th framework programme as an Industry-Academia Partnerships (IAPP) project under grant agreement number 324554.

The project will mainly target the appplication area of comparative genomics while building on top of cloud and high-performance computing. The international project consortium an international project consortium consists of the University of Malaga (Spain), RISC Software GmbH (Austria), the Johannes Kepler University Linz (Austria), Integromics (Spain), the Servicio Andaluz de Salud (Spain), and the Leibniz Supercomputing Center (Germany). The project is specifically supporting the cooperation between industry and academia through the exchange of personell.

Based on its interdisciplinary approach the project interconnects the application domain of life sciences with technologies from bioinformatics as well as Cloud Computing and High Performance Computing, which is required for processing the large amounts of data, which are generated by modern genome sequencing technology. The size of this datasets also poses the main motivation for newly developing applications from the domain of comparative genomics, since the currently available versions are not prepared to handle full genomes.

Core points to be addressed within the project are comparisons and visualizations of sizeable genome sequences up to complete genomes as well as phylogenetic trees. An additional goal is given by the user-friendly presentation of the result data based on visualization techniques for different types of output devices ranging from tablet PCs to Virtual Reality Environments.

Within the project multiple interconnected software compontents will be developed including support layers for cloud computing and high performance computing, as well as modules for data access and visualization on different types of output devices. These modules can be interconnected to form complex workflows for processing genomic data.