Insights into performance evaluation of compound-protein interaction prediction methods.

Journal: Bioinformatics (Oxford, England)
PMID: 36124806

Abstract

MOTIVATION: Machine-learning-based prediction of compound-protein interactions (CPIs) is important for drug design, screening and repurposing. Despite numerous recent publication with increasing methodological sophistication claiming consistent improvements in predictive accuracy, we have observed a number of fundamental issues in experiment design that produce overoptimistic estimates of model performance.

Authors

  • Adiba Yaseen
    Department of Computer and Information Science, Pakistan Institute of Engineering and Applied Science (PIEAS), Islamabad, Pakistan.
  • Imran Amin
    National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Pakistan.
  • Naeem Akhter
    Department of Computer and Information Sciences (DCIS), Pakistan Institute of Engineering and Applied Sciences (PIEAS), Islamabad 45650, Pakistan.
  • Asa Ben-Hur
    Department of Computer Science, Colorado State University, Fort Collins, Colorado, United States of America.
  • Fayyaz Minhas
    Department of Computer Science, University of Warwick, Coventry, UK.

Keywords

External Resources

Popular Topics
Recent Journals