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Related Experiment Video

Updated: May 10, 2026

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

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Using the iPlant collaborative discovery environment.

Shannon L Oliver^1,2, Andrew J Lenards^1,2, Roger A Barthelson^1,2

¹The iPlant Collaborative.

Current Protocols in Bioinformatics

|June 11, 2013

Summary

This summary is machine-generated.

The iPlant Discovery Environment offers a virtual workbench for plant science research, enabling data exploration, analysis, and sharing for all expertise levels. It integrates cyberinfrastructure and high-performance computing for scalable bioinformatics workflows.

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Area of Science:

Plant biology
Bioinformatics
Computational science

Background:

The iPlant Collaborative aims to address grand challenges in plant biology through informatics and social infrastructure.
Existing cyberinfrastructure supports computational needs but requires accessible interfaces for diverse researchers.

Purpose of the Study:

To describe the features of the Discovery Environment, a graphical interface for the iPlant Collaborative cyberinfrastructure.
To demonstrate how researchers can explore, analyze, and share data using scalable tools and high-performance computing.

Main Methods:

The Discovery Environment provides a virtual workbench with a graphical interface.
It offers access to iPlant's data-management system and high-performance computing resources.
Researchers utilize Applications (Apps) for data analysis and can customize or integrate their own tools.

Main Results:

The Discovery Environment enables users of all expertise levels to access and utilize powerful computational tools.
Bioinformatics workflows for high-throughput sequence data are presented as examples of the environment's capabilities.
Customizable Apps and automated workflows facilitate complex analyses.

Conclusions:

The Discovery Environment enhances accessibility to plant science cyberinfrastructure for a broad research community.
It supports data-driven research and the automation of complex analyses through integrated tools and workflows.
This platform empowers researchers to address significant challenges in plant biology more effectively.