Abstract

Cancer is a highly complex aberrant cellular state where mutations impact a multitude of signalling pathways operating in different cell types. In recent years it has become apparent that in order to understand and fight cancer, it must be viewed as a system, rather than as a set of cellular activities. This mind shift calls for new techniques that will allow us to investigate cancer as a holistic system. In this talk, I will discuss some of the progress made towards achieving such a system-level understanding using computer modelling and formal verification. I will concentrate on our recent attempts to better understand cancer through the following four examples: 1) drug target optimization for Chronic Myeloid Leukaemia using an intuitive interface called BioModelAnalyzer, which allows to prove stabilization of biological systems; 2) dynamic hybrid model of brain tumour development using F#; 3) state-based models of cancer signalling crosstalk and their analysis using model-checking; and 4) synthesis of biological programs from mutation experiments. Looking forward, I will propose a grand challenge for computing and biology that could shed new light on our ability to control cell fates during development and disease and potentially change the way we treat cancer in the future.