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网络生物标志物揭示疾病进展过程中基因调控的功能障碍。

Network biomarkers reveal dysfunctional gene regulations during disease progression.

机构信息

Key Laboratory of Systems Biology, SIBS-Novo Nordisk Translational Research Centre for PreDiabetes, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.

出版信息

FEBS J. 2013 Nov;280(22):5682-95. doi: 10.1111/febs.12536. Epub 2013 Oct 22.

Abstract

Extensive studies have been conducted on gene biomarkers by exploring the increasingly accumulated gene expression and sequence data generated from high-throughput technology. Here, we briefly report on the state-of-the-art research and application of biomarkers from single genes (i.e. gene biomarkers) to gene sets (i.e. group or set biomarkers), gene networks (i.e. network biomarkers) and dynamical gene networks (i.e. dynamical network biomarkers). In particular, differential and dynamical network biomarkers are used as representative examples to demonstrate their effectiveness in both detecting early signals for complex diseases and revealing essential mechanisms on disease initiation and progression at a network level.

摘要

通过探索高通量技术产生的日益积累的基因表达和序列数据,对基因生物标志物进行了广泛的研究。在这里,我们简要报告了从单个基因(即基因生物标志物)到基因集(即组或集生物标志物)、基因网络(即网络生物标志物)和动态基因网络(即动态网络生物标志物)的生物标志物的最新研究和应用。特别是,差异和动态网络生物标志物被用作代表性示例,以证明它们在检测复杂疾病的早期信号和揭示疾病发生和进展的网络水平的基本机制方面的有效性。

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