The-more-the-better and the-less-the-better

Bioinformatics

Volumn 22, Issue 18, 2006, Pages 2187-2188

  Li, Wentian ^a  

^a FEINSTEIN INSTITUTE FOR MEDICAL RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; BIOENGINEERING; BIOINFORMATICS; CHROMOSOME ANALYSIS; DATA ANALYSIS; DNA MICROARRAY; DNA SEQUENCE; EDITORIAL; GENE EXPRESSION; GENE MAPPING; GENETIC ALGORITHM; GENETIC ASSOCIATION; GENETIC DATABASE; GENETIC HETEROGENEITY; GENETIC SUSCEPTIBILITY; GENETIC VARIABILITY; GENOMICS; HUMAN GENETICS; INFORMATION RETRIEVAL; LEUKEMIA; MEDICAL INFORMATION; MEDICAL LITERATURE; PREDICTION; PRIORITY JOURNAL; STATISTICAL MODEL;

EID: 33748702278     PISSN: 13674803     EISSN: 13674811     Source Type: Journal    
DOI: 10.1093/bioinformatics/btl189     Document Type: Editorial

References (13)

1. Amit,Y. and Geman,D. (1997) Shape quantization and recognition with randomized trees. Neural Comput., 9, 1545-1588.
2. Breiman,L. (2001) Statistical modeling: The two cultures. Stat. Sci., 16, 199-231.
3. Burnham,K.P. and Anderson,D.R. (2002) Model Selection and Multi-Model Inference. 2nd edn. Springer-Verlag, New York, NY.
4. Díaz-Uriarte,R. and Alvarez de Andrés,S. (2006) Gene selection and classification of microarray data using random forest. BMC Bioinformatics, 7, 3.
5. Domingos,P. (1999) The role of Occam's razor in knowledge discovery. Data Mining and Knowl. Disc., 3, 409-425.
6. Edwards,J.H. (1987) Exclusion mapping. J. Med. Genet., 24, 539-543.
7. George,E.I. and McCulloch,R.E. (1993) Variable selection via Gibbs sampling. J. Am. Stat. Assoc., 88, 881-889.
8. Golub,T.R. et al. (1999) Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science, 286, 531-537.
9. Hastie,T., Tibshirani,R. and Freidman,J. (2001) The Elements of Statistical Learning. Springer-Verlag, New York, NY.
10. Li,W. and Nyholt,D.R. (2001) Marker selection by Akaike information criterion and Bayesian information criterion. Genet. Epidemiol., 21 (Suppl. 1), S272-S277.
11. Li,W. and Yang,Y. (2002) How many genes are needed for a discriminant microarray data analysis. In Lin,S.M. and Johnson,K.F. (eds), Methods of Microarray Data Analysis. Kluwer Academic, pp. 137-150.
12. Weiss,K.M. and Terwilliger,J.D. (2000) How many diseases does it take to map a gene with SNPs? Nature Genet., 26, 151-157.
13. Xiong,M. et al. (2001) Feature (gene) selection in gene expression-based tumor classification. Mol. Genet. Metabolism., 73, 239-247.