Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action
Large-scale integration of heterogeneous pharmacogenomic data for identifying drug mechanism of action
复制标题
大规模整合异质药物基因组数据以识别药物作用机制
DOI：
10.1142/9789813235533_0005
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发表时间：
2018
期刊：
影响因子：
--
通讯作者：
Peng, Jian
中科院分区：
文献类型：
--
作者：
Luo, Yunan;Wang, Sheng;Xiao, Jinfeng;Peng, Jian
各种大规模的药物基因组数据，如扰动实验和敏感性图谱，使系统地识别药物作用机制(MOAS)成为可能，这是精准医学时代的一项关键任务。然而，由于这些数据集的野生异质性、高维性和噪声性质，整合这些互补的药物基因组数据集本身就具有挑战性。在这项工作中，我们开发了Mania，一种用于大规模药物基因组数据的可扩展集成的新方法。MANIA首先通过集成包括药物敏感性、药物化学结构和扰动分析在内的多个异质数据源，构建药物-药物相似度网络。然后，它学习每种药物的紧凑载体表示，以同时编码其结构和药物基因组学特性。大量的实验表明，与基于单个数据源的预测和最先进的综合方法相比，MANIA在MOAS和目标预测方面都有显著的改进。此外，Mania发现了针对频繁突变的癌症基因的药物，这为药物的再利用提供了新的见解。
A variety of large-scale pharmacogenomic data, such as perturbation experiments and sensitivity profiles, enable the systematical identification of drug mechanism of actions (MoAs), which is a crucial task in the era of precision medicine. However, integrating these complementary pharmacogenomic datasets is inherently challenging due to the wild heterogeneity, high-dimensionality and noisy nature of these datasets. In this work, we develop Mania, a novel method for the scalable integration of large-scale pharmacogenomic data. Mania first constructs a drug-drug similarity network through integrating multiple heterogeneous data sources, including drug sensitivity, drug chemical structure, and perturbation assays. It then learns a compact vector representation for each drug to simultaneously encode its structural and pharmacogenomic properties. Extensive experiments demonstrate that Mania achieves substantially improved performance in both MoAs and targets prediction, compared to predictions based on individual data sources as well as a state-of-the-art integrative method. Moreover, Mania identifies drugs that target frequently mutated cancer genes, which provides novel insights into drug repurposing.
DOI：
10.1142/9789814583220_0015
发表时间：
2013-11
影响因子：
--
作者：
Fan Yang;Jinbo Xu;Jianyang Zeng
通讯作者：
Fan Yang;Jinbo Xu;Jianyang Zeng