I will review the use of a class of continuous-time models of transcriptional regulation. This consist of a system of (ordinary or stochastic) differential equations whose coefficients depend on a latent, discrete state Markov Jump process. The interpretation we will propose is that the DEs describe the dynamics of expression of a set of genes, while the latent processes describe activation states of transcription factor proteins. I will describe the approach to inference, and present results on a number of real data sets.
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