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Reliable Method for Assessing Seed Germination, Dormancy, and Mortality under Field Conditions
07:03

Reliable Method for Assessing Seed Germination, Dormancy, and Mortality under Field Conditions

Published on: November 6, 2016

Efficient computation of spaced seeds.

Silvana Ilie1

  • 1Department of Mathematics, Ryerson University, Toronto, ON M5B 2K3, Canada. silvana@ryerson.ca

BMC Research Notes
|March 1, 2012
PubMed
Summary
This summary is machine-generated.

Researchers developed a faster algorithm to find sensitive spaced seeds, improving bioinformatics tools. This advancement enhances the speed and sensitivity of biological sequence similarity searches.

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Genomics

Background:

  • Bioinformatics tools frequently search for local alignments in biological sequences.
  • Exact dynamic programming algorithms are quadratic, necessitating linear-time heuristics like BLAST.
  • Spaced seeds offer higher sensitivity than BLAST's consecutive seeds for approximate sequence searching.

Purpose of the Study:

  • To improve the speed of computing highly sensitive spaced seeds.
  • To enhance existing bioinformatics software through better seed computation.

Main Methods:

  • A new algorithm was developed for the overlap complexity heuristic used by SpEED.
  • The new algorithm improves computational speed by over an order of magnitude.
  • The improved implementation was used to compute enhanced seeds for various software.

Main Results:

  • The new algorithm significantly accelerates the computation of spaced seeds.
  • Improved seeds were generated for several bioinformatics software programs.
  • Multiple seeds with the same weight as MegaBLAST were computed, substantially increasing sensitivity.

Conclusions:

  • Multiple spaced seeds are integral to modern bioinformatics software.
  • Faster computation of high-quality seeds will broaden the application scope of bioinformatics tools.