We summarize feature selection approaches with recent applications in bioinformatics. We suggest to deviate from the commonly used categorization of feature selection approaches into filter, wrapper, and embedded approaches. Instead, we view feature selection as a combinatorial optimization or a search problem, by classifying feature selection approaches into exhaustive search, heuristic search,and hybrid methods, with heuristic search approaches further divided into those with or without feature importance ranking.