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. The GT-Miner program and supplemental materials, including example uses and a user guide, are freely available from http://www.cifr.ncsu.edu/bioinformatics/downloads/

Highlights

  • Contemporary biology faces challenges of analyzing and integrating the ever-accumulating high-throughput datasets to derive a coherent systems-based view of organisms [1]

  • Structures containing nodes and edges linking the nodes, can be used to model biological systems [2] wherein entities such as genes, proteins, RNA elements, and metabolites can serve as the nodes and experiment-specific relationships serve as the edges

  • Extension with new transformations and layouts is through a simple programming interface, giving direct access to the graph structure and to the Java Swing graphic display, and the extensions incorporate into the framework through runtime configuration files

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Summary

Introduction

Contemporary biology faces challenges of analyzing and integrating the ever-accumulating high-throughput datasets to derive a coherent systems-based view of organisms [1]. From a systems biology perspective, software applications supporting visualization, exploration, integration, and analysis of disparate datasets are available, such as cytoscape, VisANT, Osprey, PathwayStudio [3, 4, 5, 6]; they can be economically and computationally expensive, restricted to specific computing platforms, require significant specialist knowledge or have narrow utility, and may be constrained to handle information in specific forms.

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