DeepFlu: a deep learning approach for forecasting symptomatic influenza A infection based on pre-exposure gene expression.

Journal: Computer methods and programs in biomedicine
PMID: 34798406

Abstract

BACKGROUND AND OBJECTIVE: Not everyone gets sick after an exposure to influenza A viruses (IAV). Although KLRD1 has been identified as a potential biomarker for influenza susceptibility, it remains unclear whether forecasting symptomatic flu infection based on pre-exposure host gene expression might be possible.

Authors

  • Anna Zan
    Computational Biology Laboratory, Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung Taiwan, ROC.
  • Zhong-Ru Xie
    Department of Systems and Computational Biology, Albert Einstein College of Medicine, Yeshiva University, 1300 Morris Park Avenue, Bronx, NY, 10461, USA.
  • Yi-Chen Hsu
    Computational Biology Laboratory, Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung Taiwan, ROC.
  • Yu-Hao Chen
    Jinling Clinical Medical College, Nanjing Medical University，Nanjing，Jiangsu 210002，China.
  • Tsung-Hsien Lin
    Division of Cardiology, Department of Internal Medicine, Kaohsiung Medical University Hospital; ; Department of Internal Medicine, Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
  • Yong-Shan Chang
    Computational Biology Laboratory, Department of Computer Science & Engineering, National Taiwan Ocean University, Keelung Taiwan, ROC.
  • Kuan Y Chang
    Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung 202, Taiwan.

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