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Fig. 3 | BMC Bioinformatics

Fig. 3

From: CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning

Fig. 3

Comparison of performance of various methods with the three experimental settings D, E and F. Y-axis denotes the ROC-AUC and X-axis denotes the cell type that we are leaving out. In all three settings, CRISPRpred(SEQ) has beaten DeepCRISPR when leaving out cell HL60. CRISPRpred(SEQ)-E and CRISPRpred(SEQ)-F achieved scores slightly better than DeepCRISPR when leaving out cell HeLa. None of the settings were able to beat DeepCRISPR when leaving out cell HCT116 but managed to achieve a score close to that of DeepCRISPR

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