Hardware for hUman Genomics (HUG) is a framework that exploits hardware accelerators (FPGAs) to speedup research in the field of personalized medicine. Its high level of abstraction allows researchers and doctors to exploit the potentiality of hardware accelerators to create drugs shaped on the DNA of the individual.
By Lorenzo Di Tucci
PhD student @Politecnico di Milano
In the coming years, human genome research will likely transform medical practices. The unique genetic profile of an individual and the knowledge of molecular basis of diseases are leading to the development of personalized medicines and therapies, but the exponential growth of available genomic data requires a computational effort that may limit the progress of personalized medicine. Within this context, HUG is a novel hardware and software integrated system developed at NECSTLab (Politecnico di Milano). The framework aims at becoming an advanced support for personalized medicine research. Thanks to more efficient algorithms and data integration from different biological sources, HUG aims at simplifying the interpretation of biological information and facilitating genomic research process by means of both computational and data visualization tools.
HUG is currently available as an easy to use web interface where users can easily create pipelines of algorithms to process biological data. Once the computation is over, the framework provides scientific visualizations so that researchers can focus more on interpreting the results rather than understanding how to process them.
Algorithms used for personalized medicine research are continuously changed as research goes on and the integration into existing systems is not an easy task. Furthermore, FPGAs can be very difficult to program, especially to people with a different background than Computer Science and Electrical engineering. Hence, it may not be trivial to integrate custom code into a hardware pipeline composed of such devices. In these regards, HUG ease the process of integrating custom code into existing pipelines offering fast prototyping tools that takes high level representation of the code (C/ C++) and automatically translate the code for the FPGA performing some base code optimizations.