Literature DB >> 20036522

Hierarchically organized layout for visualization of biochemical pathways.

Jyh-Jong Tsay1, Bo-Liang Wu, Yu-Sen Jeng.   

Abstract

OBJECTIVE: Many complex pathways are described as hierarchical structures in which a pathway is recursively partitioned into several sub-pathways, and organized hierarchically as a tree. The hierarchical structure provides a natural way to visualize the global structure of a complex pathway. However, none of the previous research on pathway visualization explores the hierarchical structures provided by many complex pathways. In this paper, we aim to develop algorithms that can take advantages of hierarchical structures, and give layouts that explore the global structures as well as local structures of pathways.
METHODS: We present a new hierarchically organized layout algorithm to produce layouts for hierarchically organized pathways. Our algorithm first decomposes a complex pathway into sub-pathway groups along the hierarchical organization, and then partition each sub-pathway group into basic components. It then applies conventional layout algorithms, such as hierarchical layout and force-directed layout, to compute the layout of each basic component. Finally, component layouts are joined to form a final layout of the pathway. Our main contribution is the development of algorithms for decomposing pathways and joining layouts.
RESULTS: Experiment shows that our algorithm is able to give comprehensible visualization for pathways with hierarchies, cycles as well as complex structures. It clearly renders the global component structures as well as the local structure in each component. In addition, it runs very fast, and gives better visualization for many examples from previous related research. 2009 Elsevier B.V. All rights reserved.

Mesh:

Year:  2009        PMID: 20036522     DOI: 10.1016/j.artmed.2009.06.002

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  1 in total

1.  Visualization of protein interaction networks: problems and solutions.

Authors:  Giuseppe Agapito; Pietro Hiram Guzzi; Mario Cannataro
Journal:  BMC Bioinformatics       Date:  2013-01-14       Impact factor: 3.169

  1 in total

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