Evidence map›Paper›PMID 41858380›Full record

ArticleBioinformatics advances2026

genCRC32: collision-free CRC32-based hashing of DNA sequences.

Pavel Beran, Michael Rost, Kristina Beranová, Martin Kváč, Dagmar Stehlíková, Obiora Emmanuel Udoh, Eva Jozová, Vladislav Čurn

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Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Pavel BeranFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.ORCID https://orcid.org/0000-0002-2680-3958
Michael RostFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Kristina BeranováFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Martin KváčFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Dagmar StehlíkováFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Obiora Emmanuel UdohFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Eva JozováFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.
Vladislav ČurnFaculty of Agriculture and Technology, University of South Bohemia in České Budějovice, České Budějovice 370 05, Czech Republic.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Motivation: Efficient and collision-free hashing of DNA sequences is essential for accuracy and performance in bioinformatics applications such as genome assembly, sequence alignment, and metagenomic classification. Traditional hashing methods often result in collisions, impacting the precision and/or performance of downstream analyses. Thus, it is highly advantageous to have hashing functions that guarantee collision-free mappings for DNA sequences, particularly for k-mers up to length 16, where practical limits for 32-bit hashing are reached. In this study, we evaluate genCRC32 as a hashing primitive, reporting collision behavior, bucket balance, sensitivity to single-base changes, and speed to inform its potential use in downstream tools. Evaluation within specific software tools is outside the scope of this paper and is planned as future work. Results: We present genCRC32, an innovative hashing method that integrates a straightforward preprocessing step (gen32) with CRC32 hashing, specifically identifying eight CRC32 polynomials that ensure collision-free hashing for all DNA k-mers up to 16 nucleotides in length. Through extensive empirical evaluations, genCRC32 demonstrated zero collisions for these k-mers, achieving a one-to-one mapping without auxiliary data structures. Benchmark tests confirmed minimal computational overhead introduced by preprocessing, maintaining hashing performance comparable to established methods such as MurmurHash3 and xxHash32. Availability and implementation: The source code for genCRC32 is publicly available at: https://github.com/berybox/genCRC32. The implementation is provided in Go (version 1.24) and leverages only standard libraries, ensuring portability and ease of integration into existing bioinformatics workflows.

Identifiers

PMID41858380
PMCPMC12996896

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.