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Rare Event Detection Using Error-corrected DNA and RNA Sequencing
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Improving hash-q exact string matching algorithm with perfect hashing for DNA sequences.

Abdullah Ammar Karcioglu1, Hasan Bulut1

  • 1Department of Computer Engineering, Ege University, Izmir, Turkey.

Computers in Biology and Medicine
|March 4, 2021
PubMed
Summary

This study introduces a novel hash function to eliminate collisions in DNA sequence matching, improving exact string matching algorithms. The new methods offer faster runtimes and fewer comparisons for DNA sequence analysis.

Keywords:
DNA SequencesHash functionPattern matchingSequence analysisString matching algorithms

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Area of Science:

  • Computer Science
  • Bioinformatics
  • Computational Biology

Background:

  • Exact string matching algorithms are crucial for applications like text search and bioinformatics.
  • Traditional hash-based algorithms face challenges like hash collisions, impacting efficiency.

Purpose of the Study:

  • To propose a novel hash function that eliminates hash collisions for DNA sequences.
  • To develop two improved exact string matching algorithms utilizing the new hash function.

Main Methods:

  • A new hash function designed for perfect hashing of DNA sequences was developed.
  • Two exact string matching algorithms were proposed: one replacing the Hash-q function, and another optimizing shift calculations.
  • Performance was evaluated against six existing algorithms using E. Coli, Human Chromosome1, and synthetic datasets.

Main Results:

  • The proposed hash function provides perfect hashing for DNA sequences efficiently.
  • The new algorithms demonstrated superior performance compared to existing methods.
  • Key performance improvements were observed in average runtime, character comparisons, and hash comparisons.

Conclusions:

  • The novel hash function effectively resolves hash collisions in DNA sequence matching.
  • The developed exact string matching algorithms offer significant performance enhancements.
  • These advancements are beneficial for computational biology and large-scale sequence analysis.