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DNA sequencing provides the genetic information contained in a specific DNA fragment, the entire genome, or a complex microbiome. DNA sequences are required for biological researches involving structural analysis and a wide range of applied applications including disease diagnosis, biotechnology, forensic science, epidemiology, microbiology, and biological systematics. Because of its ability to characterize and explain biological phenomena, DNA sequencing research is becoming more common. By comparing healthy and changed DNA sequences, researchers can detect diseases such as genetic disorders or cancers, define antibody repertoires, and suggest treatments best suited to the patient. Having a quick way to sequence DNA allows for the identification and cataloging of more species, as well as faster and more tailored medical care. The disease diagnosis requires an efficient algorithm because DNA contains a large sequence of nucleotides. Aho–Corasick is optimal string pattern matching algorithm which can be used to find relevant patterns in DNA sequence. Here, we proposed a GPU-based multi-string pattern matching implementation of the Aho–Corasick method to evaluate the likelihood that certain nucleotide repeat illnesses and cancer types originate from a DNA sequence. Finding multiple string pattern matching has significantly sped up as compared to the sequential technique.

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Disease Diagnosis from DNA Sequence Using GPU-Based Aho–Corasick Algorithm

  • 会议论文

  • 发表日期：

    2025年

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  • Bandi Krishna,
  • Ramdas Vankdothu,
  • Suresh Kumar Lokhande,
  • Hussain Falih Mahdi,
  • Rakesh Nayak,
  • Bhupesh Kumar Dewangan,
  • Tanupriya Choudhary

摘要

DNA sequencing provides the genetic information contained in a specific DNA fragment, the entire genome, or a complex microbiome. DNA sequences are required for biological researches involving structural analysis and a wide range of applied applications including disease diagnosis, biotechnology, forensic science, epidemiology, microbiology, and biological systematics. Because of its ability to characterize and explain biological phenomena, DNA sequencing research is becoming more common. By comparing healthy and changed DNA sequences, researchers can detect diseases such as genetic disorders or cancers, define antibody repertoires, and suggest treatments best suited to the patient. Having a quick way to sequence DNA allows for the identification and cataloging of more species, as well as faster and more tailored medical care. The disease diagnosis requires an efficient algorithm because DNA contains a large sequence of nucleotides. Aho–Corasick is optimal string pattern matching algorithm which can be used to find relevant patterns in DNA sequence. Here, we proposed a GPU-based multi-string pattern matching implementation of the Aho–Corasick method to evaluate the likelihood that certain nucleotide repeat illnesses and cancer types originate from a DNA sequence. Finding multiple string pattern matching has significantly sped up as compared to the sequential technique.