By applying deep learning methods to a large database of zinc finger nucleases, researchers at the University of Toronto and New York University have developed an algorithm, Zfdesign, that was able to design custom zinc fingers for any given stretch of DNA. “I think this system levels the playing field for zinc fingers and CRISPR,” said Philip Kim, co-corresponding author of the team's paper published online in Nature Biotechnology on Jan. 26, 2023.