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Using meta computing tools to facilitate large-scale analyses of biological databases.

A Waugh1, G A Williams, L Wei

  • 1Stanford Medical Informatics, 251 Campus Drive, MSOB X-215, Stanford, CA 94305-5479, USA. waugh@smi.stanford.edu

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|March 27, 2001
PubMed
Summary

Computational tools are crucial for analyzing vast biological data. This study uses Legion, a distributed computing system, to efficiently scan the Protein Data Bank (PDB) for potential cation binding sites.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Structural Biology

Background:

  • Biological data generation is accelerating, necessitating efficient computational analysis tools.
  • High-performance distributed computing is vital for large-scale biological database analysis.

Purpose of the Study:

  • To develop and evaluate computational tools for analyzing large biological datasets.
  • To identify unrecognized potential cation binding sites within the Protein Data Bank (PDB) using distributed computing.

Main Methods:

  • Utilized the Legion distributed computing environment for large-scale computations.
  • Employed the Feature program to scan all protein structures in the PDB.
  • Evaluated the efficiency of Legion's parallel execution capabilities.

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Main Results:

  • Successfully scanned the entire PDB for potential cation binding sites.
  • Identified several unannotated, high-scoring candidate cation binding sites.
  • Demonstrated the efficiency of Legion for large-scale biological data analysis.

Conclusions:

  • Distributed computing, exemplified by Legion, is effective for analyzing extensive biological databases like the PDB.
  • The scan revealed novel potential cation binding sites, offering new avenues for biological research.
  • Further investigation into the identified proteins with unannotated binding sites is warranted.