New Computational Tool Based on Machine-learning Algorithms for the Identification of Rhinovirus Infection-Related Genes.

Journal: Combinatorial chemistry & high throughput screening
PMID: 31782358

Abstract

BACKGROUND: Human rhinovirus has different identified serotypes and is the most common cause of cold in humans. To date, many genes have been discovered to be related to rhinovirus infection. However, the pathogenic mechanism of rhinovirus is difficult to elucidate through experimental approaches due to the high cost and consuming time.

Authors

  • Yan Xu
    Department of Nephrology, Suzhou Ninth People's Hospital, Suzhou Ninth Hospital Affiliated to Soochow University, Suzhou, China.
  • Yu-Hang Zhang
    Institute of Health Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, China.
  • Jiarui Li
    CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, 200031, China.
  • Xiao Y Pan
    BASF & IDLab, Ghent University, Ghent, Belgium.
  • Tao Huang
    The Second Clinical Medical College of Guangzhou University of Chinese Medicine, Guangzhou, China.
  • Yu-Dong Cai
    College of Life Science, Shanghai University, Shanghai, People's Republic of China.

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