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Table 2 Evaluation results of single predictor and integrated predictor based on different species

From: EDLm6APred: ensemble deep learning approach for mRNA m6A site prediction

Species Classifiers AUROC MCC ACC Precision Recall
Human BiLSTMOne-hot 0.7810 0.4409 0.7159 0.7716 0.6095
BiLSTMEmbedding 0.8504 0.5602 0.7739 0.8470 0.6661
BiLSTMWord2vec 0.8510 0.5497 0.7695 0.8361 0.6678
EDLm6APred 0.8660 0.5819 0.7843 0.8617 0.6750
Mouse BiLSTMOne-hot 0.7838 0.4354 0.7088 0.7901 0.5739
BiLSTMEmbedding 0.8390 0.5394 0.7642 0.8296 0.6691
BiLSTMWord2vec 0.8464 0.5369 0.7604 0.8429 0.6442
EDLm6APred 0.8588 0.5664 0.7754 0.8579 0.6639
Mix BiLSTMOne-hot 0.8055 0.4758 0.7361 0.7687 0.6755
BiLSTMEmbedding 0.8459 0.5670 0.7801 0.8313 0.7028
BiLSTMWord2vec 0.8463 0.5477 0.7707 0.8189 0.6952
EDLm6APred 0.8605 0.5787 0.7862 0.8355 0.7128
  1. The evaluation indexes with EDLm6 APred better than its any single predictor are show in bold