An Overview and Comparative Analysis of CRISPR-SpCas9 gRNA Activity Prediction Tools

The CRISPR Journal, Год журнала: 2025, Номер unknown

Опубликована: Март 27, 2025

Design of guide RNA (gRNA) with high efficiency and specificity is vital for successful application the CRISPR gene editing technology. Although many machine learning (ML) deep (DL)-based tools have been developed to predict gRNA activities, a systematic unbiased evaluation their predictive performance still needed. Here, we provide brief overview in silico design assess datasets statistical metrics used evaluating model performance. We benchmark seven ML DL-based CRISPR-Cas9 prediction across nine covering six cell types three species. The DL models CRISPRon DeepHF outperform other exhibiting greater accuracy higher Spearman correlation coefficient multiple datasets. compile all into GuideNet resource web portal, aiming facilitate streamline sharing Furthermore, summarize features affecting activity, providing important insights further development more accurate models.

Язык: Английский

The future of ex vivo hematopoietic stem cell gene editing: what’s next

Regenerative Medicine, Год журнала: 2025, Номер unknown, С. 1 - 4

Опубликована: Март 26, 2025

Язык: Английский