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Network Motif Search

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Distributed and Sequential Algorithms for Bioinformatics

Part of the book series: Computational Biology ((COBO,volume 23))

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Abstract

Network motifs are recurring subgraph patterns in biological or other networks. A network motif is assumed to have a specific function associated with it, and these structures are considered as the building blocks of biological networks. Discovery of such motifs is important as it gives insight to the functioning of a network and also provides an alternative means to compare and analyze two or more biological networks. If two networks have common motifs, we can assume they perform some similar basic functions. Finding similarity also helps to find phylogenetic relationships between organisms. Detecting network motifs of a given size is a computationally hard task as the number of possible subgraphs grows exponentially with the size, and also this problem is closely related to the graph isomorphism problem which is not tractable either in the general case or as the subgraph isomorphism problem. Motif discovery involves three subtasks: finding subgraphs of a given size, dividing these into equal isomorphic classes and evaluating the statistical significance of the discovered subgraphs. The last step is usually implemented by generating many random graphs similar to the original one and comparing the frequencies of the subgraphs in the original graph and in these graphs. In this chapter, we describe motif discovery problem, show several sequential, and few distributed existing algorithms. We also provide a general framework for distributed processing of the subtasks involved.

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Authors and Affiliations

  1. Computer Engineering Department, Izmir University, Uckuyular, Izmir, Turkey

    K. Erciyes

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  1. K. Erciyes
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Erciyes, K. (2015). Network Motif Search. In: Distributed and Sequential Algorithms for Bioinformatics. Computational Biology, vol 23. Springer, Cham. https://doi.org/10.1007/978-3-319-24966-7_12

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  • DOI: https://doi.org/10.1007/978-3-319-24966-7_12

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24964-3

  • Online ISBN: 978-3-319-24966-7

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