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Maxam-Gilbert Sequencing

Maxam-Gilbert Sequencing

In the same year as the discovery of the Sanger sequencing method, another group of scientists, Allan Maxam and Walter Gilbert, demonstrated their chemical-cleavage method for DNA sequencing. The Maxam-Gilbert method relies on using different chemicals that can cleave the DNA sequence at specific sites, the separation of resulting DNA fragments of variable size using electrophoresis, and deciphering the DNA sequence from the resulting gel bands.
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Updated: May 24, 2026

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Perfect Hamming code with a hash table for faster genome mapping.

Yoichi Takenaka¹, Shigeto Seno, Hideo Matsuda

¹Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka Univesity, 1-5 Yamadaoka, Suita, Osaka, Japan. takenaka@ist.osaka-u.ac.jp

|February 29, 2012

Summary

This summary is machine-generated.

This study introduces a novel hash-based genome mapping method using perfect Hamming codes to efficiently handle DNA sequence mismatches. This approach significantly reduces computation time for mapping short DNA sequences, crucial for next-generation sequencing data analysis.

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

Next-generation sequencing generates vast amounts of data, increasing demand for efficient genome mapping tools.
Current genome mapping tools struggle with handling mismatches in short DNA sequences.
Existing algorithms require significantly more computation time to account for mismatches.

Purpose of the Study:

To develop an accelerated hash-based genome mapping method.
To reduce the computational cost of identifying DNA sequences with mismatches.
To improve the efficiency of mapping short DNA reads to a reference genome.

Main Methods:

Proposed a hash-based genome mapping technique utilizing perfect Hamming codes.
Represented DNA subsequences as words in the Galois extension field GF(2²).
Encoded DNA subsequences into code words of a perfect Hamming code, used as hash keys.

Main Results:

The perfect Hamming code effectively reduces the number of hash references needed for mismatch detection.
Demonstrated approximately a 70% reduction in necessary hash keys for mapping 2-mismatch 21-base subsequences.
The computation time for generating code words is substantially less than traditional hash references.

Conclusions:

Perfect Hamming codes offer a significant advantage in reducing hash references for genome mapping.
The proposed method effectively decreases computation time for mapping short DNA sequences.
This technology is vital for developing faster and more accurate genome mapping software to meet increasing data demands.