ASIAN: a web server for inferring a regulatory network framework from gene expression profiles
ASIAN: a web server for inferring a regulatory network framework from gene expression profiles
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DOI：
10.1093/nar/gki446
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发表时间：
2005-07-01
影响因子：
14.9
通讯作者：
Horimoto, K
中科院分区：
文献类型：
--
作者：
Aburatani, S;Goto, K;Horimoto, K
基因表达谱分析中鉴定基因功能的标准工作流程是通过各种度量和技术进行聚类，以及随后的分析，例如上游区域的序列分析。另一个具有挑战性的分析是基因调控网络的推断，一些计算方法已经被集中开发来推断基因调控网络。在这里，我们描述了我们的Web服务器，用于从大量的基因表达谱推断调控网络的框架，基于图形高斯建模（GGM）结合层次聚类（http：//eureka.ims.u-tokyo.ac.jp/asian）。GGM基于一个简单的数学结构，即计算变量之间的相关系数矩阵的倒数，因此，我们的服务器可以在合理的计算时间内分析各种数据。该服务器允许用户输入表达谱，并通过几种层次聚类技术输出基因的树状图，通过层次聚类的停止规则估计聚类数，并通过GGM输出聚类之间的网络，并具有相应的图形表示。因此，ASIAN（推理网络的自动系统）网络服务器提供了用于推断调控关系的初始基础，因为聚类作为识别基因功能的第一步。
The standard workflow in gene expression profile analysis to identify gene function is the clustering by various metrics and techniques, and the following analyses, such as sequence analyses of upstream regions. A further challenging analysis is the inference of a gene regulatory network, and some computational methods have been intensively developed to deduce the gene regulatory network. Here, we describe our web server for inferring a framework of regulatory networks from a large number of gene expression profiles, based on graphical Gaussian modeling (GGM) in combination with hierarchical clustering (http://eureka.ims.u-tokyo.ac.jp/asian). GGM is based on a simple mathematical structure, which is the calculation of the inverse of the correlation coefficient matrix between variables, and therefore, our server can analyze a wide variety of data within a reasonable computational time. The server allows users to input the expression profiles, and it outputs the dendrogram of genes by several hierarchical clustering techniques, the cluster number estimated by a stopping rule for hierarchical clustering and the network between the clusters by GGM, with the respective graphical presentations. Thus, the ASIAN ( Automatic System for Inferring A Network) web server provides an initial basis for inferring regulatory relationships, in that the clustering serves as the first step toward identifying the gene function.