Table S1. Optimization of hyperparameters of DeepM6ASeq. Table S2. Hyperparameter optimization for other classifiers. Table S3. Metrics of mean performance for tuning of hyperparameters. Table S4. Performance metrics for comparison of DeepM6ASeq with other classifiers on the mammalian unbalanced independent dataset. Table S5. Prediction scores at different confidence thresholds for species models. (PDF 100 kb
Table S1. Primers for qPCR. Table S2. The list of all features considered prior to feature selection...
Table S3. Predicted breast cancer driver genes by the seven permutation models. Table S4. Predicted ...
Additional figures. Distribution of the differences between the predicted value and the true value o...
Figure S1. Performance of the mammalian model on the mammalian validation dataset. Figure S2. Cross-...
Results obtained by reanalyzing real microarray datasets (1 table). The table in the Additional file...
Additional figures. Comparsion of the comprehensive classification performance metrics including ACC...
Additional file 1. Simulated (animal breeding) dataset. Includes four txt files: one for the groupin...
Detailed description of the parameter selection. Figure S3. The 10-CV training accuracies of the pre...
Figure S1. Binding preferences learnt by each individual neural network. Figure S2. Pearson correlat...
Detailed analysis of the prediction accuracies of the test sets. Table S6. Percent of proteins in th...
Supplementary Tables, Algorithm and Figure. Table S1: The result of Fisherâs exact test on trainin...
Features used to train DeepPVP. A table consisting of the features and their representation used in ...
Table S1. Performance of machine learning approaches on depression training dataset (1993 records). ...
Prediction performance. Performance metrics for all cell types and models. (XLSX 3371Â kb
Supplementary Tables and Figures. Table S1: Data used for the BRAKER1 benchmark. Table S2: Data for ...
Table S1. Primers for qPCR. Table S2. The list of all features considered prior to feature selection...
Table S3. Predicted breast cancer driver genes by the seven permutation models. Table S4. Predicted ...
Additional figures. Distribution of the differences between the predicted value and the true value o...
Figure S1. Performance of the mammalian model on the mammalian validation dataset. Figure S2. Cross-...
Results obtained by reanalyzing real microarray datasets (1 table). The table in the Additional file...
Additional figures. Comparsion of the comprehensive classification performance metrics including ACC...
Additional file 1. Simulated (animal breeding) dataset. Includes four txt files: one for the groupin...
Detailed description of the parameter selection. Figure S3. The 10-CV training accuracies of the pre...
Figure S1. Binding preferences learnt by each individual neural network. Figure S2. Pearson correlat...
Detailed analysis of the prediction accuracies of the test sets. Table S6. Percent of proteins in th...
Supplementary Tables, Algorithm and Figure. Table S1: The result of Fisherâs exact test on trainin...
Features used to train DeepPVP. A table consisting of the features and their representation used in ...
Table S1. Performance of machine learning approaches on depression training dataset (1993 records). ...
Prediction performance. Performance metrics for all cell types and models. (XLSX 3371Â kb
Supplementary Tables and Figures. Table S1: Data used for the BRAKER1 benchmark. Table S2: Data for ...
Table S1. Primers for qPCR. Table S2. The list of all features considered prior to feature selection...
Table S3. Predicted breast cancer driver genes by the seven permutation models. Table S4. Predicted ...
Additional figures. Distribution of the differences between the predicted value and the true value o...