title: Stable feature selection for biomarker discovery.
abstract: 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.
authors.affiliation: School of Software, Dalian University of Technology, China. zyhe@dlut.edu.cn
authors.forename: Zengyou
authors.initials: Z
authors.lastname: He
authors.forename: Weichuan
authors.initials: W
authors.lastname: Yu
mesh_terms: D000818:Animals; D001185:Artificial Intelligence; D015415:Biomarkers / Q000032:analysis / Q000378:metabolism; D019295:Computational Biology / Q000379:methods*; D006801:Humans
chemical_list: D015415:Biomarkers