首页 | 本学科首页   官方微博 | 高级检索  
   检索      


Basic microarray analysis: grouping and feature reduction
Authors:Raychaudhuri S  Sutphin P D  Chang J T  Altman R B
Institution:Stanford Medical Informatics, Department of Medicine, Stanford University, 251 Campus Drive, MSOB X-215, Stanford, CA 94305-5479, USA.
Abstract:DNA microarray technologies are useful for addressing a broad range of biological problems - including the measurement of mRNA expression levels in target cells. These studies typically produce large data sets that contain measurements on thousands of genes under hundreds of conditions. There is a critical need to summarize this data and to pick out the important details. The most common activities, therefore, are to group together microarray data and to reduce the number of features. Both of these activities can be done using only the raw microarray data (unsupervised methods) or using external information that provides labels for the microarray data (supervised methods). We briefly review supervised and unsupervised methods for grouping and reducing data in the context of a publicly available suite of tools called CLEAVER, and illustrate their application on a representative data set collected to study lymphoma.
Keywords:
本文献已被 PubMed 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号