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首页> 外文期刊>BMC Medical Informatics and Decision Making >Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data
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Discovering transnosological molecular basis of human brain diseases using biclustering analysis of integrated gene expression data

机译:利用整合基因表达数据的双聚类分析发现人脑疾病的变态学分子基础

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Background It has been reported that several brain diseases can be treated as transnosological manner implicating possible common molecular basis under those diseases. However, molecular level commonality among those brain diseases has been largely unexplored. Gene expression analyses of human brain have been used to find genes associated with brain diseases but most of those studies were restricted either to an individual disease or to a couple of diseases. In addition, identifying significant genes in such brain diseases mostly failed when it used typical methods depending on differentially expressed genes. Results In this study, we used a correlation-based biclustering approach to find coexpressed gene sets in five neurodegenerative diseases and three psychiatric disorders. By using biclustering analysis, we could efficiently and fairly identified various gene sets expressed specifically in both single and multiple brain diseases. We could find 4,307 gene sets correlatively expressed in multiple brain diseases and 3,409 gene sets exclusively specified in individual brain diseases. The function enrichment analysis of those gene sets showed many new possible functional bases as well as neurological processes that are common or specific for those eight diseases. Conclusions This study introduces possible common molecular bases for several brain diseases, which open the opportunity to clarify the transnosological perspective assumed in brain diseases. It also showed the advantages of correlation-based biclustering analysis and accompanying function enrichment analysis for gene expression data in this type of investigation.
机译:背景技术已经报道了几种脑部疾病可以被认为是超音波学方式,暗示了在这些疾病下可能的共同分子基础。但是,这些脑疾病之间在分子水平上的共性在很大程度上尚未得到开发。人类大脑的基因表达分析已被用于寻找与脑部疾病相关的基因,但其中大多数研究仅限于单个疾病或多种疾病。此外,当使用依赖于差异表达基因的典型方法时,在此类脑部疾病中鉴定重要基因的工作大多会失败。结果在这项研究中,我们使用了基于相关性的双聚类分析方法,以发现5种神经退行性疾病和3种精神疾病中的共表达基因集。通过使用双聚类分析,我们可以有效和公平地鉴定出在单个和多个脑部疾病中特异性表达的各种基因集。我们可以找到在多种脑疾病中相关表达的4,307个基因集,以及在个别脑疾病中专门指定的3,409个基因集。这些基因集的功能富集分析显示了这八种疾病共有或特有的许多新的可能的功能基础以及神经系统过程。结论这项研究介绍了几种脑疾病的可能的常见分子基础,这为阐明脑疾病假定的跨性别学观点提供了机会。在这种类型的研究中,它还显示了基于相关性的双聚类分析和伴随的功能丰富性分析对基因表达数据的优势。

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