KDDN is a systems biology method and tool to leverage existing domain knowledge and specific experimental data to model biological networks. It integratively characterizes the dynamic nature of biological systems by jointly modeling the network structure under different experimental conditions and guide the learning by existing domain knowledge.
People doing bioinformatics, computational biology and even beyond with some dynamic profiling data want to explore. KDDN provides a network perspective of the data to show how the interactions among the variables form and change.
Developed as a Cytoscape app, KDDN can be conveniently used from within Cytoscape. Straightforward interface and help documents guide users to configure, run and evaluate experiments.
Details regarding the methodology can be found at
Y. Tian, B. Zhang, E.P. Hoffman, R. Clarke, Z. Zhang, I.M. Shih, J. Xuan, D.M. Herrington and Y. Wang, “Knowledge-fused differential dependency network models for detecting significant rewiring in biological networks”, BMC Systems Biology, 8:87, 2014.