Jens Lagergren: On modeling disease progression

Modern experimental techniques are used to generate multiple types of information (genomics, transcriptomic, proteomic etc) for large collections of cancer tumors. This provides unprecedented opportunities to model cancer progression.
Despite the importance of this application, it has received very little attention compared to say evolutionary models.
I will briefly describe the data, discuss the modeling problem, and describe two types of graphical models of disease progression together with learning algorithms.