Highlights d Extended cellular Potts model captures pluripotent stem cell organization dynamics d Machine learning optimization yields conditions for multicellular patterns d In silico predicted experimental parameters generate desired patterns in vitro

No abstract

No abstract

Multi-cellular organisms originate from a single cell, ultimately giving rise to mature organisms of 1 heterogeneous cell type composition in complex structures. Recent work in the areas of stem cell 2 biology and tissue engineering have laid major groundwork in the ability to convert certain types of 3 cells into other types, but there has been limited progress in the ability to control the morphology of 4 cellular masses as they grow. Contemporary approaches to this problem have included the use of 5 artificial scaffolds, 3D bioprinting, and complex media formulations, however, there are no existing 6 approaches to controlling this process purely through genetics and from a single-cell starting point. 7Here we describe a computer-aided design approach for designing recombinase-based genetic circuits 8 for controlling the formation of multi-cellular masses into arbitrary shapes in human cells. 9

No abstract