Before revision:  With an ensemble approach of a minimal gene network for pancreas development , we show that Boolean networks with canalized / sign-compatible Boolean functionscan capture essential features of cell fate dynamics and allow the estimation of relative stabilities of network states and, hence, of transition barriers. Our Boolean network framework for calculating the relative stabilities and transition rates of network states can be used to quantify the influence of different geneson cell transitions, estimate the time sequence of cell differentiation and facilitate the rational design of cell reprogramming protocols.
After revision:  With an ensemble approach of a minimal gene network for pancreas development , we show that Boolean networks with canalized / sign-compatible Boolean functions best capture the dynamics of pancreas cell differentiation. This framework can also determine the genes' influence on cell state transitions, and thus can facilitate the rational design of cell reprogramming protocols.