SBGNViz: A Tool for Visualization and Complexity Management of SBGN Process Description Maps

Area of Science:

• Systems Biology
• Bioinformatics
• Computational Biology

Background:

• Increasing availability of cellular process and pathway information in computable formats like BioPAX and SBGN.
• Critical need for effective visualization of biological pathway data, especially for omics data analysis.
• Growing trend of web-based platforms for biological data analysis necessitates sophisticated web-based pathway viewers.

Purpose of the Study:

• To develop a web-based pathway viewer, SBGNViz, for visualizing biological pathway maps in Systems Biology Graphical Notation (SBGN) Process Description (SBGN-PD) format.
• To support visualization of both BioPAX and SBGN formats.
• To provide advanced features for biological data analysis within a web browser environment.

Main Methods:

• Development of SBGNViz, a web-based pathway viewer.
• Implementation of features for nesting nodes, automatic layout, editing, and highlighting.
• Integration with EntrezGene for detailed pathway member information.
• Creation of both ActionScript and JavaScript editions, with the JavaScript edition offering enhanced complexity management for large maps.

Main Results:

• SBGNViz successfully visualizes biological pathway maps in SBGN-PD, BioPAX, and SBGN formats.
• The viewer includes novel features like arbitrary node nesting, automatic layout, and interactive editing.
• The JavaScript edition of SBGNViz provides effective methods for managing and reducing the complexity of large pathway maps.
• SBGNViz is embeddable into web pages and usable across devices, including touch-enabled ones.

Conclusions:

• SBGNViz addresses the need for accessible and sophisticated web-based pathway visualization tools.
• The tool facilitates the integration of rich pathway information into web-based platforms for biological data analysis.
• SBGNViz supports diverse applications, from single-study result visualization to the development of comprehensive data analysis platforms.