Harnessing machine learning technique to authenticate differentially expressed genes in oral squamous cell carcinoma.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology
PMID: 39505585

Abstract

OBJECTIVE: Advancements in early detection of the disease, prognosis and the development of therapeutic strategies necessitate tumor-specific biomarkers. Despite continuous efforts, no molecular marker has been proven to be an effective therapeutic tool for the early detection of cancer. The study aims to determine diagnostic and prognostic signature genes that may be involved in cancer pathology and hence, may serve as molecular markers.

Authors

  • Amisha Patel
    Department of Microbiology, School of Science, RK University, Rajkot, Gujarat 360020, India.
  • Saswati Mahapatra
    Department of Computer Application, Faculty of Technology, Siksha 'O' Anusandhan University, Bhubaneshwar, Odisha 751030, India.
  • Ashok Kumar Bishoyi
    Department of Microbiology, Faculty of Science, Marwadi University Research Center, Marwadi University, Rajkot, 360003, Gujarat, India.
  • Abhishek Sharma
    Department of Biotechnology and Bioengineering, Institute of Advanced Research, Koba Institutional Area, Gandhinagar, India.
  • Abhijit Makwana
    Shree Nathalal Parekh Cancer Institute, Rajkot Cancer Society, Rajkot, Gujarat 360003, India.
  • Tripti Swarnkar
    S'O'A Deemed to Be University, Bhubaneswar 751001, India.
  • Anubha Gupta
    SBILab, Deptt. of ECE, IIIT-Delhi, Delhi, India.
  • Prasan Kumar Sahoo
    Department of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan.
  • Sejal Shah
    Department of Bioinformatics, Faculty of Engineering and Technology, Marwadi University, Rajkot, Gujarat, 360003, India. Electronic address: sejal.shah@marwadieducation.edu.in.

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