Evidence map›Paper›PMID 41588883›Full record

ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2026

Highly Secure In Vivo DNA Data Storage Driven by Genomic Dynamics.

Jiaxin Xu, Yu Wang, Haibo Zhou, Mingen Li, Yang Wang, Lingwei Wang, Hui Mei, Junbiao Dai, Shanze Chen, Xiaoluo Huang

Abstract read
In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2026. 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

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

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

10 authors.

Jiaxin XuDepartment of Pulmonary and Critical Care Medicine, Post-Doctoral Scientific Research Station of Basic Medicine, Shenzhen Key Laboratory of Respiratory Disease, Shenzhen Clinical Research Center for Respiratory Disease, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, (The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China.
Yu WangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Haibo ZhouCollege of Pharmacy, Jinan University, Guangzhou, Guangdong, China.
Mingen LiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Yang WangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Lingwei WangDepartment of Pulmonary and Critical Care Medicine, Post-Doctoral Scientific Research Station of Basic Medicine, Shenzhen Key Laboratory of Respiratory Disease, Shenzhen Clinical Research Center for Respiratory Disease, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, (The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China.
Hui MeiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Junbiao DaiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.
Shanze ChenDepartment of Pulmonary and Critical Care Medicine, Post-Doctoral Scientific Research Station of Basic Medicine, Shenzhen Key Laboratory of Respiratory Disease, Shenzhen Clinical Research Center for Respiratory Disease, Shenzhen Institute of Respiratory Diseases, Shenzhen People's Hospital, (The Second Clinical Medical College of Jinan University, The First Affiliated Hospital of Southern University of Science and Technology), Shenzhen, Guangdong, China.
Xiaoluo HuangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China.ORCID https://orcid.org/0009-0006-1166-6838

Funding

Innovation Program of Chinese Academy of Agricultural Sciences and Shenzhen Outstanding Talents Training FundMajor Project of Guangzhou National Laboratory GZNL2024A02003National Key Research and Development Program of China 2022YFF0710800National Key Research and Development Program of China 2022YFF0710801National Key Research and Development Program of China 2022YFF0710802National Natural Science Foundation of China 32201207Natural Science Foundation of Guangdong Province 2024A1515012923Shenzhen Clinical Research Center for Respiratory Disease LCYSSQ20220823091203007Shenzhen Key Laboratory of Respiratory Diseases SYSPG20241211173920041Shenzhen Medical Academy of Research and Translation B2302041Shenzhen Medical Academy of Research and Translation C2302001Shenzhen Science and Technology Program JCYJ2025060414246036Shenzhen Science and Technology Program KQTD20180413181837372Shenzhen Science and Technology Program RCYX20221008092950122
6 · The paper itself

Abstract

DNA is a promising medium for next-generation data storage because of ultrahigh information density and stability. DNA storage within living organisms presents further advantages, such as self-replication, compactness, and concealment. Early efforts primarily developed predetermined methods for encoding and decoding data using in vivo DNA sequences. However, these methods may pose a security risk while opening a clear channel for potential data access and breaches. To address these challenges, we propose a unified paradigm, integrated computational-biological programming (ICBP), by exploiting the intrinsic digital characteristics within computational and microbial systems. ICBP involves the construction of dynamic code tables from gene regulatory networks or complete genomes across diverse species, expanding the key space by more than 100 orders of magnitude compared with existing methods. The encryption algorithm in ICBP benefits from DNA encoding, computing, and computational operations, leading to superior encryption quality and resistance to brute force and statistical attacks. Furthermore, we demonstrated the practical utility of ICBP via the successful encryption, microbial storage, and decryption of digital files within living systems, achieving 100% data recovery after 100 generations of replication. By combining computational logic with the biological complexities of living systems, the ICBP offers a transformative strategy for secure DNA data storage.

Indexed as

Computational BiologyComputer SecurityDNAGenomicsInformation Storage and RetrievalAlgorithmsDNAcomputational chaosdata securitydynamic code tablein vivo DNA data storage

Identifiers

PMID41588883
PMCPMC12948191

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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 OpenQuestion graph.