Treffer: CytoKavosh: a cytoscape plug-in for finding network motifs in large biological networks.

Title:
CytoKavosh: a cytoscape plug-in for finding network motifs in large biological networks.
Authors:
Masoudi-Nejad A; Laboratory of Systems Biology and Bioinformatics (LBB), Institute of Biochemistry and Biophysics, University of Tehran, Tehran, Iran. amasoudin@ibb.ut.ac.ir, Ansariola M, Kashani ZR, Salehzadeh-Yazdi A, Khakabimamaghani S
Source:
PloS one [PLoS One] 2012; Vol. 7 (8), pp. e43287. Date of Electronic Publication: 2012 Aug 29.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Imprint Name(s):
Original Publication: San Francisco, CA : Public Library of Science
MeSH Terms:
Software*, Computational Biology/*methods , Protein Interaction Mapping/*methods, Algorithms ; Amino Acid Motifs ; Computer Simulation ; Models, Biological ; Programming Languages ; Protein Structure, Tertiary ; Systems Biology
References:
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FEBS Lett. 2007 Jun 19;581(15):2776-82. (PMID: 17531981)
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Bioinformatics. 2008 Jul 1;24(13):i241-9. (PMID: 18586721)
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BMC Bioinformatics. 2004 Jan 30;5:10. (PMID: 15018656)
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Entry Date(s):
Date Created: 20120907 Date Completed: 20130219 Latest Revision: 20211021
Update Code:
20250114
PubMed Central ID:
PMC3430699
DOI:
10.1371/journal.pone.0043287
PMID:
22952659
Database:
MEDLINE

Weitere Informationen

Network motifs are small connected sub-graphs that have recently gathered much attention to discover structural behaviors of large and complex networks. Finding motifs with any size is one of the most important problems in complex and large networks. It needs fast and reliable algorithms and tools for achieving this purpose. CytoKavosh is one of the best choices for finding motifs with any given size in any complex network. It relies on a fast algorithm, Kavosh, which makes it faster than other existing tools. Kavosh algorithm applies some well known algorithmic features and includes tricky aspects, which make it an efficient algorithm in this field. CytoKavosh is a Cytoscape plug-in which supports us in finding motifs of given size in a network that is formerly loaded into the Cytoscape work-space (directed or undirected). High performance of CytoKavosh is achieved by dynamically linking highly optimized functions of Kavosh's C++ to the Cytoscape Java program, which makes this plug-in suitable for analyzing large biological networks. Some significant attributes of CytoKavosh is efficiency in time usage and memory and having no limitation related to the implementation in motif size. CytoKavosh is implemented in a visual environment Cytoscape that is convenient for the users to interact and create visual options to analyze the structural behavior of a network. This plug-in can work on any given network and is very simple to use and generates graphical results of discovered motifs with any required details. There is no specific Cytoscape plug-in, specific for finding the network motifs, based on original concept. So, we have introduced for the first time, CytoKavosh as the first plug-in, and we hope that this plug-in can be improved to cover other options to make it the best motif-analyzing tool.