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| http://dx.doi.org/10.1016/j.scib.2025.07.019 | DOI Listing |
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Article Synopsis
- Nanopore direct RNA sequencing has shown great potential for studying RNA modifications, particularly pseudouridine (Ψ) and N1-methylpseudouridine (m1Ψ), which are important for mRNA vaccines.
- A new computational framework called NanoMUD was developed, utilizing a bidirectional LSTM neural network to predict these modifications with high accuracy from RNA sequencing data.
- The framework enhances the understanding of RNA modifications and their distribution, providing valuable insights for research on modified therapeutic RNA used in vaccines.
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