In which Dana speaks with Vaibhav and Jason about the principles of single cell analysis and informatics challenges associated with it. Among other things, they discuss manifolds and data topology, Bayesian approaches and considerations in prior distribution selection in biology, matrix factorization and imputing missing cell states with graphical walks through phenotypic space, and the utility of diffusion components when  Principal Component Analysis is insufficient. Dana concludes with some advice for young people interested in Systems and Computational Biology.