One of the promises of new methods of personalized medicine is that individual risks for diseases can be assessed using large DNA datasets. But many diseases are highly multifactorial, meaning that genetic risk factors are spread throughout the DNA. Finding these elusive connections and constructing a reliable and trackable statistical model from them is the goal of Matthew Robinson at the Institute of Science and Technology (IST) Austria and his international team.