Interoperability of GADU in using heterogeneous grid resources for bioinformatics applications

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• High-throughput bioinformatics tools demand substantial computational resources for genetic sequence analysis.
• Grid computing resources like Open Science Grid and TeraGrid offer scalable solutions for scientific discovery.

Purpose of the Study:

• To describe the requirements for an automated, scalable system (GADU) for running bioinformatics applications on diverse Grid resources.
• To present the architecture of GADU, emphasizing its resource independence and interoperability.

Main Methods:

• Development of the Genome Analysis and Database Update system (GADU).
• Implementation of a resource-independent configuration using the Pegasus-based virtual data system.
• Focus on automating access to heterogeneous Grid resources for bioinformatics tasks.

Main Results:

• GADU enables automated, high-throughput execution of bioinformatics applications on various Grid infrastructures.
• The system's resource-independent design ensures interoperability across heterogeneous Grid environments.
• GADU acts as a gateway for computationally intensive bioinformatics applications on the Grid.

Conclusions:

• GADU provides an automated and scalable solution for large-scale bioinformatics analyses on distributed Grid resources.
• The system's architecture facilitates interoperability and efficient utilization of heterogeneous Grid computing environments.
• GADU enhances the accessibility and throughput of complex bioinformatics applications in a Grid setting.