Cong Liu

Qimai improves DNA-protein interaction prediction for unseen proteins by integrating deep learning with LLM-based reasoning, achieving higher AUC-PR, AUC-ROC, and MCC than standalone models.

TUnA is a Transformer model that predicts protein-protein interactions from sequence data and provides uncertainty estimates for unseen sequences, improving reliability.

The paper predicts somatic mutation rates in 13 cancers using DNA motifs and identifies impactful motifs and cancer-specific regions for classification.

The paper identifies key transcription factors in immune cell specification using integrated transcriptomic and epigenomic data across mouse and human cell types.