A statistical model for the dynamic regulation of alternative splicing in D. melanogaster

Miles Lopes, University of California, Berkeley

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A version of the Ising model is used to study time-varying interactions between RNA-binding proteins and cassette exons in the biological development of D. melanogaster. Interaction parameters are estimated from data via the Tesla procedure, which is closely related to l1-regularized logistic regression. Using an efficient convex optimization program based on forward-backward splitting, the inference procedure can be scaled to thousands of variables. Simulated data is used for benchmarking the procedure, and the estimated parameters are interpreted with clustered heatmaps.

Abstract Author(s): Miles Lopes