Author

Ke Wu

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Open access Jul 2026

DiDyNet: a robust framework for differential dynamic network inference from longitudinal multi-omics data

DiDyNet, a framework for identifying phenotype-specific temporal molecular networks by defining dynamic coupling as coordinated molecular trajectories, was developed and significantly outperformed static summary statistics, including the mean, median, and difference.

Zhe Liu, Ke Wu, Taesung Park · Bioinformatics Advances · 0 citations