ArticleBriefings in bioinformatics2026
Ab initio detection of multiple epitranscriptomic modifications from Oxford nanopore technology direct RNA sequencing data.
Article in Briefings in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Epitranscriptomic Analysis of A-to-I RNA Editing and mInternational journal of molecular sciences · 2026Review
- Systematic benchmarking of dorado basecalling models for RNA modification detection with highly multiplexed nanopore sequencing.Nucleic acids research · 2026Article
- A refined Saccharomyces cerevisiae reference transcriptome from direct RNA sequencing, with a reusable pipeline for UTR annotation updates.FEMS yeast research · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Charting the eukaryotic epitranscriptome by direct RNA sequencing is promising but still very challenging, as current bioinformatics tools are based on modification-unaware software and require multiple modification-specific learning steps. Here, we introduce NanoSpeech, a modification-aware basecaller for the ab initio simultaneous detection of multiple modified bases using a transformer model, and NanoListener, which implements a simulated randomers strategy for robust training datasets and a new generation of ONT basecallers. NanoListener and NanoSpeech are independent of the specific ONT chemistry. Once a training dataset has been created, a single model with an expanded vocabulary can accurately basecall both unmodified and modified bases.
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Registered trials
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