An overview of feature selection algorithm in bioinformatics.
- Author:
Xin LI
1
;
Li MA
;
Jinjia WANG
;
Chun ZHAO
Author Information
1. Institute of Biomedical Engineering, Yanshan University, Qinhuangdao 066004, China. yddylixin@ysu.edu.cn
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Computational Biology;
methods;
Computer Simulation;
Models, Biological;
Pattern Recognition, Automated;
methods
- From:
Journal of Biomedical Engineering
2011;28(2):410-414
- CountryChina
- Language:Chinese
-
Abstract:
Feature selection (FS) techniques have become an important tool in bioinformatics field. The core algorithm of it is to select the hidden significant data with low-dimension from high-dimensional data space, and thus to analyse the basic built-in rule of the data. The data of bioinformatics fields are always with high-dimension and small samples, so the research of FS algorithm in the bioinformatics fields has great foreground. In this article, we make the interested reader aware of the possibilities of feature selection, provide basic properties of feature selection techniques, and discuss their uses in the sequence analysis, microarray analysis, mass spectra analysis etc. Finally, the current problems and the prospects of feature selection algorithm in the application of bioinformatics is also discussed.
