基于矩阵分解技术的显著基因提取及基因表达数据分析
发布时间：2019-07-08 21:24
【摘要】：基因之间存在多种多样的表达调控活动,一般认为这些调控关系隐含在基因表达谱中。因此,可以根据基因表达数据对基因调控状态进行建模,以挖掘具有生物学意义的信息及隐含在其中的基因调控关系。本文分别利用独立成分分析(ICA)和非负矩阵分解(NMF)这两种无监督矩阵分解技术对阿尔茨海默病(AD)基因表达数据进行显著基因提取及基因调控网络的构建,通过生物学分析,探讨了两种不同矩阵分解技术在挖掘潜在致病基因上的作用,通过结合两种方法所提取的显著基因的生物学分析,体现了炎症反应在AD致病机制中的重要作用,为AD早期诊断、致病机制研究及基因生物标志物的探寻提供了有益的方法。
[Abstract]:There are a variety of expression and control activities among the genes, which are generally thought to be implied in the gene expression profile. Therefore, the gene regulation state can be modeled according to the gene expression data, so that the information with the biological meaning and the gene regulation relation hidden therein can be excavated. In this paper, two non-supervised matrix decomposition techniques of independent component analysis (ICA) and non-negative matrix decomposition (NMF) were used to study the expression data of Alzheimer's disease (AD) gene. The effects of two different matrix decomposition techniques on the potential pathogenic genes are discussed, and the important role of the inflammatory reaction in the pathogenesis of AD is shown by the biological analysis of the significant genes extracted by combining the two methods, which is the early diagnosis of AD. The research of pathogenic mechanism and the search of genetic biomarkers provide a useful method.
【作者单位】： 上海海事大学信息工程学院;美国罗文大学医药研究中心;
【基金】：国家自然科学基金资助项目(61271446) 上海市科委青年科技启明星计划(A类)资助项目(11QA1402900) 上海市教委科研创新项目资助(11YZ141)
【分类号】：R749.16
，
本文编号：2511888
[Abstract]:There are a variety of expression and control activities among the genes, which are generally thought to be implied in the gene expression profile. Therefore, the gene regulation state can be modeled according to the gene expression data, so that the information with the biological meaning and the gene regulation relation hidden therein can be excavated. In this paper, two non-supervised matrix decomposition techniques of independent component analysis (ICA) and non-negative matrix decomposition (NMF) were used to study the expression data of Alzheimer's disease (AD) gene. The effects of two different matrix decomposition techniques on the potential pathogenic genes are discussed, and the important role of the inflammatory reaction in the pathogenesis of AD is shown by the biological analysis of the significant genes extracted by combining the two methods, which is the early diagnosis of AD. The research of pathogenic mechanism and the search of genetic biomarkers provide a useful method.
【作者单位】： 上海海事大学信息工程学院;美国罗文大学医药研究中心;
【基金】：国家自然科学基金资助项目(61271446) 上海市科委青年科技启明星计划(A类)资助项目(11QA1402900) 上海市教委科研创新项目资助(11YZ141)
【分类号】：R749.16
，
本文编号：2511888
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