Uncovering Biological Computation in Embryonic Stem Cells
Biological computation is the molecular Information-processing that underlies cellular decision-making. Understanding the mechanisms that govern such computation is crucial to understand how biological function is controlled and executed. In this talk, I will discuss these concepts in the context of stem cell decision-making, specifically to investigate the mechanisms that underlie embryonic stem cell pluripotency, as well as how to reset the naïve pluripotent state. The approach we have developed is applied here to transcriptional regulation, and implements logical modelling as an abstraction of transcriptional interaction networks. We apply methods from formal reasoning to enable the automatic synthesis and analysis of the complete set of logical models that are consistent with experimentally-observed behaviour. Furthermore, we utilize exhaustive decision procedures to extract evidence from all possible model trajectories to either support or refute different hypotheses, and so to generate predictions of cell behaviour in untested conditions. Subsequent experimental tests reveal that the set of models we derive are highly predictive. Our methodology transforms knowledge and data of complex biological processes from networks of possible interactions to precise, predictive biological programs governing cell function.