Pochet Nathalie L M M, Janssens Frizo A L, De Smet Frank, Marchal Kathleen, Suykens Johan A K, De Moor Bart L R
K. U. Leuven, ESAT-SCD, Kasteelpark Arenberg 10 B-3001 Leuven (Heverlee), Belgium.
Bioinformatics. 2005 Jul 15;21(14):3185-6. doi: 10.1093/bioinformatics/bti495. Epub 2005 May 12.
Microarray classification can be useful to support clinical management decisions for individual patients in, for example, oncology. However, comparing classifiers and selecting the best for each microarray dataset can be a tedious and non-straightforward task. The M@CBETH (a MicroArray Classification BEnchmarking Tool on a Host server) web service offers the microarray community a simple tool for making optimal two-class predictions. M@CBETH aims at finding the best prediction among different classification methods by using randomizations of the benchmarking dataset. The M@CBETH web service intends to introduce an optimal use of clinical microarray data classification.
微阵列分类有助于支持针对个别患者(例如肿瘤学领域)的临床管理决策。然而,比较分类器并为每个微阵列数据集选择最佳分类器可能是一项繁琐且不直接的任务。M@CBETH(主机服务器上的微阵列分类基准测试工具)网络服务为微阵列领域提供了一个用于进行最佳二分类预测的简单工具。M@CBETH旨在通过对基准测试数据集进行随机化处理,在不同分类方法中找到最佳预测。M@CBETH网络服务旨在引入临床微阵列数据分类的最佳应用。