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Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps

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  • Kentaro Inoue
  • Shinichi Shimozono
  • Hideaki Yoshida
  • Hiroyuki Kurata

Abstract

Background: For visualizing large-scale biochemical network maps, it is important to calculate the coordinates of molecular nodes quickly and to enhance the understanding or traceability of them. The grid layout is effective in drawing compact, orderly, balanced network maps with node label spaces, but existing grid layout algorithms often require a high computational cost because they have to consider complicated positional constraints through the entire optimization process. Results: We propose a hybrid grid layout algorithm that consists of a non-grid, fast layout (preprocessor) algorithm and an approximate pattern matching algorithm that distributes the resultant preprocessed nodes on square grid points. To demonstrate the feasibility of the hybrid layout algorithm, it is characterized in terms of the calculation time, numbers of edge-edge and node-edge crossings, relative edge lengths, and F-measures. The proposed algorithm achieves outstanding performances compared with other existing grid layouts. Conclusions: Use of an approximate pattern matching algorithm quickly redistributes the laid-out nodes by fast, non-grid algorithms on the square grid points, while preserving the topological relationships among the nodes. The proposed algorithm is a novel use of the pattern matching, thereby providing a breakthrough for grid layout. This application program can be freely downloaded from http://www.cadlive.jp/hybridlayout/hybridlayout.html.

Suggested Citation

  • Kentaro Inoue & Shinichi Shimozono & Hideaki Yoshida & Hiroyuki Kurata, 2012. "Application of Approximate Pattern Matching in Two Dimensional Spaces to Grid Layout for Biochemical Network Maps," PLOS ONE, Public Library of Science, vol. 7(6), pages 1-12, June.
  • Handle: RePEc:plo:pone00:0037739
    DOI: 10.1371/journal.pone.0037739
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    Cited by:

    1. ThienLuan Ho & Seung-Rohk Oh & HyunJin Kim, 2017. "A parallel approximate string matching under Levenshtein distance on graphics processing units using warp-shuffle operations," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-15, October.
    2. Koh Sasaki & Takumi Yamamoto & Masahiko Miyao & Takashi Katsuta & Ichiro Kono, 2017. "Network centrality analysis to determine the tactical leader of a sports team," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(6), pages 822-831, November.

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