Visual Analysis of Patterns and Substructure Interactions in Complex Chemical Compounds
Abstract
Substructure composition can determine the activity of compounds. To understand the potential factors affecting the compound activity, users need first to analyze patterns and how substructures interact with each other. In addition to the traditional statistical approach, interactive visualization can bring significant value with intuitive analysis and involvement of human judgment. This research study presents an interactive visualization system for visual pattern analysis. With various visualizations and data manipulation, the system enables users to explore patterns and their relationships, as well as discover how substructures interaction may affect the activity of compounds. Users will be able to derive insights and better understand the data effectively and potentially benefit from the analysis in fields such as drug discovery.
Degree
M.Sc.
Advisors
Chen, Purdue University.
Subject Area
Biochemistry|Medicine
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