Machine learning approach improves CRISPR-Cas9 guide pairing

Some will say that finding just the right wine to pair with a meal can improve even the finest cuisine, transforming a pleasant gustatory experience into something approaching perfection. But with potentially hundreds of wines to choose from, picking the “right” one can be a chore for the casual wine-lover. That’s where the sommelier comes in, applying expertise to curate a list of only the best pairings to suit one’s needs. A similar process is playing out in the very different world of gene editing, where researchers from the Broad Institute’s Genetic Perturbation Platform (GPP) and Microsoft Research have played the role of “sommelier” for researchers seeking to refine their CRISPR toolkit: they’ve developed a predictive model that reveals which single-guide RNA (sgRNA) sequences are best paired with the genome-engineering…


Link to Full Article: Machine learning approach improves CRISPR-Cas9 guide pairing