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Fig. 3 | BMC Bioinformatics

Fig. 3

From: A semi-supervised deep learning approach for predicting the functional effects of genomic non-coding variations

Fig. 3

Comparing the performance of the proposed deep learning model with existing models and a supervised model. a ROC curve in GM12878 dataset. b ROC curve in HepG2 dataset. c ROC curve in K562 dataset. d AUC values showing the performance of the proposed model and a supervised model without pseudo labels in K562 dataset. AUC, area under the ROC (receiver operating characteristic) curve; Supervised_dnn, deep neural network; SSL_dnn, semi-supervised learning by dnn with pseudo labels; \({\upalpha }(\mathrm{t})\), a parameter in the loss function

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