[1]张焕萍,王惠南,卢光明,等.基于互信息的差异共表达致病基因挖掘方法[J].东南大学学报(自然科学版),2009,39(1):151-155.[doi:10.3969/j.issn.1001-0505.2009.01.029]
 Zhang Huanping,Wang Huinan,Lu Guangming,et al.Finding differentially co-expressed disease-related genes based on mutual information[J].Journal of Southeast University (Natural Science Edition),2009,39(1):151-155.[doi:10.3969/j.issn.1001-0505.2009.01.029]
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基于互信息的差异共表达致病基因挖掘方法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
39
期数:
2009年第1期
页码:
151-155
栏目:
生物医学工程
出版日期:
2009-01-20

文章信息/Info

Title:
Finding differentially co-expressed disease-related genes based on mutual information
作者:
张焕萍1 王惠南1 卢光明2 钟元1 张志强2
1 南京航空航天大学生物医学工程系, 南京 210016; 2 南京军区南京总医院医学影像科, 南京 210002
Author(s):
Zhang Huanping1 Wang Huinan1 Lu Guangming2 Zhong Yuan1 Zhang Zhiqiang2
1 Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing210016, China
2 Department of Medical Imaging, Nanjing General Hospital of Nanjing Military Command, Nanjing 210002, China
关键词:
互信息 最大团 差异共表达致病基因
Keywords:
mutual information clique differentially co-expressed disease-related genes
分类号:
Q811.4
DOI:
10.3969/j.issn.1001-0505.2009.01.029
摘要:
为了挖掘基因表达数据中的差异共表达致病基因模块,提出了基于互信息和最大团相结合的方法.互信息用于度量基因表达谱之间的相互关系,计算任意2条基因表达谱在2种不同样本中的互信息值,得到2个互信息矩阵M11和M2,2选定2个阈值T11和T2(T1>T2)212将矩阵M11和M22二值化,并通过M11和M22中元素的逻辑运算得到图的邻接矩阵,从邻接矩阵挖掘出的最大团则为差异共表达致病基因模块.将该方法应用于Colon数据,选定T1=12.2,T2=21.0,得到6个相互重叠的最大团,实验结果表明,该方法能有效挖掘出差异共表达致病基因模块.
Abstract:
Mutual information combined with clique analysis method is introduced to identify differentially co-expressed disease-related genes at the level of biological modules from gene expression data. The mutual information is used to measure the co-expression relationships of gene data. Two square symmetric mutual information matrices M1and M2 are obtained by calculating the values of mutual information between each pair of genes in two different kinds of samples. Threshold values T11 and T2(T1>T2)212 are chosen respectively for the binarization of M11 and M2. The adjacency matrix of graph is obtained by logical operation “AND” of M11 and M22. The cliques detected from the adjacency matrix represent the differentially co-expressed disease-related gene modules. This method was applied to Colon microarray data with T1=2.2, T2=1.0, six overlapped cliques were detected. The results indicate that this method is very efficient in identifying differentially co-expressed disease-related gene modules from gene expression data.

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备注/Memo

备注/Memo:
作者简介: 张焕萍(1975—),女,博士生; 王惠南(联系人),男,教授,博士生导师,wanghn_nuaa@sina.com.
基金项目: 国家重点基础研究发展计划(973计划)资助项目(2006CB705707).
引文格式: 张焕萍,王惠南,卢光明,等.基于互信息的差异共表达致病基因挖掘方法[J].东南大学学报:自然科学版,2009,39(1):151-155.
更新日期/Last Update: 2009-01-20