Unbiaseddti: mitigating real-world bias of drug-target interaction prediction by using deep ensemble-balanced learning

HIGHLIGHTS

• who: Aida Tayebi et al. from the Department of Industrial Engineering and Management Systems, University of Central Florida, College of Medicine, Bionix Cluster, University of Central Florida, Orlando, FL, USA have published the article: UnbiasedDTI: Mitigating Real-World Bias of Drug-Target Interaction Prediction by Using Deep Ensemble-Balanced Learning, in the Journal: Molecules 2022, 27, 2980. of /2022/
• what: The authors propose a computational framework along with experimental validations to predict drug-target interaction using an ensemble of deep learning models to address the class imbalance problem in the DTI domain. The aim of . . .
  

   

  

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