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NetDS specifications


Unique identifier OMICS_12456
Name NetDS
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Computer skills Advanced
Version 3.0.1
Stability Stable
Maintained Yes




No version available


  • person_outline Kwon Y.K.

Publication for NetDS

NetDS citations


Unraveling a tumor type specific regulatory core underlying E2F1 mediated epithelial mesenchymal transition to predict receptor protein signatures

Nat Commun
PMCID: 5543083
PMID: 28775339
DOI: 10.1038/s41467-017-00268-2

[…] overall organization of the network (Supplementary Table ; Supplementary Fig. ). (ii) Network motif identification: Feedback loops from the E2F1 interaction map were identified using Cytoscape plugin NetDS (v3.0). For the identification of feedback loops, we set the loop length to three nodes (see “Discussion” section for detail). (iii) Motif ranking: To identify the most important motifs with res […]


Identification of miRNA mRNA Modules in Colorectal Cancer Using Rough Hypercuboid Based Supervised Clustering

Sci Rep
PMCID: 5318911
PMID: 28220871
DOI: 10.1038/srep42809

[…] sents the extended network.The final version of the network was further analyzed to identify regulatory motifs like feedback (FBLs) and feedforward loops (FFLs), with the help of the Cytoscape plugin NetDS. The transcription factors and miRNAs are responsible for the combinatorial regulation of gene expression at transcription level and post-transcription level, respectively. The network shown in […]


Analysis of microRNA and Gene Expression Profiles in Multiple Sclerosis: Integrating Interaction Data to Uncover Regulatory Mechanisms

Sci Rep
PMCID: 5046091
PMID: 27694855
DOI: 10.1038/srep34512

[…] eir targets, unless otherwise indicated in TransmiR. The gene-based network was created in a similar fashion. The networks were constructed and visualized using Cytoscape (version 3.2.0). We employed NetDS, a plugin for Cytoscape, to uncover FFLs and FBLs that contribute to the complexity of the regulatory networks in MS. The Cytoscape session files are available from the corresponding authors upo […]


PANET: A GPU Based Tool for Fast Parallel Analysis of Robustness Dynamics and Feed Forward/Feedback Loop Structures in Large Scale Biological Networks

PLoS One
PMCID: 4109960
PMID: 25058310
DOI: 10.1371/journal.pone.0103010

[…] he robustness , and the coherent FFLs can be considered as a design principle of human signaling networks that improve network robustness against update-rule perturbations .Inspired by those studies, NetDS, a Cytoscape plugin, was recently developed to analyze the robustness-related dynamics and FFL/FBL structures of networks . However, there were some significant limitations with regard to fully […]


A Systems' Biology Approach to Study MicroRNA Mediated Gene Regulatory Networks

Biomed Res Int
PMCID: 3848080
PMID: 24350286
DOI: 10.1155/2013/703849

[…] of a gene regulatory network. The final version of the network can be further analyzed to identify regulatory motifs like feedforward loops (FFLs), for example, with the help of the Cytoscape plugin NetDS []. Thereafter, the complete network or parts of it can be converted into a detailed mechanistic model which is described in detail in the following section. (3)  Model Construction and Calibra […]


RMOD: A Tool for Regulatory Motif Detection in Signaling Network

PLoS One
PMCID: 3710000
PMID: 23874612
DOI: 10.1371/journal.pone.0068407

[…] toKavosh detect motifs that recur in the network much more often than expected in a random network; NetMatch searches only for network motifs that match a user-defined query graph. In addition, the NetDS , a Cytoscape plugin, was recently developed to analyze a limited size of feedback and feedforward loops. However, it is difficult to identify regulatory motifs in the signaling networks using t […]


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NetDS institution(s)
School of Electrical Engineering, University of Ulsan, Daehak-ro, Nam-gu, Ulsan, Japan
NetDS funding source(s)
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (2010-0010533).

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