Zhang Fan, Chen Jake Y
Indiana University School of Informatics, Indianapolis, IN, USA.
Methods Mol Biol. 2011;719:511-26. doi: 10.1007/978-1-61779-027-0_24.
The advent of Omics technologies as genomics and proteomics has brought the hope of discovering novel biomarkers that can be used to diagnose, predict, and monitor the progress of disease. The importance of data mining to identify biological markers for the diagnostic classification and prognostic assessment in the context of microarray and proteomic data has been increasingly recognized. We present an overview of general data mining methods and their applications to biomarker discovery with particular focus on genomics and proteomics data. Two case studies are exemplarily presented, and relevant data mining terminology and techniques are explained.
随着基因组学和蛋白质组学等组学技术的出现，人们带来了发现可用于诊断、预测和监测疾病进展的新型生物标志物的希望。在微阵列和蛋白质组学数据的背景下，数据挖掘对于识别用于诊断分类和预后评估的生物标志物的重要性已得到越来越多的认可。我们概述了一般数据挖掘方法及其在生物标志物发现中的应用，特别关注基因组学和蛋白质组学数据。示例性地介绍了两个案例研究，并解释了相关的数据挖掘术语和技术。
