Abstract
BackgroundBiochemical networks play an essential role in systems biology. Rapidly growing network data and versatile research activities call for convenient visualization tools to aid intuitively perceiving abstract structures of networks and gaining insights into the functional implications of networks. There are various kinds of network visualization software, but they are usually not adequate for visual analysis of complex biological networks mainly because of the two reasons: 1) most existing drawing methods suitable for biochemical networks have high computation loads and can hardly achieve near real-time visualization; 2) available network visualization tools are designed for working in certain network modeling platforms, so they are not convenient for general analyses due to lack of broader range of readily accessible numerical utilities.ResultsWe present LucidDraw as a visual analysis tool, which features (a) speed: typical biological networks with several hundreds of nodes can be drawn in a few seconds through a new layout algorithm; (b) ease of use: working within MATLAB makes it convenient to manipulate and analyze the network data using a broad spectrum of sophisticated numerical functions; (c) flexibility: layout styles and incorporation of other available information about functional modules can be controlled by users with little effort, and the output drawings are interactively modifiable.ConclusionsEquipped with a new grid layout algorithm proposed here, LucidDraw serves as an auxiliary network analysis tool capable of visualizing complex biological networks in near real-time with controllable layout styles and drawing details. The framework of the algorithm enables easy incorporation of extra biological information, if available, to influence the output layouts with predefined node grouping features.
Highlights
Biochemical networks play an essential role in systems biology
For maximal computation speed, the layout algorithm was implemented in C++ and compiled into a .mexw32 file to work in MATLAB
Network data and example layouts The networks used in this work were built from a set of metabolic reactions that are taken from a reconstructed genome-wide metabolic network of P. aeruginosa PAO1 [17]
Summary
Biochemical networks play an essential role in systems biology. Rapidly growing network data and versatile research activities call for convenient visualization tools to aid intuitively perceiving abstract structures of networks and gaining insights into the functional implications of networks. The prevalence of computer-aided technologies for modeling large-scale biochemical networks causes a strong demand on visualization tools for intuitive presentation of the complex network structures. Barsky et al use similar strategy in their software Cerebral in which nodes are placed in predefined layers according to the subcellular localizations. They use a technique to bundle edges connected to hub nodes and improve visual effect dramatically when high degree nodes are present [3]. Cerebral is developed further as a new visualization tool for analyzing experimental data in the context of an interaction graph model [9]
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