DeePathNet: A Transformer-Based Deep Learning Model Integrating Multiomic Data with Cancer Pathways.

Journal: Cancer research communications
Published Date: Dec 1, 2024

Abstract

DeePathNet integrates cancer-specific biological pathways using transformer-based deep learning for enhanced cancer analysis. It outperforms existing models in predicting drug responses, cancer types, and subtypes. By enabling pathway-level biomarker discovery, DeePathNet represents a significant advancement in cancer research and could lead to more effective treatments.

Authors

  • Zhaoxiang Cai
    ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
  • Rebecca C Poulos
    ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia.
  • Adel Aref
    ProCan, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, Australia.
  • Phillip J Robinson
    ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
  • Roger R Reddel
    ProCan®, Children's Medical Research Institute, Faculty of Medicine and Health, The University of Sydney, Westmead, NSW, Australia.
  • Qing Zhong

Keywords

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