Comment on 'network-constrained regularization and variable selection for analysis of genomic data'

Bioinformatics

Volumn 24, Issue 21, 2008, Pages 2566-2568

  Binder, Harald ^a,b   Schumacher, Martin ^b  

^a UNIVERSITY OF FREIBURG   (Germany)

^b UNIVERSITY OF FREIBURG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYSIS; GENOMICS; MICROARRAY ANALYSIS; NOTE; PREDICTION; PRIORITY JOURNAL; QUALITY CONTROL; STATISTICAL MODEL;

ALGORITHMS; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENE REGULATORY NETWORKS; GENOME; GLIOBLASTOMA; HUMANS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; SIGNAL TRANSDUCTION;

EID: 54949131787     PISSN: 13674803     EISSN: 14602059     Source Type: Journal    
DOI: 10.1093/bioinformatics/btn412     Document Type: Note

References (12)

1. Bair,E. et al. (2006) Prediction by supervised principal components. J. Am Star. Assoc., 101, 119-137.
2. Binder,H. and Schumacher,M. (2008a) Adapting prediction error estimates for biased complexity selection in high-dimensional bootstrap samples. Stat. Appl. Genet. Mol. Biol., 7, Article 12.
3. Binder,H. and Schumacher,M. (2009b) Allowing for mandatory covariates in boosting estimation of sparse high-dimensional survival models. BMC Bioinformatics, 9, 14.
4. Efron,B. and Tibshirani,R. (1997) Improvements on cross-validation: The .623+ boostrap method. J. Am. Six. Assoc., 92, 548-560.
5. Gerds,T.A. and Schumacher,M. (2006) Consistent estimation of the expected Brier score in general survival models with right-censored event times. Biom J., 48, 1029-1040.
6. Gerds,T.A. and Schumacher,M. (2007) Efron-type measures of prediction error for survival analysis. Biometrics, 63, 1283-1287.
7. Horvath,S. et al. (2006) Analysis of oncogenic signaling networks in glioblastoma identifies ASPM as a molecular target. Proc. Natl Acad. Sci. USA, 103, 17402-17407.
8. Kanehisa,M. and Goto,S. (2000) KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res., 28, 27-30.
9. Li,C. and Li,H. (20M) Network-constrained regularization and variable selection for analysis of genomic data. Bioinformatics, 24, 1175-1182. Doi: 10.1093/bioinformatics/btn081.
10. Schumacher,M. et al. (2007) Assessment of survival prediction models based on microarray data. Bioinformatics, 23, 1768-1774.
11. Tibshirani,R. (1996) Regression shrinkage and selection via the lasso. J. R. Stat. Soc. B, 58, 267-288.
12. Zou,H. and Hastie,T. (2005) Regularization and variable selection via the elastic net. J. R. Stat. Soc. B, 67, 301-320.