The Rubin lab develops computational methods to investigate the sources of genetic variability among individuals. Their approach is unique in considering humans both as a target organism (i.e. working on health-related issues) and as a model organism. Specifically, the group explores complex patterns involving either genetic markers alone or in combination with other markers that predict the outcome of cancer. Such an approach allow asking the following questions in the field of personalized medicine: what makes some patients respond better than others to certain types of treatment? Can we use such understanding to predict which drug is the most beneficial for certain individuals? Which patients are at greater risk to develop rapid disease progression, and in which patients the disease will be eliminated or remain stable? The group has developed expertise in human genome analysis, as well as a unique set of tools for mining genetic and genomic information using machine learning techniques.