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Maxam-Gilbert Sequencing

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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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Related Experiment Video

Updated: Mar 12, 2026

Empirical, Metagenomic, and Computational Techniques Illuminate the Mechanisms by which Fungicides Compromise Bee Health

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Improving Bloom Filter Performance on Sequence Data Using k-mer Bloom Filters.

David Pellow¹, Darya Filippova², Carl Kingsford³

¹1 The Blavatnik School of Computer Science, Tel Aviv University , Tel Aviv, Israel .

Journal of Computational Biology : a Journal of Computational Molecular Cell Biology

|November 10, 2016

Summary

This summary is machine-generated.

K-mer Bloom filters (kBFs) leverage sequence overlap information to significantly reduce false positives or memory usage in sequencing data analysis. This optimization improves k-mer set storage and querying for applications like metagenomics.

Keywords:

Bloom fitters efficient data structures genomics k-mers.string algorithms

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Area of Science:

Bioinformatics
Computational Biology
Genomics

Background:

K-mer content analysis offers performance improvements in sequencing applications.
Traditional data structures struggle with large k-mer sets; Bloom filters (BFs) are used but have a false positive rate (FPR).

Purpose of the Study:

To investigate methods for reducing FPR or memory footprint of k-mer sets stored in BFs.
To leverage k-mer overlap information from original sequences for BF optimization.

Main Methods:

Developed and analyzed variants of k-mer Bloom filters (kBFs).
Derived theoretical upper bounds for kBF FPR.
Evaluated performance in terms of FPR, memory usage, and query speed.

Main Results:

K-mer overlap information reduced FPR up to 30x with minimal memory increase and slightly slower queries (1.3-1.6x).
Alternatively, k-mer overlap information halved storage space while maintaining original FPR.
Several kBF variants were analyzed.

Conclusions:

K-mer Bloom filters offer significant advantages over standard BFs for storing and querying large k-mer sets.
KBFs provide flexible trade-offs between FPR, memory usage, and query speed for various sequencing applications.