Machine learning based identification potential feature genes for prediction of drug efficacy in nonalcoholic steatohepatitis animal model.

Journal: Lipids in health and disease
PMID:

Abstract

BACKGROUND: Nonalcoholic Steatohepatitis (NASH) results from complex liver conditions involving metabolic, inflammatory, and fibrogenic processes. Despite its burden, there has been a lack of any approved food-and-drug administration therapy up till now.

Authors

  • Marwa Matboli
    Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • Ibrahim Abdelbaky
    Department of Electronics and Information Engineering, Jeonbuk National University, Jeonju, 54896, South Korea.
  • Abdelrahman Khaled
    Bioinformatics Group, Center of Informatics Sciences (CIS), School of Information Technology and Computer Sciences, Nile University, Giza, Egypt.
  • Radwa Khaled
    Biotechnology/Biomolecular Chemistry Department, Faculty of Science, Cairo University, Cairo, Egypt.
  • Shaimaa Hamady
    Faculty of Science, Ain Shams University, Cairo, Egypt.
  • Laila M Farid
    Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • Mariam B Abouelkhair
    Pathology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • Noha E El-Attar
    Information Systems Department, Faculty of Computers and Artificial Intelligence, Banha University, Banha, Egypt. noha.ezzat@fci.bu.edu.eg.
  • Mohamed Farag Fathallah
    Medical Pathology Department, Faculty of Medicine, Cairo University, Cairo, Egypt.
  • Manal S Abd El Hamid
    Medical Physiology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.
  • Gena M Elmakromy
    Endocrinology & Diabetes Mellitus Unit, Department of Internal Medicine, Badr University in Cairo, Badr City, Egypt.
  • Marwa Ali
    Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt.