DiDyNet: a robust framework for differential dynamic network inference from longitudinal multi-omics data
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Motivation: Understanding disease dynamics from longitudinal multi-omics is hindered by traditional approaches that focus on univariate trajectories and static networks while ignoring temporal evolution. We developed DiDyNet, a f... ...
