Linear-mixed effects models for feature selection in high-dimensional NMR spectra

Expert Systems with Applications

Volumn 36, Issue 3 PART 1, 2009, Pages 4703-4708

  Mei, Yajun ^a   Kim, Seoung Bum ^b   Tsui, Kwok Leung ^a  

^a Georgia Institute of Technology   (United States)

^b University of Texas at Arlington   (United States)

Author keywords

False discovery rate; Feature selection; Linear mixed effects models; Multiple hypothesis testing; Nuclear magnetic resonance

Indexed keywords

FEATURE EXTRACTION; METABOLITES; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; STATISTICAL TESTS;

CLASSIFICATION MODELS; EFFICIENT FEATURE SELECTIONS; FALSE DISCOVERY RATE; LINEAR MIXED-EFFECTS MODEL; MULTIPLE HYPOTHESIS TESTING; NUCLEAR MAGNETIC RESONANCE (NMR); TIME-COURSE EXPERIMENTS; TWO SAMPLE T TESTS;

NUCLEAR MAGNETIC RESONANCE;

EID: 58349115402     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.06.032     Document Type: Article

References (19)

1. Beckonert O., Bollard M.E., Ebbels T.M.D., Keun H.C., Antti H., Holmes E., et al. NMR-based metabonomics toxicity classification: Hierarchical cluster analysis and k-nearest-neighbour approaches. Analytical Chemistry Acta 490 1 (2003) 3-15
2. Benjamini Y., and Hochberg Y. Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society Series B: Statistical Methodology 57 1 (1995) 289-300
3. Benjamini Y., and Yekutieli D. The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29 4 (2001) 1165-1188
4. 1H NMR data. Chemometrics and Intelligent Laboratory Systems 81 (2006) 50-59
5. Farrant R.D., Lindon J.C., Rahr E., and Sweatman B.C. An automatic data reduction and transfer method to aid pattern recognition analysis and classification of NMR spectra. Journal of Pharmaceutical and Biomedical Analysis 10 2-3 (1992) 141-144
6. Griffin J.L. Metabonomics: NMR spectroscopy and pattern recognition analysis of body fluids and tissues for characterisation of xenobiotic toxicity and disease diagnosis. Current Opinion in Chemical Biology 7 5 (2003) 648-654
7. Holmes E., and Antti H. Chemometric contributions to the evolution of metabonomics: Mathematical solutions to characterising and interpreting complex biological NMR spectra. Analyst 127 12 (2002) 1549-1557
8. Holmes E., Nicholson J.K., and Tranter G. Metabonomic characterization of genetic variations in toxicological metabolic responses using probabilistic neural networks. Chemical Research in Toxicology 14 2 (2001) 182-191
9. Jansen J.J., Hoefsloot H.C., Boelens H.F., van der Greef J., and Smilde A.K. Analysis of longitudinal metabolomics data. Bioinformatics 20 15 (2004) 2438-2446
10. Lee G.-C., and Woodruff D.L. Beam search for peak alignment of NMR signals. Analytica Chimica Acta 513 2 (2004) 413-416
11. Lindon, J. C. (2004). Metabonomics - Techniques and applications. Business briefing: Future drug discovery (pp. 1-6).
12. Lindon J.C., Holmes E., and Nicholson J.K. Pattern recognition methods and applications in biomedical magnetic resonance. Progress in Nuclear Magnetic Resonance Spectroscopy 39 1 (2001) 1-40
13. Nicholson J.K., Connelly J., Lindon J.C., and Holmes E. Metabonomics: A platform for studying drug toxicity and gene function. Nature Reviews Drug Discovery 1 2 (2002) 153-161
14. Nicholson J.K., Lindon J.C., and Holmes E. Metabonomics: Understanding the metabolic response of living systems to pathophysiological stimuli via multi-variate statistical analysis of biological NMR spectroscopic data. Xenobiotica 29 11 (1999) 1181-1189
15. Shaffer J.P. Multiple hypothesis testing. Annual Review of Psychology 46 (1995) 561-584
16. Storey J.D. The positive false discovery rate: A Baysian interpretation and the q-value. Annals of Statistics 31 6 (2003) 2013-2035
17. Storey J.D., and Tibshirani R. Statistical significance for genomewide studies. Proceedings of the National Academy of Sciences of the USA 100 16 (2003) 9440-9445
18. Wang Y., Holmes E., Nicholson J.K., Cloarec O., Chollet J., Tanner M., et al. Metabonomic investigations in mice infected with Schistosoma mansoni: An approach for biomarker identification. Proceedings of the National Academy of Sciences of the USA 101 34 (2004) 12676-12681
19. Wang Y., Tang H., Nicholson J.K., Hylands P.J., Sampson J., and Holmes E. A metabonomic strategy for the detection of the metabolic effects of chamomile (matricaria recutita L.) ingestion. Journal of Agricultural and Food Chemistry 53 2 (2005) 191-196