Figure 2From: Efficient design of meganucleases using a machine learning approachCross-validation performance of various in silico methods. (Left) %Top10 — percentage of targets with at least one positive molecule in Top10 ranked, (Right) AUC – AUC score (see Material and Methods) Mact - predictions made on the basis of module cleavage activities, Fx — FoldX score, Rt — Rosetta score, SeqMact — protein/target sequences + module cleavage activities, SeqMactFxStr — all features combined (sequences + module cleavage activities + FoldX scores and interactions). Error bars are estimated from 30 independent cross-validation experiments.Back to article page