pathClass: an R-package for integration of pathway knowledge into support vector machines for biomarker discovery
pathClass: an R-package for integration of pathway knowledge into support vector machines for biomarker discovery
复制标题
DOI：
10.1093/bioinformatics/btr157
复制
发表时间：
2011-05-15
期刊：
影响因子：
5.8
通讯作者：
Beissbarth, Tim
中科院分区：
文献类型：
--
作者：
Johannes, Marc;Froehlich, Holger;Beissbarth, Tim
预后和诊断生物标志物的发现是根据临床风险因素成功分层患者的关键问题之一。为此，统计分类方法，如支持向量机（SVM），是经常使用的工具。不同的小组最近表明，使用先前的生物学知识显着提高分类结果的准确性以及基因列表的可重复性和可解释性。在这里，我们介绍了pathClass，这是一组不同的基于SVM的分类方法，用于改进基因选择和分类性能。pathClass中包含的方法不仅依赖于基因表达数据，而且还利用基因网络数据中携带的信息。
Prognostic and diagnostic biomarker discovery is one of the key issues for a successful stratification of patients according to clinical risk factors. For this purpose, statistical classification methods, such as support vector machines (SVM), are frequently used tools. Different groups have recently shown that the usage of prior biological knowledge significantly improves the classification results in terms of accuracy as well as reproducibility and interpretability of gene lists. Here, we introduce pathClass, a collection of different SVM-based classification methods for improved gene selection and classfication performance. The methods contained in pathClass do not merely rely on gene expression data but also exploit the information that is carried in gene network data.