GEPAS：一个用于微阵列基因表达数据分析的基于网络的资源。
GEPAS: A web-based resource for microarray gene expression data analysis.
作者信息
Herrero Javier, Al-Shahrour Fátima, Díaz-Uriarte Ramón, Mateos Alvaro, Vaquerizas Juan M, Santoyo Javier, Dopazo Joaquín
机构信息
Bioinformatics Unit, Centro Nacional de Investigaciones Oncológicas, c/Melchor Fernández Almagro 3, 28029, Madrid, Spain.
出版信息
Nucleic Acids Res. 2003 Jul 1;31(13):3461-7. doi: 10.1093/nar/gkg591.
Abstract
We present a web-based pipeline for microarray gene expression profile analysis, GEPAS, which stands for Gene Expression Profile Analysis Suite (http://gepas.bioinfo.cnio.es). GEPAS is composed of different interconnected modules which include tools for data pre-processing, two-conditions comparison, unsupervised and supervised clustering (which include some of the most popular methods as well as home made algorithms) and several tests for differential gene expression among different classes, continuous variables or survival analysis. A multiple purpose tool for data mining, based on Gene Ontology, is also linked to the tools, which constitutes a very convenient way of analysing clustering results. On-line tutorials are available from our main web server (http://bioinfo.cnio.es).
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本文引用的文献
1
Gene expression data preprocessing.基因表达数据预处理。
Bioinformatics. 2003 Mar 22;19(5):655-6. doi: 10.1093/bioinformatics/btg040.
2
Combining hierarchical clustering and self-organizing maps for exploratory analysis of gene expression patterns.结合层次聚类和自组织映射进行基因表达模式的探索性分析。
J Proteome Res. 2002 Sep-Oct;1(5):467-70. doi: 10.1021/pr025521v.
3
Microarray databases: standards and ontologies.微阵列数据库：标准与本体论。
Nat Genet. 2002 Dec;32 Suppl:469-73. doi: 10.1038/ng1028.
4
Identification of genes involved in resistance to interferon-alpha in cutaneous T-cell lymphoma.皮肤T细胞淋巴瘤中参与α-干扰素耐药相关基因的鉴定
Am J Pathol. 2002 Nov;161(5):1825-37. doi: 10.1016/s0002-9440(10)64459-8.
5
Use of keyword hierarchies to interpret gene expression patterns.使用关键词层次结构来解释基因表达模式。
Bioinformatics. 2001 Apr;17(4):319-26. doi: 10.1093/bioinformatics/17.4.319.
6
A hierarchical unsupervised growing neural network for clustering gene expression patterns.一种用于聚类基因表达模式的分层无监督生长神经网络。
Bioinformatics. 2001 Feb;17(2):126-36. doi: 10.1093/bioinformatics/17.2.126.
7
Support vector machine classification and validation of cancer tissue samples using microarray expression data.使用微阵列表达数据对癌组织样本进行支持向量机分类与验证。
Bioinformatics. 2000 Oct;16(10):906-14. doi: 10.1093/bioinformatics/16.10.906.
8
Gene expression data analysis.基因表达数据分析。
FEBS Lett. 2000 Aug 25;480(1):17-24. doi: 10.1016/s0014-5793(00)01772-5.
9
Gene ontology: tool for the unification of biology. The Gene Ontology Consortium.基因本体论：生物学统一工具。基因本体论联合会。
Nat Genet. 2000 May;25(1):25-9. doi: 10.1038/75556.
10
Knowledge-based analysis of microarray gene expression data by using support vector machines.利用支持向量机对微阵列基因表达数据进行基于知识的分析。
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