ArticleNature communications2025
De novo non-canonical nanopore basecalling enables private communication using heavily-modified DNA data at single-molecule level.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- DamageFormer: a damage-aware multimodal deep learning framework for DNA lesion identification from nanopore sequencing.bioRxiv : the preprint server for biology · 2026Article
- Motif caller for sequence reconstruction in motif-based DNA storage.Scientific reports · 2025Article
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Authors and funding
11 authors.
Funding
Abstract
Hidden messages in DNA molecules by employing chemical modifications has been suggested for private data storage and transmission at high information density. However, rapidly decoding these "molecular keys" with corresponding basecallers remains challenging. We present DeepSME, a nanopore sequencing and deep-learning based framework towards single-molecule encryption, demonstrated by using 5-hydroxymethylcytosine (5hmC) substitution for individual nucleotide recognition rather than sequential interactions. This non-natural, motif-insensitive methylation disrupts ion current, resulting in a readout failure of 67.2%-100%, concealing the privacy within the DNAs. We further develop an alignment-free DeepSME basecaller as a key to reconstitute the digital information. Our three-stage training pipeline, expands k-mer size from 4
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