PEP-NET · Predictive Epigenetics: Fusing Theory and Experiment

Epigenetic mechanisms of gene regulation are profoundly implicated in human health and disease. However, we are still far from a complete mechanistic understanding of many epigenetic processes. Without an understanding of mechanisms we cannot fully understand function in healthy cells, in disease states, and the effects and side effects of therapeutic interventions. This severely limits the development of healthcare strategies. Research in epigenetics has typically been based on experiments and not on theory. Although this has delivered large amounts of information, information alone is not sufficient. Further progress urgently needs a paradigm shift in the way in which we study epigenetics, namely: epigenetics needs mathematics. Mathematical models are essential to capture and understand the complex, dynamic and stochastic nature of epigenetic regulation. Models are immensely powerful because they identify unifying concepts and enable predictions of system properties. Modelling epigenetic processes not only holds the key to a deep mechanistic understanding, but also ultimately, to drug response predictions, patient-specific diagnoses and new therapies. One of the greatest challenges to uniting biology and mathematics is the barrier between disciplines, because education in each field has traditionally been mono-disciplinary. The PEP-NET ITN will overcome these barriers by uniting 16 outstanding European academic laboratories and companies who have pioneered the successful combination of theoretical and experimental epigenetics. PEP-NET will train a new cohort of 15 European researchers to combine quantitative experiments with predictive theoretical models, and to apply this knowledge to basic and applied questions of epigenetic function.