A System for Visualizing and Analyzing Near-Optimal Protein Sequence Alignments

Abstract

System modeling and analysis is an imperfect art and as a consequence there are problems where alternative solutions may exist. Information visualization is often used to enhance system modeling and analysis efforts by taking advantage of human perceptual capabilities. Our research uses visual representations of alternative solutions as a way to aid understanding and foster insight into problems, their solutions, and the underlying algorithms. Specifically, our system visualizes large sets of near-optimal protein sequence alignments. Prior efforts focused on the visualization of near-optimal alignments, using an animation metaphor for providing context to detailed displays. This paper discusses novel extensions: (1) a new overview display, the enhanced path graph; (2) the integration of the detail-oriented (animation) and overview-oriented (path graph) displays; and (3) additional human-computer interaction capabilities for filtering, highlighting, and mixed-initiative interaction that allow researchers to combine their expertise with algorithmic output to gain insight into the sequence alignment algorithms and the problem domain. Two case studies illustrate the effectiveness of this system.