Machine-learning algorithm predicts how cells repair broken DNA

The human genome has its own proofreaders and editors, and their handiwork is not as haphazard as once thought. When DNA's double helix is broken after damage from, say, exposure to X-rays, molecular machines perform a kind of genetic "auto-correction" to put the genome back together -- but those repairs are often imperfect. Just as your smartphone might amend a misspelled text message into an incoherent phrase, the cell's natural DNA repair process can add or remove bits of DNA at the break site in a seemingly random and unpredictable manner. Editing genes with CRISPR-Cas9 allows scientists to break DNA at specific locations, but this can create "spelling errors" that alter the function of genes. This response to CRISPR-induced damage, called "end joining," is useful for disabling a gene, but researchers have deemed it too error-prone to exploit for therapeutic purposes.