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Related Experiment Video

Updated: Mar 7, 2026

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Using SCOPE to Identify Potential Regulatory Motifs in Coregulated Genes

Published on: May 31, 2011

MotifNet: a web-server for network motif analysis.

Ilan Y Smoly^1,2, Eugene Lerman¹, Michal Ziv-Ukelson¹

¹Department of Computer Science, Ben-Gurion University of the Negev, Beer-Sheva, Israel.

Bioinformatics (Oxford, England)

|February 7, 2017

Summary

This summary is machine-generated.

MotifNet is a new web-server for analyzing network motifs, which are recurring patterns in complex networks. This tool simplifies motif discovery and analysis for researchers, offering interactive filtering and visualization capabilities.

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Last Updated: Mar 7, 2026

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Area of Science:

Computational Biology
Network Science
Bioinformatics

Background:

Network motifs are recurring topological patterns in complex networks.
Identifying network motifs aids in understanding network design principles.
Existing tools for motif analysis are often computationally intensive and require local installation.

Purpose of the Study:

To introduce MotifNet, the first open-access web-server for network motif analysis.
To provide researchers with an accessible platform for identifying and analyzing network motifs.

Main Methods:

MotifNet is a web-server implemented using ReactJs and Python, with data stored in a MySQL database.
It supports the analysis of integrated networks with labeled nodes and edges.
The server can search for motifs up to eight nodes in size.

Main Results:

MotifNet offers graphical presentation of output motifs.
Users can interactively filter motifs by significance, instance count, and label information.
The platform allows distinguishing between node-centered motifs and network-wide recurring motifs.

Conclusions:

MotifNet democratizes network motif analysis by providing an easy-to-use, open-access web tool.
It facilitates the exploration of complex network structures and underlying design principles.
The interactive features enhance the usability and depth of motif analysis for researchers.