A gene selection method for microarray data based on binary PSO encoding gene-to-class sensitivity information

IEEE/ACM Transactions on Computational Biology and Bioinformatics

Volumn 14, Issue 1, 2017, Pages 85-96

  Han, Fei ^a   Yang, Chun ^a   Wu, Ya Qi ^a   Zhu, Jian Sheng ^a   Ling, Qing Hua ^b   Song, Yu Qing ^a   Huang, De Shuang ^c  

^a JIANGSU UNIVERSITY   (China)

^b JIANGSU UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^c TONGJI UNIVERSITY   (China)

Author keywords

Binary particle swarm optimization; Gene selection; Gene to class sensitivity information; Microarray data

Indexed keywords

BINS; CLASSIFICATION (OF INFORMATION); GENE ENCODING; NEAREST NEIGHBOR SEARCH; PARTICLE SWARM OPTIMIZATION (PSO); SIGNAL ENCODING; SUPPORT VECTOR MACHINES;

BINARY PARTICLE SWARM OPTIMIZATION; FUNCTIONAL GENES; GENE SELECTION; K-NEAREST NEIGHBORS; MICROARRAY DATA; PREDICTION ACCURACY; PRIOR INFORMATION; SUPPORT VECTOR MACHINE CLASSIFIERS;

GENES;

ALGORITHM; BIOLOGICAL MODEL; BIOMIMETICS; COMPUTER SIMULATION; CROWDING (AREA); DNA MICROARRAY; GENE EXPRESSION PROFILING; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; SUPPORT VECTOR MACHINE;

ALGORITHMS; BIOMIMETICS; COMPUTER SIMULATION; CROWDING; GENE EXPRESSION PROFILING; MODELS, BIOLOGICAL; MODELS, STATISTICAL; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE;

EID: 85020268441     PISSN: 15455963     EISSN: None     Source Type: Journal    
DOI: 10.1109/TCBB.2015.2465906     Document Type: Article

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