ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization.

ArrayMining: a modular web-application for microarray analysis combining ensemble and consensus methods with cross-study normalization.
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DOI:
10.1186/1471-2105-10-358
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发表时间:
2009-10-28
期刊:
影响因子:
3
通讯作者:
Krasnogor N
Krasnogor N
中科院分区:
生物学4区
文献类型:
--
作者:
Glaab E;Garibaldi JM;Krasnogor N

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DNA微阵列数据的统计分析为研究疾病的遗传成分提供了宝贵的诊断工具。为了利用大量可用的数据集和分析方法,最好将不同的算法和来自不同研究的数据结合起来。为此目的在几乎完全自动化的过程中应用集合学习、共识聚类和交叉研究标准化方法,并在单一界面下将不同的分析模块连接在一起,将简化许多微阵列分析任务。我们介绍了ArrayMining.net,这是一个用于微阵列分析的网络应用程序,它提供了对特征选择、聚类、预测、基因集分析和交叉研究归一化方法的广泛选择。与其他与微阵列相关的网络工具不同,一项分析任务的多个算法和数据集可以使用集合特征选择、集合预测、共识聚类和跨平台数据集成来组合。通过以模块化方式连接不同的分析工具,新的探索路线成为可能,例如,使用从基因集分析获得的特征和来自多项研究的数据进行整体样本分类。通过自动参数选择机制以及与网络工具和数据库的链接,进一步简化了分析,以进行功能注释和文献挖掘。ArrayMining.net是一个用于微阵列分析的免费网络应用程序,结合了基于集合和共识方法的广泛算法选择,使用自动参数选择并与注释数据库集成。
Statistical analysis of DNA microarray data provides a valuable diagnostic tool for the investigation of genetic components of diseases. To take advantage of the multitude of available data sets and analysis methods, it is desirable to combine both different algorithms and data from different studies. Applying ensemble learning, consensus clustering and cross-study normalization methods for this purpose in an almost fully automated process and linking different analysis modules together under a single interface would simplify many microarray analysis tasks. We present ArrayMining.net, a web-application for microarray analysis that provides easy access to a wide choice of feature selection, clustering, prediction, gene set analysis and cross-study normalization methods. In contrast to other microarray-related web-tools, multiple algorithms and data sets for an analysis task can be combined using ensemble feature selection, ensemble prediction, consensus clustering and cross-platform data integration. By interlinking different analysis tools in a modular fashion, new exploratory routes become available, e.g. ensemble sample classification using features obtained from a gene set analysis and data from multiple studies. The analysis is further simplified by automatic parameter selection mechanisms and linkage to web tools and databases for functional annotation and literature mining. ArrayMining.net is a free web-application for microarray analysis combining a broad choice of algorithms based on ensemble and consensus methods, using automatic parameter selection and integration with annotation databases.
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