Software and code

Predicts TAD boundaries without Hi-C by integrating DNA sequences and epigenomic features.

A universal deep-learning architecture for cross-scale chromatin interaction prediction.

Transfer learning-based model for distinguishing super-enhancers from typical enhancers.

Interpretable transformer framework for enhancer-enhancer interaction prediction with cross-context transferability.

A two-step model for universal prediction of interactions between chromatin accessible regions.

A de novo open chromatin region prediction tool for plant genomes.