DeepAffinity: interpretable deep learning of compound–protein affinity through unified recurrent and convolutional neural networks

Abstract

Drug discovery demands rapid quantification of compound–protein interaction (CPI). However, there is a lack of methods that can predict compound–protein affinity from sequences alone with high applicability, accuracy and interpretability.

Document Details

Document Type
Pub Defense Publication
Publication Date
Feb 15, 2019
Source ID
10.1093/bioinformatics/btz111

Entities

People

  • Di Wu
  • Mostafa Karimi
  • Yang Shen
  • Zhangyang Wang

Organizations

  • Defense Advanced Research Projects Agency
  • National Institute of General Medical Sciences
  • National Institutes of Health
  • Texas A&M University

Tags

Fields of Study

  • Computer science

Readers

  • Molecular and Cellular Biochemistry
  • Neural Network Machine Learning.

Technology Areas

  • AI & ML
  • AI & ML - Neural Networks