基于组织多层网络模型的药物重定位方法研究

计算药物重定位对于改善人类健康具有重要的意义，是一项极具挑战性和迫切需要解决的问题。药物刺激具有组织特异性的特征，可通过网络结构的变化进行有效刻画。因此，本项目拟从多组织出发，采用复杂网络模型，挖掘药物作用模块，设计药物重定位高效算法。本项目主要研究：（1）基于多层网络模型构建药物-组织特异性多层网络、分析多层网络拓扑结构特性；（2）利用张量理论、关联规则定义多层网络药物作用模块、设计高效的多层网络模块挖掘算法，分析多层网络模块与药物的关联关系；（3）基于多层网络模块构建药物相似性，通过集成表型、临床等多源数据，构建药物-疾病网络，实现多层网络条件下的药物重定位。该项目的实施为计算药物重定位研究提供新思路与新方法。

Computational drug repositioning or repurposing technique is of great significance for improving human health. It is a challenge and very urgent problem to be solved. Drug effect with tissue-specific features can be effectively depicted through the change of structural properties of the network. Therefore, this project intends to detect drug effect related modules and design effective algorithms for drug repositioning in multiple tissues system based on complex network model. The principal contents of this research project include: (1) We respectively construct drug related and tissue-specific networks based on multilayer network model, quantify the topological properties of these multilayer networks. (2) Based on tensor theory and association rules, drug modules of multilayer networks are defined and efficient and effective algorithms are developed to detect these modules from multilayer networks. Then we discuss the relationship between the drug effects and the modules. (3) The similarity between drug pairs is constructed by using the modules. Built on the integration of phenotype or clinical data, we construct drug-disease heterogeneous networks to reposition the existing drugs. The implementation of this project provides new ideas and new methods for the study of computational drug repositioning.