Multifaceted protein-protein interaction prediction based on Siamese residual RCNN.

Journal: Bioinformatics (Oxford, England)
Published Date: Jul 15, 2019

Abstract

MOTIVATION: Sequence-based protein-protein interaction (PPI) prediction represents a fundamental computational biology problem. To address this problem, extensive research efforts have been made to extract predefined features from the sequences. Based on these features, statistical algorithms are learned to classify the PPIs. However, such explicit features are usually costly to extract, and typically have limited coverage on the PPI information.

Authors

  • Muhao Chen
    University of California, Davis, CA, USA.
  • Chelsea J-T Ju
    Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA.
  • Guangyu Zhou
    Department of Computer Science, University of California at Los Angeles, Los Angeles, CA 90095, USA.
  • Xuelu Chen
    Department of Computer Science, University of California, Los Angeles, Los Angeles, CA, USA.
  • Tianran Zhang
    Department of Bioengineering, University of California, Los Angeles, Los Angeles, CA, USA.
  • Kai-Wei Chang
    1 Department of Computer Science, University of California, Los Angeles, California.
  • Carlo Zaniolo
    University of California, Los Angeles.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.

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