Base Editor

Base editing is a genome editing technique enabling precise, single-nucleotide alterations, crucial for treating genetic diseases. Current research focuses on improving base editor efficiency and reducing off-target effects, employing machine learning models like attention-based multi-task networks to predict editing outcomes and accelerate design optimization. These predictive models, often incorporating sparsity and disentanglement principles, aim to minimize experimental trial-and-error, thereby enhancing the speed and precision of base editor development. The ultimate goal is to translate this technology into effective clinical applications for genetic disorders.