Literature DB >> 28165111

MotifNet: a web-server for network motif analysis.

Ilan Y Smoly1,2, Eugene Lerman1, Michal Ziv-Ukelson1, Esti Yeger-Lotem2,3.   

Abstract

SUMMARY: Network motifs are small topological patterns that recur in a network significantly more often than expected by chance. Their identification emerged as a powerful approach for uncovering the design principles underlying complex networks. However, available tools for network motif analysis typically require download and execution of computationally intensive software on a local computer. We present MotifNet, the first open-access web-server for network motif analysis. MotifNet allows researchers to analyze integrated networks, where nodes and edges may be labeled, and to search for motifs of up to eight nodes. The output motifs are presented graphically and the user can interactively filter them by their significance, number of instances, node and edge labels, and node identities, and view their instances. MotifNet also allows the user to distinguish between motifs that are centered on specific nodes and motifs that recur in distinct parts of the network.
AVAILABILITY AND IMPLEMENTATION: MotifNet is freely available at http://netbio.bgu.ac.il/motifnet . The website was implemented using ReactJs and supports all major browsers. The server interface was implemented in Python with data stored on a MySQL database. CONTACT: estiyl@bgu.ac.il or michaluz@cs.bgu.ac.il. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

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Year:  2017        PMID: 28165111     DOI: 10.1093/bioinformatics/btx056

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  3 in total

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2.  Morbi-Mortality of the Victims of Internal Conflict and Poor Population in the Risaralda Province, Colombia.

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Journal:  Int J Environ Res Public Health       Date:  2019-05-11       Impact factor: 3.390

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Journal:  Cell Rep       Date:  2020-04-28       Impact factor: 9.423

  3 in total

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