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KDDN specifications


Unique identifier OMICS_08329
Alternative name Knowledge-fused Differential Dependency Network
Software type Package/Module
Interface Graphical user interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Medium
Version 1.1.0
Stability Stable
Maintained Yes


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  • person_outline Yue Wang <>

Publication for Knowledge-fused Differential Dependency Network

KDDN in publications

PMCID: 5506248
PMID: 28713572
DOI: 10.1038/hortres.2017.32

[…] topology in the mutant and wild-type background, network-based analysis was carried out using the differential dependency network (ddn) algorithm as implemented in its cytoscape-based version, knowledge-fused differential dependency network (kddn), where the predicted cis-regulatory connections among the degs determined from plant regmap, was used as a priori information. cytoscape […]

PMCID: 5494892
PMID: 28673325
DOI: 10.1186/s13058-017-0866-x

[…] genes in f3 hf offspring, but only downregulated genes in f1 hf offspring. ingenuity pathway analysis identified upregulation of notch signaling as a key alteration in hf offspring. further, knowledge-fused differential dependency network analysis identified ten node genes that in the hf offspring were uniquely connected to genes linked to increased cancer risk (ankef1, igfbp6, sema5b), […]

PMCID: 5303311
PMID: 28187708
DOI: 10.1186/s12859-017-1515-1

[…] expression analysis [–]. for example, high-degree nodes (i.e., hubs) that only exist in one of the biologically disparate groups may indicate the regulatory rule of the hub genes only in that group. knowledge-fused differential dependency network (kddn) is a recently proposed method to construct knowledge incorporated network that can show the rewiring connections between two groups []. […]

PMCID: 4131167
PMID: 25055984
DOI: 10.1186/s12918-014-0087-1

[…] r software package and the experimental data are freely available at http://www.cbil.ece.vt.edu/software.htm., experiments on both synthetic and real data demonstrate the effectiveness of the knowledge-fused differential dependency network in revealing the statistically significant rewiring in biological networks. the method efficiently leverages data-driven evidence and existing […]

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KDDN institution(s)
Department of Electrical & Computer Engineering, Virginia Tech, Arlington, VA, USA
KDDN funding source(s)
National Institutes of Health, under Grants [CA160036, CA164384, NS29525, CA149147, HL111362]

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