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

The visualization of biological networks is critically important to aid researchers in understanding complex biological systems and arouses interest in designing efficient layout algorithms to draw biological networks according to their topology structures, especially for those networks with potenti...

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Detalles Bibliográficos
Autores principales: He, Sheng, Liu, Yi-Jun, Ye, Fei-Yue, Li, Ren-Pu, Dai, Ren-Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715240/
https://www.ncbi.nlm.nih.gov/pubmed/31465473
http://dx.doi.org/10.1371/journal.pone.0221620
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author He, Sheng
Liu, Yi-Jun
Ye, Fei-Yue
Li, Ren-Pu
Dai, Ren-Jun
author_facet He, Sheng
Liu, Yi-Jun
Ye, Fei-Yue
Li, Ren-Pu
Dai, Ren-Jun
author_sort He, Sheng
collection PubMed
description The visualization of biological networks is critically important to aid researchers in understanding complex biological systems and arouses interest in designing efficient layout algorithms to draw biological networks according to their topology structures, especially for those networks with potential modules. The algorithms of grid layout series have an advantage in generating compact layouts with overlap-free nodes compared to force-directed; however, extant grid layout algorithms have difficulty in drawing modular networks and often generate layouts of high visual complexity when applied to networks with dense or clustered connectivity structure. To specifically assist the study of modular networks, we propose a grid- and modularity-based layout algorithm (GML) that consists of three stages: network preprocessing, module layout and grid optimization. The algorithm can draw complex biological networks with or without predefined modules based on the grid layout algorithm. It also outperforms other existing grid-based algorithms in the measurement of computation performance, ratio of edge-edge/node-edge crossings, relative edge lengths, and connectivity F-measures. GML helps users to gain insight into the network global characteristics through module layout, as well as to discern network details with grid optimization. GML has been developed as a VisANT plugin (https://hscz.github.io/Biological-Network-Visualization/) and is freely available to the research community.
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spelling pubmed-67152402019-09-10 A new grid- and modularity-based layout algorithm for complex biological networks He, Sheng Liu, Yi-Jun Ye, Fei-Yue Li, Ren-Pu Dai, Ren-Jun PLoS One Research Article The visualization of biological networks is critically important to aid researchers in understanding complex biological systems and arouses interest in designing efficient layout algorithms to draw biological networks according to their topology structures, especially for those networks with potential modules. The algorithms of grid layout series have an advantage in generating compact layouts with overlap-free nodes compared to force-directed; however, extant grid layout algorithms have difficulty in drawing modular networks and often generate layouts of high visual complexity when applied to networks with dense or clustered connectivity structure. To specifically assist the study of modular networks, we propose a grid- and modularity-based layout algorithm (GML) that consists of three stages: network preprocessing, module layout and grid optimization. The algorithm can draw complex biological networks with or without predefined modules based on the grid layout algorithm. It also outperforms other existing grid-based algorithms in the measurement of computation performance, ratio of edge-edge/node-edge crossings, relative edge lengths, and connectivity F-measures. GML helps users to gain insight into the network global characteristics through module layout, as well as to discern network details with grid optimization. GML has been developed as a VisANT plugin (https://hscz.github.io/Biological-Network-Visualization/) and is freely available to the research community. Public Library of Science 2019-08-29 /pmc/articles/PMC6715240/ /pubmed/31465473 http://dx.doi.org/10.1371/journal.pone.0221620 Text en © 2019 He et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
He, Sheng
Liu, Yi-Jun
Ye, Fei-Yue
Li, Ren-Pu
Dai, Ren-Jun
A new grid- and modularity-based layout algorithm for complex biological networks
title A new grid- and modularity-based layout algorithm for complex biological networks
title_full A new grid- and modularity-based layout algorithm for complex biological networks
title_fullStr A new grid- and modularity-based layout algorithm for complex biological networks
title_full_unstemmed A new grid- and modularity-based layout algorithm for complex biological networks
title_short A new grid- and modularity-based layout algorithm for complex biological networks
title_sort new grid- and modularity-based layout algorithm for complex biological networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6715240/
https://www.ncbi.nlm.nih.gov/pubmed/31465473
http://dx.doi.org/10.1371/journal.pone.0221620
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