The GenaGrid consortium won the grant of the National Office for Research and Technology (at National Technology Program) in November 2008. The title of the proposed 4 year long project was „Bioinformatic services for genetic association studies using high-performance grid computation” and has the identifier „GENAGRID”. The members of the consortium are:

  • Semmelweis University
  • Budapest University of Technology and Economics
  • MTA KFKI Research Institute for Particle and Nuclear Physics
  • Silicon Computers Ltd.
  • Csertex Ltd.

Abiomics Europe Ltd. is the company responsible for the utilization of the intellectual properties of the consortium and has exclusive rights to the developed technologies. Abiomics Europe drives the business development, market research and marketing activities for the consortium.

The GenaGrid research group operates a molecular biology lab and the most powerful grid supercomputer dedicated for life science research in Hungary with 512 CPUs (March 2010).

„To cope with the challenges in genetic research and particularly in genetic association studies (GAS), we have been developing GENAGRID, a high-performance grid; hosting databases, knowledge-bases, services, and methods for genomic R&D activities and applications. The goals of the project are grouped around the following topics:
The biomedical goals are the improvement of the design of genotyping experiments, the analysis of genotype data, the development of methods for integrative analysis of genetic variations, microRNA and gene expression data, and knowledge-rich, model-based interpretation of the results. The pharmacogenomic goal is the support of rational, knowledge based drug design, specifically target identification by probabilistic fusion of information from chemoinformatics to biomedicine including the results of GA research. The medical goals are support for clinical genetic consultancy based on commercially available genotypic information, which includes the automated information collection, manual curation, report generation, and the design of disease-specific and general genotyping kits with focus on the Hungarian/EEU/EU population. It also investigates the balanced and principled information dissemination related to commercially available personal genotypic information, particularly in case of asthma and allergy. The knowledge engineering and statistical goals are efficient inference in very-large scale probabilistic knowledge bases and decision networks, the development of robust statistical inference methods for association studies and for learning gene regulatory networks, and the development of methods for the fusion of the results of data analysis and factual prior knowledge. The goals related to high-performance computation are the investigation of the specializations of proprietary and external methods to a massively parallel grid environment and to Field-Programmable Gate Arrays (FPGAs), the efficient grid-enablement of GAS related databases and services, and the development of a service for new ones.”