Deep learning framework for RNA 5hmC prediction using RNA language model embeddings
Table 6
Performance results of different deep learning models which were trained on the 80% Training set and tested on the Validation set (the remaining 20% Training set). The highest values of each metric are boldfaced. The scores are presented in ‘mean±standard deviation’ format. Here, in the {DL1 + DL2} architecture, Word embeddings are used as input to the DL1 branch, and RiNALMo embeddings are used as input to the DL2 branch. This experiment was repeated 20 times with different random seeds.