Figure 1

Feedback loop between experimental and computational stages of research and development. Applications of genomics and omics in industry originate from continuous collaborations between theoreticians, computational and experimental scientists in a feedback loop: Computational predictions provide ground for setting up new experiments and generate new data with new levels of complexity. These data are again analyzed by computational scientists to refine the predictions and to generate new hypotheses for further experimental validation. In absence of a priori biological hypotheses, exploratory learning approaches can be used to generate new hypotheses or to guide the parametrization choices for new statistical models.