Evidence map›Paper›PMID 34508146›Full record

ArticleScientific reports2021

A self-contained and self-explanatory DNA storage system.

Min Li, Jiashu Wu, Junbiao Dai, Qingshan Jiang, Qiang Qu, Xiaoluo Huang, Yang Wang

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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

7 authors.

Min Li *Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Jiashu Wu *Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Junbiao DaiShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Qingshan JiangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Qiang QuShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Xiaoluo HuangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China.
Yang WangShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, 518055, China. yang.wang1@siat.ac.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Current research on DNA storage usually focuses on the improvement of storage density by developing effective encoding and decoding schemes while lacking the consideration on the uncertainty in ultra-long-term data storage and retention. Consequently, the current DNA storage systems are often not self-contained, implying that they have to resort to external tools for the restoration of the stored DNA data. This may result in high risks in data loss since the required tools might not be available due to the high uncertainty in far future. To address this issue, we propose in this paper a self-contained DNA storage system that can bring self-explanatory to its stored data without relying on any external tool. To this end, we design a specific DNA file format whereby a separate storage scheme is developed to reduce the data redundancy while an effective indexing is designed for random read operations to the stored data file. We verified through experimental data that the proposed self-contained and self-explanatory method can not only get rid of the reliance on external tools for data restoration but also minimise the data redundancy brought about when the amount of data to be stored reaches a certain scale.

Indexed as

Databases, GeneticAlgorithmsDNAHumansInformation Storage and RetrievalModels, TheoreticalResearchDNA

Identifiers

PMID34508146
PMCPMC8433296

What OpenQuestion holds

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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.