School of Software, Dalian University of Technology, China.
Comput Biol Chem. 2010 Aug;34(4):215-25. doi: 10.1016/j.compbiolchem.2010.07.002. Epub 2010 Aug 10.
Feature selection techniques have been used as the workhorse in biomarker discovery applications for a long time. Surprisingly, the stability of feature selection with respect to sampling variations has long been under-considered. It is only until recently that this issue has received more and more attention. In this article, we review existing stable feature selection methods for biomarker discovery using a generic hierarchical framework. We have two objectives: (1) providing an overview on this new yet fast growing topic for a convenient reference; (2) categorizing existing methods under an expandable framework for future research and development.
特征选择技术长期以来一直被用作生物标志物发现应用中的主力军。令人惊讶的是，特征选择对采样变化的稳定性长期以来一直没有得到充分考虑。直到最近，这个问题才越来越受到关注。本文采用通用的分层框架，综述了用于生物标志物发现的现有稳定特征选择方法。我们有两个目标：（1）为方便参考，提供对这个新的、但发展迅速的主题的概述；（2）在可扩展的框架下对现有方法进行分类，以促进未来的研究和开发。
