权重基因共表达网络分析在生物医学中的应用

发布时间：2018-06-22 10:31

本文选题：权重基因共表达网络分析 + 高通量技术　；参考：《生物工程学报》2017年11期

【摘要】：高通量生物监测方法可以同时检测同一样本的上千个参数,其在生物医学中的应用越来越广泛,但如何系统地分析并从高通量数据中挖掘有用信息,仍是一项重要的课题。网络生物学的出现使人们对复杂生物系统有了更深刻的理解,组织/细胞功能执行具有模块化特点。目前,相关网络(Correlation network)被越来越多地应用于生物信息学,权重基因共表达网络分析(Weighted gene co-expression network analysis,WGCNA)是描述样品基因表达相关模式的一种系统生物学工具。在此,对WGCNA在疾病分型及预后、发病机制和其他相关领域研究进展作一个较为系统的综述。首先,对WGCNA的原理、分析流程和优势缺点进行总结。其次,介绍如何用WGCNA研究疾病、正常组织、药物、进化和基因组注释。最后,结合新高通量技术展望WGCNA应用新空间。以期科研工作者能够对WGCNA的应用有所了解。
[Abstract]:High-throughput biological monitoring method can detect thousands of parameters of the same sample at the same time, and its application in biomedicine is more and more extensive. However, how to systematically analyze and mine useful information from high-throughput data is still an important subject. The emergence of network biology makes people have a deeper understanding of complex biological systems, and the execution of tissue / cell functions has the characteristics of modularization. At present, correlation network is more and more used in bioinformatics. Weighted gene co-expression network analysis (WGCNA) is a systematic biological tool to describe the related patterns of gene expression in samples. In this paper, the progress of WGCNA in disease classification and prognosis, pathogenesis and other related fields is reviewed systematically. Firstly, the principle, analysis flow and advantages and disadvantages of WGCNA are summarized. Secondly, it introduces how to use WGCNA to study disease, normal tissue, medicine, evolution and genome annotation. Finally, the new space of WGCNA application is prospected with new high flux technology. It is expected that the researchers will be able to understand the application of WGCNA.
【作者单位】：福建农林大学生命科学学院;军事医学科学院卫生勤务与医学情报研究所;宁波市医疗中心李惠利医院消化内科;德州A&M健康医学中心;
【基金】：国家自然科学基金(No.81502091) 浙江省自然科学基金(No.LQ14H030001) 宁波市自然科学基金(No.2013A610232)资助~~
【分类号】：R318

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