Projects
CompBioMed2 is a proposal for the second phase of the Computational Biomedicine Centre of Excellence (CoE), CompBioMed, an outward facing CoE comprising members from academia, industry and the healthcare sector. CompBioMed has established itself as a hub for practitioners in the field, successfully nucleating a substantial body of research, education, training, innovation and...
Abstract in Spanish:
El proyecto PIXIL es un esfuerzo de colaboración científico-tecnológica transfronterizo y multidisciplinar, con el objetivo de desarrollar las herramientas más punteras para analizar el subsuelo terrestre, con especial interés en favorecer el crecimiento de la energía...
High performance computing (HPC) has transformed scientific research across numerous disciplines by supportingtheory and experiments with numerical simulations. Exascale computing is the next milestone in HPC and is called to play an important role in economic competitiveness, societal challenges and science leadership. Combustion isone of the fields with high strategic...
This project is going to apply exascale HPC techniques to different energy industry simulations of critical interest for Mexico. ENERXICO will give solutions for oil & gas industry in upstream, midstream and downstream problems, wind energy industryand combustion efficiency for transportation. This project brings together the main stakeholders of the energy industry...
PRACE, the Partnership for Advanced Computing is the permanent pan-European High Performance Computing service providing world-class systems for world-class science. Systems at the highest performance level (Tier-0) are deployed by Germany, France, Italy, Spain and Switzerland, providing researchers with more than 17 billion core hours of compute time. HPC experts from 25...
In the previous project, EPIC, we developed a consistent methodological framework for the exploration of disease comorbidity at the molecular level. EPIC provides a first overview of disease interactions from the general level to the one of individual patients. Particularly interesting is the network of patient-subgroups that matches, in a statistically significant manner,...
Effective personalized medicine for paediatric cancers must address a multitude of challenges, including domain-specific challenges. To overcome these challenges, we propose a comprehensive computational effort to combine knowledge-base, machine-learning, and mechanistic models to predict optimal standard and experimental therapies for each child. Our approach is based on...
Health scientific discovery and innovation are expected to quickly move forward under the so called fourth paradigm ofscience , which relies on unifying the traditionally separated and heterogeneous high-performance computing and big dataanalytics environments. Under this paradigm, the DeepHealth project will provide HPC computing power at the service of biomedical...
At an increasing rate, industrial and scientific institutions need to deal with massive data flows streaming in from a multitude of sources. For instance, maritime surveillance applications combine high-velocity data streams, including vessel position signals emitted from hundreds of thousands of vessels across the world and acoustic signals of autonomous, unmanned vessels;...
CYBELE generates innovation and create value in the domain of agri-food, and its verticals in the sub-domains of PA andPLF in specific, as demonstrated by the real-life industrial cases to be supported, empowering capacity building within theindustrial and research community. Since agriculture is a high volume business with low operational efficiency, CYBELE aspires at...