Cross validation consistency for the assessment of genetic programming results in microarray studies

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 2611, Issue , 2003, Pages 99-106

  Moore, Jason H ^a  

^a VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; DISCRIMINANT ANALYSIS; GENE EXPRESSION; GENES; GENETIC ALGORITHMS; LEARNING SYSTEMS; STOCHASTIC SYSTEMS; TISSUE;

ANALYTICAL STRATEGY; DNA MICROARRAY DATA; DNA MICROARRAY TECHNOLOGY; GENE EXPRESSION PATTERNS; INHERENT COMPLEXITY; MICROARRAY DATA ANALYSIS; STOCHASTIC PROPERTIES; VARIABLE AND FEATURE SELECTION;

GENETIC PROGRAMMING;

EID: 35248826919     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-36605-9_10     Document Type: Article

References (22)

1. Schena, M., Shalon, D., Davis, R. W., Brown, P.O.: Quantitative monitoring of gene expression patterns with a complementary DNA microarray. Science 270 (1995) 467-470
2. Velculesco, V.E., Zhang, L., Vogelstein, B., Kinzler, K. W.: Serial analysis of gene expression. Science 270 (1995) 484-487
3. Caprioli, R.M., Farmer, T.B., Gile, J.: Molecular imaging of biological samples: Localization of peptides and proteins using MALDI-TOF MS. Analyt. Chem. 69 (1997) 4751-4760
4. Bradley, J.V.: Distribution-free statistical tests. Prentice-Hall, Englewood Cliffs (1968)
5. Freitas, A.A.: Understanding the crucial role of attribute interaction in data mining. Artificial Intelligence Reviews 16(2001) 177-199
6. Moore, J.H., Williams, S.M.: New strategies for identifying gene-gene interactions in hypertension. Annals of Medicine 34 (2002) 88-95
7. Ritchie, M.D., Hahn, L.W., Roodi, N., Bailey, L.R., Dupont, W.D., Plummer, W.D., Parl, F.F. and Moore, J.H.: Multifactor dimensionality reduction reveals high-order interactions among estrogen metabolism genes in sporadic breast cancer. American Journal of Human Genetics 69 (2001) 138-147
8. Templeton, A.R.: Epistasis and complex traits. In: Wade, M., Brodie III, B., Wolf, J. (eds.): Epistasis and Evolutionary Process. Oxford University Press, New York (2000)
9. Fisher, R.A.: The Use of Multiple Measurements in Taxonomic Problems. Ann. Eugen. 7 (1936) 179-188
10. Johnson, R.A., Wichem, D.W.: Applied Multivariate Statistical Analysis. Prentice Hall, Upper Saddle River (1998)
11. Huberty, C.J.: Applied Discriminant Analysis. John Wiley & Sons, Inc., New York Chichester Bisbane Toronto Singapore (1994)
12. rd edn. Irwin, Homewood (1990)
13. Moore, J.H., Parker, J.S., Hahn, L.W.: Symbolic discriminant analysis for mining gene expression patterns. In: De Raedt, L., Flach, P. (eds) Lecture Notes in Artificial Intelligence 2167, pp 372-81, Springer-Verlag, Berlin (2001)
14. Koza, J.R.: Genetic Programming: On the Programming of Computers by Means of Natural Selection. The MIT Press, Cambridge London (1992)
15. Moore, J.H., Parker, J.S.: Evolutionary computation in microarray data analysis. In: Lin, S. and Johnson, K. (eds): Methods of Microarray Data Analysis. Kluwer Academic Publishers, Boston (2001)
16. Moore, J.H., Parker, J.S., Olsen, N., Aune, T. Symbolic discriminant analysis of microarray data in autoimmune disease. Genetic Epidemiology 23 (2002) 57-69
17. Hastie, T., Tibshirani, R., Friedman, J.: The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer, New York (2001)
18. Devroye, L., Gyorfi, L., Lugosi, G.: A Probabilistic Theory of Pattern Recognition. Springer-Verlag, New York (1996)
19. Golub, T.R., Slonim, D.K., Tamayo, P., Huard, C., Gaasenbeek, M., Mesirov, J.P., Coller, H., Loh, M.L., Downing, J.R., Caligiuri, M.A., Bloomfield, C.D., Lander, E.S.: Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
20. Maas, K., Chan, S., Parker, J., Slater, A., Moore, J.H., Olsen, N., and Aune, T.M.: Cutting edge: molecular portrait of human autoimmunity. Journal of Immunology 169 (2002) 5-9
21. Gilbert, R.J., Rowland, J.J., Kell, D.B.: Genomic computing: explanatory modelling for functional genomes. In: Whitley, D., Goldberg, D., Cantu-Paz, E., Spector, L., Parmee, I., Beyer, H.-G. (eds): Proceedings of the Genetic and Evolutionary Computation Conference. Morgan Kaufmann Publishers, San Francisco (2000)
22. Eisen, M.B., Spellman, P.T., Brown, P.O., Botstein, D.: Cluster analysis and display of genome-wide expression patterns. Proceedings of the National Academy of Sciences USA 95 (1998) 14863-68