药物反应预测的多头图注意

P. Selvi Rajendran, M. Sivannarayna
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引用次数: 0

摘要

精准医疗的基础是根据病人的基因特征、生活方式和环境因素来治疗疾病。这种方法提高了临床试验的成功率,加快了药品监管审批的速度。预测肿瘤对特定抗癌治疗的易感性是成功实施精准医学的关键。药物联合治疗已被证明是非常有效的癌症治疗降低耐药性,提高治疗效果。由于抗癌药物的数量不断增加,所有这些治疗组合的实验都变得昂贵和耗时。在癌细胞系上进行大规模药物反应测试可能有助于了解药物与癌细胞的反应方式。本研究提出一个多头图注意网络来进行药物反应预测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi Head Graph Attention for Drug Response Predicton
Precision medicine is based on curing diseases based on a patient's genetic profile, lifestyle, and environmental factors. This method improves clinical trial success rates and speed up drug regulatory approval. Predicting tumour vulnerability to specific anti-cancer therapy is critical for the successful implementation of precision medicine. Drug combinations have been shown to be very effective in cancer treatment to lower the drug resistance and improve the therapeutic effectiveness. The experiments carried out in all these therapeutic combinations have become expensive and time-consuming as a result of the increasing number of anti-cancer drugs. Large-scale drug response testing on cancer cell lines might help to understand the way drugs react with cancer cells. This study proposes a multi head graph attention network to perform drug response prediction.
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