Spring 2016

Modelling Gene Expression Dynamics with Gaussian Processes

Thursday, Mar. 10, 2016 11:30 am12:00 pm PST

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Calvin Lab

Gaussian processes provide a convenient and flexible class of non-parametric model for temporal and spatial data. We are applying Gaussian processes in a range of biological applications involving high-throughput time course data, e.g. modeling the elongation dynamics of polymerase, uncovering mRNA production delays, inferring regulatory networks and most recently identifying perturbations and bifurcations from high-throughput expression data. I will provide an overview of Gaussian process inference and describe some of our recent work in modeling gene expression dynamics.