Tree evolving networks.
Learn network by choosing one gene as Y and others as betas, then lasso to find betas predictive of Y.
Extends this by adding a second penalty which reduces the variation in the betas in two regressions, where the second regression is fit to a daughter node of the first experiment.
I.e. same cell before, during, and after treatment.
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