AttDRP: Attention Mechanism-based Model for Anti-Cancer Drug Response Prediction 


Vol. 48,  No. 6, pp. 713-722, Jun.  2021
10.5626/JOK.2021.48.6.713


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  Abstract

Resistance to anti-cancer drugs makes chemotherapy ineffective for cancer patients. Drug resistance is caused by genetic alterations in cancer cells. Many studies have investigated drug responses of diverse cancer cell lines to various anti-cancer drugs to understand drug response mechanisms. Existing studies have proposed machine learning models for drug response prediction to find effective anti-cancer drugs. However, currently there are no models to learn the relationship between anticancer drugs and genes to improve the prediction accuracy. In this paper, we proposed a predictive model AttDRP that could identify important genes associated with anti-cancer drugs and predict drug responses based on identified genes. AttDRP exhibited better predictive accuracy than existing models and we found that the attention scores of AttDRP could be effective tools to analyze molecular structures of anticancer drugs. We hope that our proposed method would contribute to the development of precision medicine for effective chemotherapy. Resistance to anti-cancer drugs makes chemotherapy ineffective for cancer patients. Drug resistance is caused by genetic alterations in cancer cells. Many studies have investigated drug responses of diverse cancer cell lines to various anti-cancer drugs to understand drug response mechanisms. Existing studies have proposed machine learning models for drug response prediction to find effective anti-cancer drugs. However, currently there are no models to learn the relationship between anticancer drugs and genes to improve the prediction accuracy. In this paper, we proposed a predictive model AttDRP that could identify important genes associated with anti-cancer drugs and predict drug responses based on identified genes. AttDRP exhibited better predictive accuracy than existing models and we found that the attention scores of AttDRP could be effective tools to analyze molecular structures of anticancer drugs.


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  Cite this article

[IEEE Style]

J. Choi, S. Seo, S. Park, "AttDRP: Attention Mechanism-based Model for Anti-Cancer Drug Response Prediction," Journal of KIISE, JOK, vol. 48, no. 6, pp. 713-722, 2021. DOI: 10.5626/JOK.2021.48.6.713.


[ACM Style]

Jonghwan Choi, Sangmin Seo, and Sanghyun Park. 2021. AttDRP: Attention Mechanism-based Model for Anti-Cancer Drug Response Prediction. Journal of KIISE, JOK, 48, 6, (2021), 713-722. DOI: 10.5626/JOK.2021.48.6.713.


[KCI Style]

최종환, 서상민, 박상현, "AttDRP: 주의집중 메커니즘 기반의 항암제 약물 반응성 예측 모델," 한국정보과학회 논문지, 제48권, 제6호, 713~722쪽, 2021. DOI: 10.5626/JOK.2021.48.6.713.


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