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一种用于生物网络布局的通用算法。

A generic algorithm for layout of biological networks.

机构信息

Leibniz-Institute of Plant Genetics and Crop Plant Research (IPK), Corrensstrasse 3, D-06466 Gatersleben, Germany.

出版信息

BMC Bioinformatics. 2009 Nov 12;10:375. doi: 10.1186/1471-2105-10-375.

Abstract

BACKGROUND

Biological networks are widely used to represent processes in biological systems and to capture interactions and dependencies between biological entities. Their size and complexity is steadily increasing due to the ongoing growth of knowledge in the life sciences. To aid understanding of biological networks several algorithms for laying out and graphically representing networks and network analysis results have been developed. However, current algorithms are specialized to particular layout styles and therefore different algorithms are required for each kind of network and/or style of layout. This increases implementation effort and means that new algorithms must be developed for new layout styles. Furthermore, additional effort is necessary to compose different layout conventions in the same diagram. Also the user cannot usually customize the placement of nodes to tailor the layout to their particular need or task and there is little support for interactive network exploration.

RESULTS

We present a novel algorithm to visualize different biological networks and network analysis results in meaningful ways depending on network types and analysis outcome. Our method is based on constrained graph layout and we demonstrate how it can handle the drawing conventions used in biological networks.

CONCLUSION

The presented algorithm offers the ability to produce many of the fundamental popular drawing styles while allowing the exibility of constraints to further tailor these layouts.

摘要

背景

生物网络被广泛用于表示生物系统中的过程,并捕获生物实体之间的相互作用和依赖关系。由于生命科学领域的知识不断增长,它们的规模和复杂性也在稳步增加。为了帮助理解生物网络,已经开发了几种用于布局和图形表示网络以及网络分析结果的算法。然而,当前的算法专门针对特定的布局风格,因此每种网络和/或布局风格都需要不同的算法。这增加了实现的工作量,意味着必须为新的布局风格开发新的算法。此外,在同一图表中组合不同的布局约定还需要额外的工作。用户通常也无法自定义节点的放置位置,以根据其特定需求或任务调整布局,并且对交互式网络探索的支持也很少。

结果

我们提出了一种新颖的算法,可以根据网络类型和分析结果以有意义的方式可视化不同的生物网络和网络分析结果。我们的方法基于约束图布局,并展示了如何处理生物网络中使用的绘图约定。

结论

所提出的算法提供了生成许多基本流行绘图风格的能力,同时允许约束的灵活性进一步调整这些布局。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a4c4/2785797/4007ffa17fef/1471-2105-10-375-1.jpg

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