[1]毛玉杰,魏东,李玉双.采用偏最小二乘法的基因-药物共模块识别[J].华侨大学学报(自然科学版),2020,41(1):121-125.[doi:10.11830/ISSN.1000-5013.201903012]
　MAO Yujie,WEI Dong,LI Yushuang.Identify Gene-Drug Co-Modules by Partial Least Square Method[J].Journal of Huaqiao University(Natural Science),2020,41(1):121-125.[doi:10.11830/ISSN.1000-5013.201903012]
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采用偏最小二乘法的基因-药物共模块识别()
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《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第41卷
期数:
2020年第1期
页码:
121-125
栏目:
出版日期:
2020-01-20

文章信息/Info

Title:
Identify Gene-Drug Co-Modules by Partial Least Square Method
文章编号:
1000-5013(2020)01-0121-05
作者:
毛玉杰1;  魏东1; 2;  李玉双1
1. 燕山大学 理学院, 河北 秦皇岛 066004;2. 河北数港科技有限公司, 河北 秦皇岛 066004
Author(s):
MAO Yujie1;  WEI Dong1; 2;  LI Yushuang1
1. School of Science, Yanshan University, Qinhuangdao 066004, China; 2. Hebei Dataport Technology Limited Company, Qinhuangdao 066004, China
关键词:
偏最小二乘算法;  药物关联网络;  基因模块;  药物模块;  基因-药物共模块
Keywords:
partial least square algorithm;  drug association network;  gene module;  drug module;  gene-drug co-module
分类号:
Q332
DOI:
10.11830/ISSN.1000-5013.201903012
文献标志码:
A
摘要:
首先,将药物二维化学结构转化为数值序列,计算药物之间的皮尔逊相关系数,进而构建药物关联网络;然后,在带有基因网络约束的稀疏偏最小二乘算法的基础上,加入药物关联网络信息,提出伴有基因和药物关联网络正则约束的稀疏偏最小二乘(SGDPLS)算法;最后,将SGDPLS算法应用于基因-药物共模块识别.结果表明:药物关联网络信息的加入能够有效提高所识别的共模块中基因模块与药物模块的相关性,增加共模块的生物可解释性.
Abstract:
First, we transform the two-dimensional chemical structures of drugs into digital sequences, calculate the Pearson correlation coefficients between drugs, and then construct a drug association network. Next, we incorporate the information from drug association network into sparse partial least square algorithm with gene network, and presente the sparse partial least square algorithm with gene and drug association networks(SGDPLS)algorithm. Finally, we apply SGDPLS algorithm to identify gene-drug co-modules. The result shows that, the addition of drug association network can improve the correlations between the gene modules and drug modules identified from the common module, and enhance the interpretability of the modules.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2019-03-06
通信作者: 李玉双(1980-),女,教授,博士,主要从事生物数学的研究.E-mail:yushuangli@ysu.edu.cn.
基金项目: 国家自然科学基金资助项目(61807029)
更新日期/Last Update: 2020-01-20