Towards density-optimal DNA storage with practical bijective coding.

Jiasen Li, Mingkai Dong, Zhengwei Qi, Haibing Guan

Abstract read

In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

1 citing paper in PubMed.

Towards density-optimal DNA storage with practical bijective coding.Nature communications · 2026
Article

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

4 authors.

Jiasen LiSchool of Computer Science, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID 0009-0006-4828-6580

Mingkai DongSchool of Computer Science, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.ORCID 0000-0002-4839-055X

Zhengwei QiSchool of Computer Science, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China.

Haibing GuanSchool of Computer Science, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China. hbguan@sjtu.edu.cn.ORCID 0000-0002-4714-7400

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

DNA storage is a promising solution to data explosion due to its high density and longevity. However, existing coding methods struggle to efficiently avoid error-prone sequences while retaining usable ones, leading to low density and high copy numbers. Here we show Siyuan Code, a DNA storage codec that achieves theoretically optimal density. Our method maps binary data to nearly all suitable low-error sequences in a one-to-one manner, using our data structure to catalog and avoid error-prone patterns. This allows operation under very strict biochemical constraints with minimal redundancy. Experiments demonstrate a storage density of 1.66 bits per nucleotide and a capacity of 41 exabytes per gram of DNA, with perfect data retrieval using only six copies per strand. Encoding and decoding speeds reach approximately 1 megabyte per second on commodity hardware, comparable to early USB flash drives. These results bring DNA storage closer to practical deployment.

Indexed as

Computers, MolecularDNAInformation Storage and RetrievalAlgorithmsDNA

Identifiers

PMID42802272

DOI10.1038/s41467-026-77024-y

PMCPMC13616932

What OpenQuestion holds

Textmetadata

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Registered trials

None linked

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.