Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows.

Journal: STAR protocols
PMID: 34746868

Abstract

MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a).

Authors

  • Vijit Saini
    Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Narellan Road & Gilchrist Drive, Campbelltown, NSW 2560, Australia.
  • Mugdha V Joglekar
    Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Narellan Road & Gilchrist Drive, Campbelltown, NSW 2560, Australia.
  • Wilson K M Wong
    Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Narellan Road & Gilchrist Drive, Campbelltown, NSW 2560, Australia.
  • Guozhi Jiang
    Department of Medicine and Therapeutics, and Hong Kong Institute of Diabetes and Obesity, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, Special Administrative Region, China.
  • Najah T Nassif
    School of Life Sciences and the Centre for Health Technologies, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia.
  • Ann M Simpson
    School of Life Sciences and the Centre for Health Technologies, University of Technology Sydney, 15 Broadway, Ultimo, NSW 2007, Australia.
  • Ronald C W Ma
    Department of Medicine and Therapeutics, and Hong Kong Institute of Diabetes and Obesity, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, Special Administrative Region, China.
  • Louise T Dalgaard
    Department of Science and Environment, Roskilde University, Universitetsvej 1, 4000 Roskilde, Denmark.
  • Anandwardhan A Hardikar
    Diabetes and Islet Biology Group, School of Medicine, Western Sydney University, Narellan Road & Gilchrist Drive, Campbelltown, NSW 2560, Australia.

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