An efficient grid layout algorithm for biological networks utilizing various biological attributes |
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Authors: | Kaname Kojima Masao Nagasaki Euna Jeong Mitsuru Kato Satoru Miyano |
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Institution: | (1) Human Genome Center, Institute of Medical Science, University of Tokyo, 4-6-1 Shirokanedai, Minato-ku Tokyo, 108-8639, Japan |
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Abstract: | Background Clearly visualized biopathways provide a great help in understanding biological systems. However, manual drawing of large-scale
biopathways is time consuming. We proposed a grid layout algorithm that can handle gene-regulatory networks and signal transduction
pathways by considering edge-edge crossing, node-edge crossing, distance measure between nodes, and subcellular localization
information from Gene Ontology. Consequently, the layout algorithm succeeded in drastically reducing these crossings in the
apoptosis model. However, for larger-scale networks, we encountered three problems: (i) the initial layout is often very far
from any local optimum because nodes are initially placed at random, (ii) from a biological viewpoint, human layouts still
exceed automatic layouts in understanding because except subcellular localization, it does not fully utilize biological information
of pathways, and (iii) it employs a local search strategy in which the neighborhood is obtained by moving one node at each
step, and automatic layouts suggest that simultaneous movements of multiple nodes are necessary for better layouts, while
such extension may face worsening the time complexity. |
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