The model architecture and training procedure of Enhancer-MDLF. (A) Enhancer-MDLF comprises a dna2vec module predominantly composed of convolutional layers and a motif module primarily consisting of Dense layers. It takes dna2vec and motif frequency, the two sequence encoding results, as inputs. The fused features are derived by concatenating after feature extraction and subsequently passed through a sigmoid function for enhancer detection. (B) The training procedure of the Enhancer-MDLF framework. The process involves iterations through the training set five times to iteratively refine the predictive model. Subsequently, this model undergoes testing on the test set to yield the final prediction results.