ModCRE-NN: Interpretable Deep Learning Harnesses Structural and Evolutionary Synergy to Predict Transcription Factor Binding Specificity (opens in new tab)

We present ModCRE-NN, a machine-learning framework and server for predicting transcription-factor (TF) DNA-binding motifs through the integration of structural and evolutionary information. The method combines structure-derived Position Weight Matrices (PWMs) together with PWMs of homologous spanning multiple evolutionary sequence-identity intervals, which are integrated into a unified 20-channel tensor representation. Benchmark datasets were constructed on experimental databases of TF motifs...