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General Information
    • ISSN: 2010-3697
    • Frequency: Bimonthly
    • DOI: 10.7763/IJMO
    • Editor-in-Chief: Prof. Adrian Olaru
    • Executive Editor: Ms.Yoyo Y. Zhou
    • Abstracting/ Indexing: Engineering & Technology Digital Library, ProQuest, Crossref, Electronic Journals Library, Google Scholar, EI (INSPEC, IET).
    • E-mail ijmo@iacsitp.com
Editor-in-chief
Prof. Adrian Olaru
University Politehnica of Bucharest, Romania
I'm happy to take on the position of editor in chief of IJMO. It's a journal that shows promise of becoming a recognized journal in the area of modelling and optimization. I'll work together with the editors to help it progress.
IJMO 2014Vol.4(5): 367-374 ISSN: 2010-3697
DOI: 10.7763/IJMO.2014.V4.403

Application of a K-Ladder Connectivity Algorithm for Clustering of Protein Evolutionary Network

Reshma Nibhani, Avi Soffer, Ahuva Mu'alem, Zeev Volkovich, and Zakharia Frenkel
Abstract—An evolutionary network (EN) in formatted protein sequence space is a very large graph representing information about sequence similarity of relatively short protein fragments. This graph can be used for detecting hidden relatedness between proteins, which is highly significant in protein annotation. Effective EN analysis requires an appropriate graph clustering approach. Based on the fact that biological relatedness is strongly dependent on the number of independent graph nodes connections, we develop a network clustering method that is capable to produce quality clusters the members of which have a satisfactory level of relatedness. In this article we describe a new network partitioning method which is based on the k-cycles graph connectivity approach. After formally defining a unique structure, named k-ladder connectivity, we demonstrate that the k-ladder-based algorithm is able to successfully detect the groups of functionally related proteins. To exhibit the quality of the method, we have conducted a set of experiments in which it has been very effective in clustering of EN, as well as the significantly denser protein-protein interaction networks (PPINs). Furthermore, it can be simply adapted for more complicated structures than cycles, as well as applied to other large networks of different types.

Index Terms—K-ladder, connectivity algorithm, network clustering, protein evolutionary network, formatted protein sequence space, protein-protein interaction networks.

The authors are with the ORT Braude College of Engineering, Karmiel, Israel and Research Fellow at Institute of Evolution, University of Haifa, Israel (e-mail: reshma.iidsalld2007@gmail.com, asoffer@braude.ac.il and ahumu@yahoo.com, vlvolkov@braude.ac.il, zakharf@research.haifa.ac.il).

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Cite: Reshma Nibhani, Avi Soffer, Ahuva Mu'alem, Zeev Volkovich, and Zakharia Frenkel, "Application of a K-Ladder Connectivity Algorithm for Clustering of Protein Evolutionary Network," International Journal of Modeling and Optimization vol. 4, no. 5, pp. 367-374, 2014.

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