DTMP-prime: A deep transformer-based model for predicting prime editing efficiency and PegRNA activity.

ABSTRACT: Prime editors are CRISPR-based genome engineering tools with significant potential for rectifying patient mutations. However, their usage requires experimental optimization of the prime editing guide RNA (PegRNA) to achieve high editing efficiency. This paper introduces the deep transformer-based model for predicting prime editing efficiency (DTMP-Prime), a tool specifically designed to predict PegRNA activity and prime editing (PE) efficiency. DTMP-Prime facilitates the design of appropriate PegRNA and ngRNA. A transformer-based model was constructed to scrutinize a wide-ranging set of PE data, enabling the extraction of effective features of PegRNAs and target DNA sequences. The integration of these features with the proposed encoding strategy and DNABERT-based embedding has notably impr

SUBMITTER: Alipanahi R 

PROVIDER: S-EPMC11626815 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature