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Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples
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Toward optimizing the cache performance of suffix trees for sequence analysis algorithms suffix tree cache

Chih Lee1, Chun-Hsi Huang

  • 1Department of Computer Science and Engineering, University of Connecticut, 06269 Storrs, CT, USA. chih.lee@uconn.edu

Advances in Experimental Medicine and Biology
|September 25, 2010
PubMed
Summary
This summary is machine-generated.

Optimizing suffix trees with improved spatial locality speeds up maximal exact repeat finding. Cache-oblivious algorithms reduce cache misses, enhancing performance in bioinformatics analyses.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Algorithm Optimization

Background:

  • Suffix tree construction is well-studied, but post-construction operations are less optimized.
  • Maximal exact repeat finding is a crucial bioinformatics task relying on suffix trees.

Purpose of the Study:

  • To investigate the impact of improved spatial locality on suffix tree post-construction operations.
  • To evaluate cache-oblivious algorithms for maximal exact repeat finding.

Main Methods:

  • Implemented two versions of suffix trees tailored for a maximal exact repeat finding algorithm (MERF).
  • Developed two variants of MERF, one cache-oblivious and one non-optimized.
  • Conducted experiments using the 16 chromosomes of Saccharomyces cerevisiae.

Main Results:

  • The cache-oblivious MERF demonstrated superior speed compared to its non-optimized counterpart.
  • Consistently lower cache miss rates were observed for the optimized version across all tested cases.
  • Performance gains were evident in post-construction operations on suffix trees.

Conclusions:

  • Improved spatial locality significantly enhances the efficiency of suffix tree operations.
  • Cache-oblivious algorithms are effective for accelerating maximal exact repeat finding in bioinformatics.
  • Optimized suffix tree implementations offer substantial performance benefits for genomic data analysis.