Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review.

ABSTRACT: CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9) is a popular and effective two-component technology used for targeted genetic manipulation. It is currently the most versatile and accurate method of gene and genome editing, which benefits from a large variety of practical applications. For example, in biomedicine, it has been used in research related to cancer, virus infections, pathogen detection, and genetic diseases. Current CRISPR/Cas9 research is based on data-driven models for on- and off-target prediction as a cleavage may occur at non-target sequence locations. Nowadays, conventional machine learning and deep learning methods are applied on a regular basis to accurately predict on-target knockout efficacy and off-target profile

SUBMITTER: Sherkatghanad Z 

PROVIDER: S-EPMC10199778 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature