Artificial intelligence to guide precision anticancer therapy with multitargeted kinase inhibitors.

Journal: BMC cancer
Published Date: Nov 24, 2022

Abstract

BACKGROUND: Vast amounts of rapidly accumulating biological data related to cancer and a remarkable progress in the field of artificial intelligence (AI) have paved the way for precision oncology. Our recent contribution to this area of research is CancerOmicsNet, an AI-based system to predict the therapeutic effects of multitargeted kinase inhibitors across various cancers. This approach was previously demonstrated to outperform other deep learning methods, graph kernel models, molecular docking, and drug binding pocket matching.

Authors

  • Manali Singha
    Department of Biological Sciences, Louisiana State University, Baton Rouge, LA 70803, USA.
  • Limeng Pu
    Division of Electrical & Computer Engineering, Louisiana State University, Baton Rouge, LA, 70803, USA.
  • Brent A Stanfield
    Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
  • Ifeanyi K Uche
    Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
  • Paul J F Rider
    Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
  • Konstantin G Kousoulas
    Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA, 70803, USA.
  • J Ramanujam
    Division of Electrical and Computer Engineering, Louisiana State University, Baton Rouge, LA 70803, USA.
  • Michal Brylinski
    Department of Biological Sciences, Louisiana State University, Baton Rouge, LA, United States.

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