Biomedical Engineering Reference
In-Depth Information
6. Bibliography on Microarray Data Analysis on World Wide Web: http://www.nslij-
genetics.org/microarray/
7. Slonim DK. 2002. From patterns to pathways: gene expression data analysis comes of age.
Nature Genet
32
:502-508.
8. Chaussabel D, Sher A. 2002. Mining microarray expression data by literature profiling.
Ge-
nome Biol
3
:RESEARCH0055.
9. Khatri P, Draghici S, Ostermeier GC, Krawetz SA. 2002. Profiling gene expression using onto-
express.
Genomics
79
:266-270.
10. Mootha VK, Lindgren CM, Eriksson KF, Subramanian A, Sihag S, Lehar J, Puigserver P,
Carlsson E, Ridderstrale M, Laurila E, Houstis N, Daly MJ, Patterson N, Mesirov JP, Golub
TR, Tamayo P, Spiegelman B, Lander ES, Hirschhorn JN, Altshuler D, Groop LC. 2003. PGC-
1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated
in human diabetes.
Nature Genet
34
:267-273.
11. Clarke PA, te Poele R, Wooster R, Workman P. 2001. Gene expression microarray analysis in
cancer biology, pharmacology, and drug development: progress and potential.
Biochem Phar-
macol
62
:1311-1336.
12. Carr KM, Bittner M, Trent JM. 2003. Gene-expression profiling in human cutaneous mela-
noma.
Oncogene
22
:3076-3080.
13. Salter AH, Nilsson KC. 2003. Informatics and multivariate analysis of toxicogenomics data.
Curr Opin Drug Discov Devel
6
:117-122.
14. Pomeroy SL, Tamayo P, Gaasenbeek M, Sturla LM, Angelo M, McLaughlin ME, Kim JY,
Goumnerova LC, Black PM, Lau C, Allen JC, Zagzag D, Olson JM, Curran T, Wetmore C,
Biegel JA, Poggio T, Mukherjee S, Rifkin R, Califano A, Stolovitzky G, Louis DN, Mesirov
JP, Lander ES, Golub TR. 2002. Prediction of central nervous system embryonal tumour out-
come based on gene expression.
Nature
415
:436-442.
15. Service RF. 2003. Genetics and medicine: recruiting genes, proteins for a revolution in diag-
nostics.
Science
300
:236-239.
16. Ardekani AM, Petricoin
III
EF, Hackette JL. 2003. Molecular diagnostics: an FDA perspective.
Expert Rev Mol Diagn
3
:129-140.
17. Quackenbush J. 2002. Microarray data normalization and transformation.
Nature Genet
32
:496-501.
18. Pan W. 2002. A comparative review of statistical methods for discovering differentially ex-
pressed genes in replicated microarray experiments.
Bioinformatics
18
:546-554.
19. Troyanskaya OG, Garber ME, Brown PO, Botstein D, Altman RB. 2002. Nonparametric
methods for identifying differentially expressed genes in microarray data.
Bioinformatics
18
:1454-1461.
20.
Pan W, Lin J, Le CT. 2002. How many replicates of arrays are required to detect gene expres-
sion changes in microarray experiments? a mixture model approach.
Genome Biol
3
:research0022.
21.
Li J, Liu H, Downing JR, Yeoh AE, Wong L. 2003. Simple rules underlying gene expression
profiles of more than six subtypes of acute lymphoblastic leukemia (ALL) patients.
Bioinfor-
matics
19
:71-78.
22.
Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, Coller H, Loh ML,
Downing JR, Caligiuri MA, Bloomfield CD, Lander ES. 1999. Molecular classification of can-
cer: class discovery and class prediction by gene expression monitoring.
Science
286
:531-537.
23.
Liu H, Li J, Wong L. 2002. A comparative study on feature selection and classification meth-
ods using gene expression profiles and proteomics patterns.
Genome Informatics
13
:51-60.
24.
Li W, Yang Y. 2002. Zipf's law in importance of genes for cancer classification using microar-
ray data.
J Theor Biol
219
:539-551.
25.
Lee KE, Sha N, Dougherty ER, Vannucci M, Mallick BK. 2003. Gene selection: a Bayesian
variable selection approach.
Bioinformatics
19
:90-97.
