Improved CRISPR/Cas9 Off-target Prediction with DNABERT and Epigenetic Features
This study improves CRISPR/Cas9 off-target prediction by integrating DNABERT with epigenetic features, showing better performance than existing models.
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Kanazawa UniversityORCID 0000-0001-5474-7087Unclaimed ORCID profile · follow to get notified of new preprints
3 papers
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This study improves CRISPR/Cas9 off-target prediction by integrating DNABERT with epigenetic features, showing better performance than existing models.
Hiro Takahashi, Shido Miyaki, Hitoshi Onouchi…·Motoyuki Itoh
The paper identifies conserved upstream open reading frames (uORFs) in animal genomes and finds seven novel regulatory uORFs that repress main ORF translation.
Hiro Takahashi, Noriya Hayashi, Yuta Hiragori…·Hitoshi Onouchi
The paper introduces a pipeline called ESUCA to identify conserved upstream ORFs (CPuORFs) across multiple plant species and finds that many of these CPuORFs are functionally conserved.