基于网络成分分析的阿尔茨海默症靶基因动态表达研究

doi:10.3969/j.issn.0258-8021. 2013 0406

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Abstract Regulating the relationship between the analysis of transcription factors and target genes and building transcriptional regulatory networks are of great significance for the study of Alzheimer's disease (AD) pathogenesis, early diagnosis and pharmaceutical. Network component analysis (NCA) is a way to dynamically predict transcription factor activity and performance affect relations. According to a priori knowledge that transcription factor regulates multiple genes and induces the changes of gene expression, in this article 10 transcription factors were pretreated and 85 target genes were selected for network component analysis, and 162 of regulation relationship were used to build AD gene regulatory networks to form and show the dynamic regulation of relations and the role of transcription factor target genes. Dynamic prediction of transcription factor activity was varied significantly in line with the changes of its target genes regulating the pathological features of AD. For example, the expression values of the target gene NONO was increased from 3 126 to 4 508 in control with TF ANAPC5, but the expression values of the target gene YWHAZ was decreased from 6 000 to close to 0. The study provided a new insight and theoretical basis for The pathogenic mechanism and early diagnosis of AD.

Key words： Alzheimer’s disease nonnegative matrix factorization microarray gene expression data

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	KONG Wei^1*CUI Di Bo^1MOU Xiao Yang^2

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KONG Wei^1*CUI Di Bo^1MOU Xiao Yang^2. Using Network Component Analysis to Dissect Dynamic Expression of Gene and Network Structure in Alzheimer's Disease[J]. journal1, 2013, 32(4): 418-425.

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http://cjbme.csbme.org/EN/10.3969/j.issn.0258-8021. 2013 0406 OR http://cjbme.csbme.org/EN/Y2013/V32/I4/418

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