Title

GT-Miner: a graph-theoretic data miner, viewer, and model processor

Authors

Douglas E. Brown¹, Amy J. Powell¹, Ignazio Carbone¹ and Ralph A. Dean^1, *

Affiliation

¹Center for Integrated Fungal Research (CIFR), Department of Plant Pathology, Box 7251, North Carolina State University, Raleigh, NC 27695 7251

Email

radean2@ncsu.edu; * Corresponding author

Article Type

Software

Date

received September 24, 2008; accepted October 10, 2008; published December 15, 2008

Abstract

Inexpensive computational power combined with high-throughput experimental platforms has created a wealth of biological information requiring analytical tools and techniques for interpretation. Graph-theoretic concepts and tools have provided an important foundation for information visualization, integration, and analysis of datasets, but they have often been relegated to background analysis tasks. GT-Miner is designed for visual data analysis and mining operations, interacts with other software, including databases, and works with diverse data types. It facilitates a discovery-oriented approach to data mining wherein exploration of alterations of the data and variations of the visualization is encouraged. The user is presented with a basic iterative process, consisting of loading, visualizing, transforming, and then storing the resultant information. Complex analyses are built-up through repeated iterations and user interactions. The iterative process is optimized by automatic layout following transformations and by maintaining a current selection set of interest for elements modified by the transformations. Multiple visualizations are supported including hierarchical, spring, and force-directed self-organizing layouts. Graphs can be transformed with an extensible set of algorithms or manually with an integral visual editor. GT-Miner is intended to allow easier access to visual data mining for the non-expert.

Keywords

graph theory; data mining; visualization; information visualization

Citation

Brown et al., Bioinformation 3(5): 235-237 (2008)

Edited by

P. Kangueane

ISSN

0973-2063

Publisher

Biomedical Informatics

License

This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.