Robert G. Endres

This study shows that Turing patterns are more likely to occur by chance in biological networks and identifies an optimal network size for robust Turing behavior.

The paper engineers a synthetic three-node Turing gene circuit in E. coli that generates periodic spatial patterns, validated by a differential equation model.

This study investigates how multistability, growth, and boundary conditions affect Turing pattern formation, showing that nonlinearities and realistic factors can lead to different pattern outcomes than classical theory predicts.