Foundation for Research and Technology – Hellas (FORTH)

http://www.forth.gr http://www.ics.forth.gr

FORTH-ICS research activities include but are not limited to: hardware architectures, internet security and safety, high performance and wireless networking and mobile communication, knowledge representation and reasoning, database systems, user interfaces for interactive applications and services that are accessible, usable, and user friendly, computer vision, autonomous mobile robots with “intelligent” behaviour, biomedical informatics in the context of personalized, predictive and preventive medicine, biological and translational research via the application of computational methods and also advanced computational methods for performing research in biology.

The Bioinformatics and Computational Medicine Labs of FORTH-ICS focus its R&D activities towards the development of novel ICT technologies in the wider context of personalized, predictive and preventive medicine aiming at: the optimal management of chronic diseases and the development of clinical decision support systems; the optimization of diagnosis and treatment through the use of novel medical imaging analysis tools and predictive models; the integration of multi-level biomedical data for supporting postgenomic clinical trials; the integration of in vitro, in vivo and clinical data with mathematical and computational approaches to better understand cancer complexity and progression; the implementation of well-established in silico methods and tools towards novel approaches that could be incorporated in the medical clinical research; the understanding of spatio-temporal neuronal dynamics of the brain reflecting different perceptual, motor or cognitive states that may be indicative of a wider range of cognitive functions or brain pathologies; the semantic interoperability of biomedical data tools and models for enhancing biomedical knowledge discovery; the applications of the state-of-the-art and best-practices in computational methods on specific biological problems with the intent to discover new biomedical knowledge, and support Translation BioMedical methodologies.

The role of FORTH-ICS in RD-Connect will be the discovery of new associations between genotype, molecular and clinical phenotypes, towards the devise of complex clinico-genomic prediction models. In this direction relevant data-mining and machine-learning techniques and tools will be appropriately customized and tuned (e.g., R/Bioconductor packages, Weka etc.)