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Key Collaboration Initiated for Optimization of Bioinformatics Computing Performance

By LabMedica International staff writers
Posted on 03 Apr 2013
A new consortium has been formed for research and development of IT solutions to optimize computing for the analysis and management of macro-datasets generated from genomics research, as well as to facilitate clinical applications based on these datasets.

The huge sets of data produced in genomics studies, typically with Next Generation Sequencing technology, are processed by high performance computers and office workstations, and more recently by mobile devices like tablets and smartphones. More...
The sequence of only a single human genome, for example, requires about 3 gigabytes of storage. New methods are required to process these data quickly and efficiently and to better enable their subsequent application.

Integromics (Granada, Spain) has announced that it will invest in the optimization of computing performance for bioinformatics applications, with a special focus on clinical applications, by participating in a European project named “Mr. SymBioMath” that includes renowned high performance computing (HPC) experts. The project, funded with more than EUR 2.6 million by the Seventh Framework Program for R & D of the European Union and coordinated by the Laboratory of Bioinformatics and Information Technology of the University of Malaga-UMA (Spain), has been designed to provide solutions to these needs through synergy between Integromics (Spain), the Leibniz Supercomputing Centre in Munich-LRZ (Germany), the Johannes Kepler University of Linz-JKU (Austria), RISC Software (Austria), and Carlos Haya Hospital (Spain).


The Mr. SymBioMath project is to result in new software applications and data analysis methods to accelerate genomics adoption in the clinical domain. At the level of computation, the research will be focused on two major challenges: transmission of large volumes of data and optimization of genetic comparison models and visualizations. JKU will be responsible for creating new models for comparative genomics, evolutionary distances between different organisms, and identification of correlations between genetic variation and phenotypic response of patients to particular treatments. The supercomputing infrastructure will be provided by the UMA and RISC. They will also develop applications to deliver, collect, and display test information. LRZ will focus on the provisioning of enhanced visualization and Virtual Reality hardware and software for the analysis of the interconnected huge genomic datasets in this project.

The final implementation into commercial software will be done by Integromics. “Integromics will contribute from a commercial perspective in the design of applications compatible with both computer and tablets-smartphones,” said Juan Elvira, CTO of Integromics. At the clinical level, Miguel Blanco, Chief of Allergy Carlos Haya Hospital, explained that the project will use data available in the National Allergy Network to validate the software solutions; e.g., for early detection of drug reactions and allergies. The project leader, Dr. Oswaldo Trelles, highlighted that one of the strengths of this study is its focus on medical practice. “The solutions we seek,” said Dr. Trelles “are targeted to a wide range of scientific applications, with personalized medicine certainly being one of them. Indeed, one of the objectives is to implement applications prototypes applied in real-use case scenarios and to evaluate their potential for detecting from genomic data of allergic patients the possible adverse reactions to treatment.”

The Mr. SymBioMath project represents an ideal opportunity for Integromics to reinforce its commitment to the development of software solutions for personalized medicine applied to the clinics. “This grant and collaboration with renowned computing experts will contribute to the democratization of genomics, in particular through the usage of mobile devices,” said Eduardo González Couto, CSO of Integromics.

Related Links:
Mr. SymBioMath Project
Integromics



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