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International Symposium on Bioinformatics Research and Applications

ISBRA 2017: Bioinformatics Research and Applications pp 403–407Cite as

NemoLib: A Java Library for Efficient Network Motif Detection

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Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 10330))

Abstract

A network motif is defined as an overabundant subgraph pattern in a network and has been applied in various biological and medical problems. Various network motif detection algorithms and tools are currently available. However, most existing software programs are outdated, incompatible with modern operating systems, or do not provide sufficient operation instructions. Furthermore, most tools provide limited information regarding network motifs, which necessitates post-processing program to apply to real problems. Consequently, the lack of usability brings a certain amount of skepticism about the relevance of network motifs in investigating real biological problems. Therefore, this paper introduces NemoLib (network motif library) as a general purpose tool for detection and analysis of network motifs. NemoLib is highly programmable Java library which provides for extensibility.

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Authors and Affiliations

  1. Division of Computing and Software Systems, School of Science, Technology, Engineering, and Mathematics, University of Washington Bothell, 18115 Campus Way NE, Bothell, WA, 98011-8246, USA

    Andrew Andersen & Wooyoung Kim

Authors
  1. Andrew Andersen
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  2. Wooyoung Kim
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Corresponding authors

Correspondence to Andrew Andersen or Wooyoung Kim .

Editor information

Editors and Affiliations

  1. Georgia State University, Atlanta, Georgia, USA

    Zhipeng Cai

  2. University of Texas at Dallas, Richardson, Texas, USA

    Ovidiu Daescu

  3. Central South University, Changsha, China

    Min Li

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Andersen, A., Kim, W. (2017). NemoLib: A Java Library for Efficient Network Motif Detection. In: Cai, Z., Daescu, O., Li, M. (eds) Bioinformatics Research and Applications. ISBRA 2017. Lecture Notes in Computer Science(), vol 10330. Springer, Cham. https://doi.org/10.1007/978-3-319-59575-7_42

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  • DOI: https://doi.org/10.1007/978-3-319-59575-7_42

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59574-0

  • Online ISBN: 978-3-319-59575-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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