Researchers at New York University (NYU), Columbia University, and the New York Genome Center have developed an artificial intelligence (AI) platform that can predict on- and off-target activity of CRISPR tools that target RNA instead of DNA.

The team paired a deep learning model with CRISPR screens to control the expression of human genes in different ways, akin to either flicking a light switch to shut them off completely or by using a dimmer knob to partially turn down their activity. The resulting neural network, which they called targeted inhibition of gene expression via gRNA design— TIGER—was able to predict efficacy from guide sequence and context. The team suggests the new technology could pave the way to the development of precise gene controls for use in CRISPR-based therapies.

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Genenews, 2023.07.03

AI Predicts Activity of RNA-Targeting CRISPR Tools (genengnews.com)