Evidence map›Paper›PMID 41880514›Full record

ArticleScience advances2026

Machine learning-directed massively parallel programmable nucleic acid amplification.

Zhi Weng, Wenle Huang, Yi Wu, Xuehao Xiu, Hui Lv, Fei Wang, Xiaolei Zuo, Chunhai Fan, Ping Song

Abstract read
In one paragraph

Article in Science 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.

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

9 authors.

Zhi WengInternational Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, National Center for Translational Medicine, Shanghai 200030, China.ORCID 0000-0003-0136-1978
Wenle HuangInternational Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, National Center for Translational Medicine, Shanghai 200030, China.
Yi WuInternational Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, National Center for Translational Medicine, Shanghai 200030, China.ORCID 0009-0003-1951-495X
Xuehao XiuInternational Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, National Center for Translational Medicine, Shanghai 200030, China.ORCID 0000-0003-0799-6683
Hui LvInstitute of Materiobiology, College of Sciences, Shanghai University, Shanghai 200444, China.ORCID 0009-0007-4900-9021
Fei WangState Key Laboratory of Synergistic Chem-Bio Synthesis, School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0003-3948-6899
Xiaolei ZuoState Key Laboratory of Synergistic Chem-Bio Synthesis, School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0001-7505-2727
Chunhai FanState Key Laboratory of Synergistic Chem-Bio Synthesis, School of Chemistry and Chemical Engineering, New Cornerstone Science Laboratory, Frontiers Science Center for Transformative Molecules, Zhangjiang Institute for Advanced Study and National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai 200240, China.ORCID 0000-0002-7171-7338
Ping SongInternational Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, National Center for Translational Medicine, Shanghai 200030, China.ORCID 0000-0001-5947-4604

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dynamic regulation of amplification efficiency is pivotal yet challenging in molecular diagnostics and DNA data storage. Here, we develop a thermodynamics-based approach to achieve continuous and precise modulation of nucleic acid amplification efficiency. By decoupling sequence specificity from hybridization energy regulation via a primer-tag compensation strategy, we demonstrate programmed amplification with high resolution (33 versus 81%). Leveraging 2483 experimental data, we constructed a machine learning model that improved prediction accuracy from

Indexed as

Machine LearningNucleic Acid Amplification TechniquesHigh-Throughput Nucleotide SequencingHumansThermodynamics

Identifiers

PMID41880514
PMCPMC13015887

What OpenQuestion holds

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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.