ReSimNet: drug response similarity prediction using Siamese neural networks.

Journal: Bioinformatics (Oxford, England)
Published Date:

Abstract

MOTIVATION: Traditional drug discovery approaches identify a target for a disease and find a compound that binds to the target. In this approach, structures of compounds are considered as the most important features because it is assumed that similar structures will bind to the same target. Therefore, structural analogs of the drugs that bind to the target are selected as drug candidates. However, even though compounds are not structural analogs, they may achieve the desired response. A new drug discovery method based on drug response, which can complement the structure-based methods, is needed.

Authors

  • Minji Jeon
    Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea.
  • Donghyeon Park
    Department of Computer Science and Engineering, Korea University, Seoul 02841, South Korea.
  • Jinhyuk Lee
    Department of Computer Science and Engineering, Korea University, Seoul, 02841, Republic of Korea.
  • Hwisang Jeon
    Interdisciplinary Graduate Program in Bioinformatics, Korea University, Seoul 02841, South Korea.
  • Miyoung Ko
    Department of Computer Science and Engineering, Korea University, Seoul 02841, South Korea.
  • Sunkyu Kim
    Department of Computer Science and Engineering, Korea University, Seoul 02841, South Korea.
  • Yonghwa Choi
    Department of Computer Science and Engineering, Korea University, Seoul 02841, Korea.
  • Aik-Choon Tan
    Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, Aurora, CO 12801, USA.
  • Jaewoo Kang
    Department of Computer Science and Engineering, Korea University, Seoul, Republic of Korea.