Evidence map›Paper›PMID 41206925›Full record

ArticleBioinformatics (Oxford, England)2025

De-Bruijn graph partitioning for scalable and accurate DNA storage processing.

Florestan De Moor, Olivier Boullé, Dominique Lavenier

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Florestan De MoorIRISA, CNRS, Rennes, 35042, France.
Olivier BoulléIRISA, CNRS, Rennes, 35042, France.
Dominique LavenierIRISA, CNRS, Rennes, 35042, France.ORCID 0000-0003-2557-680X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationDNA-based data storage offers a compelling solution for long-term, high-density archiving. In this framework, accurately reconstructing high-quality encoded sequences after sequencing is critical, as it directly impacts the design of error-correcting codes optimized for DNA storage. Furthermore, efficient and scalable processing is essential to manage the large volumes of data expected in such applications.

resultsWe introduce a novel method based on de-Bruijn graph partitioning, enabling fast and accurate processing of sequencing data regardless of the underlying sequencing technology and without requiring prior knowledge of the information encoded in the oligonucleotides. Evaluated on both synthetic and real datasets, the method achieves excellent precision and recall. It is implemented in C++ within the software ConCluD and optimized for multi-core servers. Our experiments show that a dataset of 89 million reads, corresponding to a 10 GB fasta file, can be fully processed in less than a minute on a standard 32-cores server. AVAILABILITY AND IMPLEMENTATION: The ConCluD software and the scripts to reproduce the experiments from this paper are available at https://gitlab.inria.fr/pim/org.pim.dnarxiv under the GNU AGPLv3 licence. An archival snapshot of the repository is also provided at https://doi.org/10.5281/zenodo.17160067.

Indexed as

DNAInformation Storage and RetrievalSequence Analysis, DNASoftwareAlgorithmsHigh-Throughput Nucleotide SequencingDNA

Identifiers

PMID41206925
PMCPMC12619639

What Socratic holds

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LicenceCC BY
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Registered trials

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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 Socratic graph.