Predicting protein-protein interactions through sequence-based deep learning.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: High-throughput experimental techniques have produced a large amount of protein-protein interaction (PPI) data, but their coverage is still low and the PPI data is also very noisy. Computational prediction of PPIs can be used to discover new PPIs and identify errors in the experimental PPI data.

Authors

  • Somaye Hashemifar
    Toyota Technological Institute at Chicago, 6045 S. Kenwood Avenue, Chicago, IL 60637, USA.
  • Behnam Neyshabur
    Toyota Technological Institute at Chicago, Chicago, IL, USA.
  • Aly A Khan
    Toyota Technological Institute at Chicago, Chicago, IL, USA.
  • Jinbo Xu
    Toyota Technological Institute at Chicago, Chicago, IL 60615, USA.