Data mining with iPlant: a meeting report from the 2013 GARNet workshop, Data mining with iPlant

Area of Science:

• Plant science
• Bioinformatics
• Genomics

Background:

• High-throughput sequencing has led to a 'data deluge' in biology, with datasets reaching terabytes.
• Wet bench biologists often lack the necessary data analysis skills and infrastructure for large-scale data.
• Storing and sharing large datasets create bottlenecks for research collaboration.

Framework:

• The iPlant Collaborative provides free cyberinfrastructure for data storage and analysis.
• Leverages high-performance computing to manage and analyze large biological datasets.
• Aimed at alleviating bottlenecks in the plant science data pipeline.

Implementation:

• A four-day workshop on Data mining with iPlant was held in September 2013 at Warwick University.
• Trained UK plant science researchers on using the iPlant platform.
• Focused on practical application of iPlant for research.

Implications:

• iPlant lowers barriers to accessing and utilizing complex bioinformatics resources.
• Facilitates scientific discovery in plant science through enhanced data analysis.
• Serves as a platform for education and outreach in bioinformatics and data science.