Unsupervised pattern recognition: An introduction to the whys and wherefores of clustering microarray data
Unsupervised pattern recognition: An introduction to the whys and wherefores of clustering microarray data
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DOI：
10.1093/bib/6.4.331
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发表时间：
2005-12-01
影响因子：
9.5
通讯作者：
Okey, AB
中科院分区：
文献类型：
--
作者：
Boutros, PC;Okey, AB
聚类法已成为微阵列数据分析和解释的一个组成部分。聚类的算法基础--应用无监督的机器学习技术来识别数据集中固有的模式--已经建立得很好。本文讨论了这些技术的生物学动机和应用，以整合基因表达数据与其他生物信息，如功能注释、启动子数据和蛋白质组数据。
Clustering has become an integral part of microarray data analysis and interpretation. The algorithmic basis of clustering - the application of unsupervised machine-learning techniques to identify the patterns inherent in a data set - is well established. This review discusses the biological motivations for and applications of these techniques to integrating gene expression data with other biological information, such as functional annotation, promoter data and proteomic data.