GALGO: An R package for multivariate variable selection using genetic algorithms

Bioinformatics

Volumn 22, Issue 9, 2006, Pages 1154-1156

  Trevino, Victor ^a   Falciani, Francesco ^a  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CHROMOSOME ANALYSIS; CLASSIFICATION; COMPUTER LANGUAGE; COMPUTER PROGRAM; DATA ANALYSIS; DECISION THEORY; FUNCTIONAL GENOMICS; GENETIC ALGORITHM; MULTIVARIATE ANALYSIS; PRIORITY JOURNAL; STATISTICAL MODEL;

EID: 33646121277     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btl074     Document Type: Article

References (7)

1. Dudoit,S. and Fridlyand,J. (2003) Classification in microarray experiments. In Speed,T.P. (ed.), Statistical Analysis of Gene Expression Microarray Data, Chapman & Hall/CRC, Boca Raton, FL, pp. 93-158.
2. Gentleman,R.C. et al. (2004) Bioconductor: Open software development for computational biology and bioinformatics. Genome Biol., 5, R80.
3. Goldberg,D.E. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, Reading, MA, Vol. xiii, p. 412.
4. Lee,J.W. et al. (2005) An extensive comparison of recent classification tools applied to microarray data. Comput. Stat. Data Anal., 48, 869-885.
5. Li,L.P. et al. (2001) Gene selection for sample classification based on gene expression data: Study of sensitivity to choice of parameters of the GA/KNN method. Bioinformatics, 17, 1131-1142.
6. Ooi,C.H. and Tan,P. (2003) Genetic algorithms applied to multi-class prediction for the analysis of gene expression data. Bioinformatics, 19, 37-44.
7. Sha,N. et al. (2004) Bayesian variable selection in multinomial probit models to identify molecular signatures of disease stage. Biometrics, 60, 812-819.