Open AccessApplication Analysis of Feature Selection (FS) in Bioinformatics
Author(s) -
Changxin Song
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1345/5/052017
Subject(s) - feature selection , feature (linguistics) , computer science , data mining , selection (genetic algorithm) , pattern recognition (psychology) , informatics , bioinformatics , algorithm , artificial intelligence , biology , engineering , philosophy , linguistics , electrical engineering
The feature selection (FS) algorithm selects the effective data from the M original features. The effective feature of low-dimensional data is the structural optimization of the high-dimensional samples. The sample data of bioinformatics was studied using the feature selection (FS) algorithm, which was mainly applied to gene sequence analysis, oligonucleotide array analysis and proteome data analysis. This will explore the intrinsic characteristics of biological systems. This paper mainly discusses the application of feature selection (FS) algorithm in life informatics, and points out the development direction of FS algorithm in bioinformatics by analyzing the problems existing in FS algorithm.