Zihao Liu

SENT-DTI: Semantic-enhanced drug-target interaction prediction with negative training strategy

To mitigate the impact of false-negative associations caused by negative sampling of DPPs, the proposed SENT-DTI method is inspired by the advantage of negative training (NT) strategy on identification of false-negative samples and design a novel NT strategy that adaptively learns the probability distribution of known DPP features by incorporating a unified high-confidence false-negative association filtering mechanism into a negative loss objective function.