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Consistent visualizations of changing knowledge
Hannah J Tipney1, Ronald P Schuyler, Lawrence Hunter
1University of Colorado, Pharmacology, Aurora, CO.
Summit on Translational Bioinformatics
|February 25, 2011
Summary
Biological networks evolve with new data. Retaining user customizations and visualizing provenance aids network exploration and discovery, supported by the ReOrient system.
Area of Science:
- Computational Biology
- Bioinformatics
- Systems Biology
Background:
- Biological networks are crucial for representing complex biological data.
- Evolving biological knowledge necessitates dynamic network representations.
- Customization of networks by researchers presents challenges in knowledge management.
Purpose of the Study:
- To address the challenge of evolving biological knowledge in network representations.
- To enhance network exploration and analysis in the face of changing data.
- To present the ReOrient system for managing knowledge change in biological networks.
Main Methods:
- Implementing retention of user customizations in network analysis.
- Collecting and visualizing knowledge provenance.
- Extending the Hanalyzer system to create ReOrient.
Main Results:
- User customizations and provenance visualization facilitate effective network exploration.
- The ReOrient system supports network analysis amidst evolving knowledge.
- Improved insight generation and hypothesis formulation through dynamic network exploration.
Conclusions:
- Effective management of evolving biological knowledge is key for discovery.
- Systematic tracking of network changes and user interactions enhances biological insights.
- The ReOrient system offers a robust solution for dynamic biological network analysis.
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