Speaker: Theodore Perkins Modeling gap gene dynamics based on expression and transcription factor binding data The gap gene system of Drosophila melanogaster is a canonical example of a developmental gene network. We describe work on fitting differential equation models of gap gene expression dynamics, based on quantitative expression data and estimates of transcription factor binding affinities. We find that good estimates of qualitative regulatory relationships between genes can be obtained from purely wild-type expression data. Further, detailed dynamical features of gap expression can be explained in terms of transient or changing regulatory influences. Fitting the differential equations is a computationally challenging task; one of the contributions of this work is a new, fast fitting routine that combines traditional fitting approaches with ideas from (nonlinear) regression. Our more recent work focuses on relating expression dynamics to sequence and transcription factor binding data. We describe several methods for incorporating such data into dynamical models, and our findings on relationships between binding affinities and the regulatory weights in more phenomenological models.