Variable selection for disease progression models: Methods for oncogenetic trees and application to cancer and HIV

Disease progression models are important for understanding the critical steps during the development of diseases. The models are imbedded in a statistical framework to deal with random variations due to biology and the sampling process when observing only a finite population.