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Bioinformatics Research on Drug Sensitivity Prediction

  • Yaojia Chen
  • , Liran Juan
  • , Xiao Lv*
  • , Lei Shi*
  • *Corresponding author for this work
  • University of Electronic Science and Technology of China
  • School of Life Science and Technology, Harbin Institute of Technology
  • Beidahuang Industry Group General Hospital
  • Naval Medical University

Research output: Contribution to journalReview articlepeer-review

Abstract

Modeling-based anti-cancer drug sensitivity prediction has been extensively studied in recent years. While most drug sensitivity prediction models only use gene expression data, the remarkable impacts of gene mutation, methylation, and copy number variation on drug sensitivity are neglected. Drug sensitivity prediction can both help protect patients from some adverse drug reactions and improve the efficacy of treatment. Genomics data are extremely useful for drug sensitivity prediction task. This article reviews the role of drug sensitivity prediction, describes a variety of methods for predicting drug sensitivity. Moreover, the research significance of drug sensitivity prediction, as well as existing problems are well discussed.

Original languageEnglish
Article number799712
JournalFrontiers in Pharmacology
Volume12
DOIs
StatePublished - 9 Dec 2021
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • anti-cancer
  • database
  • deep learning
  • drug sensitivity
  • machine learning

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