The complexity and scale of biological data are growing at an explosive rate. Currently, the main bottleneck towards new biological insights is often our ability to interpret existing data, rather than limitations in the availability of data. In recent years, the field of Machine Learning has provided a number of spectacular advances within various biological domains, and the community of researchers applying Machine Learning to address biological problems is rapidly growing. This conference is an attempt to highlight some of the important current developments on the interface between Machine Learning and biology - with particular focus on the area of bio-molecular structure and modelling.