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BGBlast: a BLAST grid implementation with database self-updating and adaptive replication.

Gabriele A Trombetti1, Ivan Merelli, Alessandro Orro

  • 1Institute for Biomedical Technologies - National Research Council, via Fratelli Cervi 93, 20090 Segrate (MI), Italy.

Studies in Health Technology and Informatics
|May 4, 2007
PubMed
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BGBlast addresses the computational challenges of large-scale sequence analysis by porting BLAST to the Grid platform. This approach efficiently manages distributed BLAST databases, optimizing performance and resource utilization.

Area of Science:

  • Bioinformatics
  • Computational Biology
  • Distributed Computing

Background:

  • BLAST is a widely used bioinformatics tool for sequence alignment.
  • Computational complexity arises with large query sets and reference databases.
  • Efficiently managing large-scale BLAST analyses is a significant challenge.

Purpose of the Study:

  • To present BGBlast, a novel approach for handling the computational complexity of large BLAST executions.
  • To leverage the Grid platform and EGEE infrastructure for enhanced BLAST performance.
  • To introduce innovative features for efficient distributed BLAST database management.

Main Methods:

  • Porting the BLAST application to the Grid platform.
  • Utilizing the distributed computing power of the EGEE infrastructure.

Related Experiment Videos

  • Implementing features for up-to-date and version-controlled database management.
  • Employing delta encoding for space-efficient storage of older database versions.
  • Using an adaptive algorithm to manage database replicas for balancing parallelism and storage costs.

    • Main Results:

    • BGBlast effectively handles the computational complexity of large BLAST executions.
    • Databases are kept up-to-date while allowing regression to earlier versions.
    • Delta encoding provides time and space efficiency for storing database versions.
    • Adaptive replica management dynamically balances execution parallelism and storage costs.

    Conclusions:

    • BGBlast offers a scalable and efficient solution for large-scale sequence analysis using BLAST on the Grid.
    • The system optimizes resource utilization and performance in distributed environments.
    • Innovative database management features enhance the usability and cost-effectiveness of distributed BLAST.