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Deep Learning Techniques and Covid-19 Drug Discovery: Fundamentals, State-Of-The-Art and Future Directions Publisher



Jamshidi MB1, 2 ; Lalbakhsh A3 ; Talla J1, 2 ; Peroutka Z1, 2 ; Roshani S4 ; Matousek V5 ; Roshani S4 ; Mirmozafari M6 ; Malek Z7 ; La Spada L8 ; Sabet A9 ; Dehghani M10 ; Jamshidi M11 ; Honari MM12 Show All Authors
Authors
  1. Jamshidi MB1, 2
  2. Lalbakhsh A3
  3. Talla J1, 2
  4. Peroutka Z1, 2
  5. Roshani S4
  6. Matousek V5
  7. Roshani S4
  8. Mirmozafari M6
  9. Malek Z7
  10. La Spada L8
  11. Sabet A9
  12. Dehghani M10
  13. Jamshidi M11
  14. Honari MM12
  15. Hadjilooei F13
  16. Jamshidi A14
  17. Lalbakhsh P15
  18. Hashemidezaki H1
  19. Ahmadi S16
  20. Lotfi S17
Show Affiliations
Authors Affiliations
  1. 1. Research and Innovation Centre for Electrical Engineering (RICE), University of West Bohemia, Pilsen, 301 00, Czech Republic
  2. 2. Department of Power Electronics And Machines (KEV), University of West Bohemia, Pilsen, 301 00, Czech Republic
  3. 3. School of Engineering, Macquarie University, Sydney, 2109, NSW, Australia
  4. 4. Department of Electrical Engineering, Islamic Azad University, Kermanshah Branch, Kermanshah, 1477893855, Iran
  5. 5. Department of Computer Science and Engineering (KIV), University of West Bohemia, Pilsen, 301 00, Czech Republic
  6. 6. Department of Electrical and Computer Engineering, University of Wisconsin–Madison, Madison, 53706, WI, United States
  7. 7. Medical Sciences Research Center, Faculty of Medicine, Tehran Medical Sciences Branch, IAU, Tehran, 1477893855, Iran
  8. 8. School of Engineering and the Built Environment, Edinburgh Napier University, Edinburgh, EH11 4DY, United Kingdom
  9. 9. Department of Pharmacy, Irma Lerma Rangel College of Pharmacy, Texas A&M University, Kingsville, 78363, TX, United States
  10. 10. Department of Physics and Astronomy, Louisiana State University, Baton Rouge, 70803, LA, United States
  11. 11. Young Researchers and Elite Club, Islamic Azad University, Kermanshah Branch, Kermanshah, 1477893855, Iran
  12. 12. Electrical and Mechanical Engineering Department, University of Alberta, Edmonton, T6G1H9, AB, Canada
  13. 13. Department of Radiation Oncology, Cancer Institute, Tehran University of Medical Sciences, Tehran, 1416753955, Iran
  14. 14. Dentistry School, Babol University of Medical Sciences, Babol, 4717647745, Iran
  15. 15. Department of English Language and Literature, Razi University, Kermanshah, 6714414971, Iran
  16. 16. Department of Technologies and Measurement (KET), University of West Bohemia, Pilsen, 301 00, Czech Republic
  17. 17. Department of Theoretical Electrical Engineering (KTE), University of West Bohemia, Pilsen, 301 00, Czech Republic

Source: Studies in Systems# Decision and Control Published:2021


Abstract

The world is in a frustrating situation, which is exacerbating due to the time-consuming process of the COVID-19 vaccine design and production. This chapter provides a comprehensive investigation of fundamentals, state-of-the-art and some perspectives to speed up the process of the design, optimization and production of the medicine for COVID-19 based on Deep Learning (DL) methods. The proposed platforms are able to be used as predictors to forecast antigens during the infection disregarding their abundance and immunogenicity with no requirement of growing the pathogen in vitro. First, we briefly survey the latest achievements and fundamentals of some DL methodologies, including Deep Boltzmann Machines (DBM), Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Hopfield network and Long Short-Term Memory(LSTM). These techniques help us to reach an integrated approach for drug development by non-conventional antigens. We then propose several DL-based platforms to utilize for future applications regarding the latest publications and medical reports. Considering the evolving date on COVID-19 and its ever-changing nature, we believe this survey can give readers some useful ideas and directions to understand the application of Artificial Intelligence (AI) to accelerate the vaccine design not only for COVID-19 but also for many different diseases or viruses. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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