A deterministic method for estimating free energy genetic network landscapes with applications to cell commitment and reprogramming paths
Depicting developmental processes as movements in free energy genetic landscapes is an illustrative tool. However, exploring such landscapes to obtain quantitative or even qualitative predictions is hampered by the lack of free energy functions corresponding to the biochemical Michaelis– Menten or Hill rate equations for the dynamics. Being armed with energy landscapes defined by a network and its