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Predicting Synergistic Drug Combinations Based on Fusion of Cell and Drug Molecular Structures

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成果类型:
期刊论文
作者:
Shiyu Yan*;Gang Yu;Jiaoxing Yang;Lingna Chen
通讯作者:
Shiyu Yan
作者机构:
[Shiyu Yan; Gang Yu; Lingna Chen] Computer School, University of South China, Hengyang, China
[Jiaoxing Yang] The First Affiliated Hospital, University of South China, Hengyang, China
通讯机构:
[Shiyu Yan] C
Computer School, University of South China, Hengyang, China
语种:
英文
关键词:
Deep Learning technique;Synergistic drug combination;Computational model;Feature extraction
期刊:
INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES
ISSN:
1913-2751
年:
2025
页码:
1-11
机构署名:
本校为第一且通讯机构
摘要:
Drug combination therapy has shown improved efficacy and decreased adverse effects, making it a practical approach for conditions like cancer. However, discovering all potential synergistic drug combinations requires extensive experimentation, which can be challenging. Recent research utilizing deep learning techniques has shown promise in reducing the number of experiments and overall workload by predicting synergistic drug combinations. Therefore, developing reliable and effective computational methods for predicting these combinations is essential. This paper proposed a novel method called ...

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