Enabling data-intensive biomedical studies

The constantly increasing size and complexity of datasets involved in biomedical projects is deeply transforming approaches to their solution. Large scale studies require specifically designed computational frameworks that are capable of fulfilling many diverse requirements, the most important of which can be summarized in the fundamental properties of scalability, reproducibility and traceability. Although in recent years several new technologies have emerged that help deal with the issues raised by data-intensive research projects, applying them to the construction of a computational solution for the specific problem at hand is far from trivial, as no one-size-fits-all recipe exists for such a task. This work describes a methodology for approaching this new class of studies through several examples of solutions applied to concrete research problems.