A machine learning approach for analyzing bistable systems in biology

Bistable systems arise frequently in the modelling of biological systems, particularly in systems biology. A famous example is the Collins toggle switch, a gene regulatory network with two genes that repress the expression of each other. Typically, the qualitative behaviour of these systems is examined using traditional techniques such as phase portraits and stability analysis. These approaches rely on the accuracy of the proposed model equations. Recently, machine learning has been used increasingly in the analysis of models stemming from applications in physics, but these methods have not yet been used widely for biological models. We develop a machine learning approach to analyze the behaviour of bistable systems in biology, particularly in cases where there may be information missing in the model equations and demonstrate its effectiveness in the case of the Collins toggle switch.