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BioFabric Visualization of Network Alignments

Desai, R. M.; Longabaugh, W. J. R.; Hayes, W. B.

2019-12-19 bioinformatics
10.1101/2019.12.18.881664 bioRxiv
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BackgroundDozens of global network alignment algorithms have been developed over the past fifteen years. Effective network visualization tools are lacking and would enhance our ability to gain an intuitive understanding of the strengths and weaknesses of these algorithms. ResultsWe have created a plugin to the existing network visualization tool BioFabric, called VISNAB: Visualization of Network Alignments using BioFabric. We leverage BioFabrics unique approach to layout (nodes are horizontal lines connected by vertical lines representing edges) to improve understanding of network alignment performance. Our visualization tool allows the user to clearly spot deficiencies in alignments that cannot be detected through simply evaluating and comparing standard numerical topological measures such as the Edge Coverage (EC) or Symmetric Substructure Score (S3). Furthermore, we provide new automatic layouts that allow researchers to identify problem areas in an alignment. Finally, our new definitions of node groups and link groups that arise from our visualization technique allows us to also introduce novel numeric measures for assessing alignment quality. ConclusionsOur new approach to visualize network alignments will allow researchers to gain a new, and better, understanding of the strengths and shortcomings of the many available network alignment algorithms.

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