Literature DB >> 18424458

Fast grid layout algorithm for biological networks with sweep calculation.

Kaname Kojima1, Masao Nagasaki, Satoru Miyano.   

Abstract

MOTIVATION: Properly drawn biological networks are of great help in the comprehension of their characteristics. The quality of the layouts for retrieved biological networks is critical for pathway databases. However, since it is unrealistic to manually draw biological networks for every retrieval, automatic drawing algorithms are essential. Grid layout algorithms handle various biological properties such as aligning vertices having the same attributes and complicated positional constraints according to their subcellular localizations; thus, they succeed in providing biologically comprehensible layouts. However, existing grid layout algorithms are not suitable for real-time drawing, which is one of requisites for applications to pathway databases, due to their high-computational cost. In addition, they do not consider edge directions and their resulting layouts lack traceability for biochemical reactions and gene regulations, which are the most important features in biological networks.
RESULTS: We devise a new calculation method termed sweep calculation and reduce the time complexity of the current grid layout algorithms through its encoding and decoding processes. We conduct practical experiments by using 95 pathway models of various sizes from TRANSPATH and show that our new grid layout algorithm is much faster than existing grid layout algorithms. For the cost function, we introduce a new component that penalizes undesirable edge directions to avoid the lack of traceability in pathways due to the differences in direction between in-edges and out-edges of each vertex. AVAILABILITY: Java implementations of our layout algorithms are available in Cell Illustrator. CONTACT: masao@ims.u-tokyo.ac.jp SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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Year:  2008        PMID: 18424458     DOI: 10.1093/bioinformatics/btn196

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  7 in total

1.  BFL: a node and edge betweenness based fast layout algorithm for large scale networks.

Authors:  Tatsunori B Hashimoto; Masao Nagasaki; Kaname Kojima; Satoru Miyano
Journal:  BMC Bioinformatics       Date:  2009-01-15       Impact factor: 3.169

2.  An efficient biological pathway layout algorithm combining grid-layout and spring embedder for complicated cellular location information.

Authors:  Kaname Kojima; Masao Nagasaki; Satoru Miyano
Journal:  BMC Bioinformatics       Date:  2010-06-18       Impact factor: 3.169

3.  Application of approximate pattern matching in two dimensional spaces to grid layout for biochemical network maps.

Authors:  Kentaro Inoue; Shinichi Shimozono; Hideaki Yoshida; Hiroyuki Kurata
Journal:  PLoS One       Date:  2012-06-05       Impact factor: 3.240

4.  CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.

Authors:  Henry Heberle; Marcelo Falsarella Carazzolle; Guilherme P Telles; Gabriela Vaz Meirelles; Rosane Minghim
Journal:  BMC Bioinformatics       Date:  2017-09-13       Impact factor: 3.169

5.  BioUML: an integrated environment for systems biology and collaborative analysis of biomedical data.

Authors:  Fedor Kolpakov; Ilya Akberdin; Timur Kashapov; Llya Kiselev; Semyon Kolmykov; Yury Kondrakhin; Elena Kutumova; Nikita Mandrik; Sergey Pintus; Anna Ryabova; Ruslan Sharipov; Ivan Yevshin; Alexander Kel
Journal:  Nucleic Acids Res       Date:  2019-07-02       Impact factor: 16.971

6.  A new grid- and modularity-based layout algorithm for complex biological networks.

Authors:  Sheng He; Yi-Jun Liu; Fei-Yue Ye; Ren-Pu Li; Ren-Jun Dai
Journal:  PLoS One       Date:  2019-08-29       Impact factor: 3.240

7.  LucidDraw: efficiently visualizing complex biochemical networks within MATLAB.

Authors:  Sheng He; Juan Mei; Guiyang Shi; Zhengxiang Wang; Weijiang Li
Journal:  BMC Bioinformatics       Date:  2010-01-15       Impact factor: 3.169

  7 in total

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