Prediction of colon cancer using an evolutionary neural network

Neurocomputing

Volumn 61, Issue 1-4, 2004, Pages 361-379

  Kim, Kyung Joong ^a   Cho, Sung Bae ^a  

^a Yonsei University   (South Korea)

Author keywords

Colon cancer; DNA Microarray; Evolutionary neural network; Feature selection; Information gain

Indexed keywords

ALGORITHMS; CELLS; DISEASE CONTROL; DNA; GENES; TUMORS;

HYBRIDIZATION; MICROARRAYS;

NEURAL NETWORKS;

COMPLEMENTARY DNA;

ANALYTIC METHOD; ARTICLE; ARTIFICIAL NEURAL NETWORK; CANCER CELL; COLON CANCER; COMPUTER PREDICTION; CONTROLLED STUDY; DNA HYBRIDIZATION; DNA MICROARRAY; EVOLUTIONARY ADAPTATION; EXPERIMENTAL DESIGN; GENE EXPRESSION PROFILING; GENE TECHNOLOGY; GENETIC ALGORITHM; GENETIC IDENTIFICATION; HUMAN; HUMAN CELL; INFORMATION PROCESSING; MAJOR CLINICAL STUDY; PRIORITY JOURNAL; SOMATIC MUTATION; STATISTICAL ANALYSIS;

EID: 10244259163     PISSN: 09252312     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neucom.2003.11.008     Document Type: Article

References (39)

1. Alon U. Barkai N. Notterman D.A. Gish K. Ybarra S. Mack D. Levine A.J. Broad patterns of gene expression revealed by clustering analysis of tumor and normal colon tissues probed by oligonucleotide arrays Proc. Natl. Acad. Sci. USA 96 1999 6745-6750
2. J.-H. Ahn, S.-B. Cho, Combining multiple neural networks evolved by speciation, ICONIP 2000, 2000, pp. 230-234.
3. J.-H. Ahn, S.-B. Cho, Speciated neural networks evolved with fitness sharing technique, Proceedings of the 2001 Congress on Evolutionary Computation, Vol. 1, 2001, pp. 390-396.
4. Barrett J.C. Kawasaki E.S. Microarrays: The use of oligonucleotides and cDNA for the analysis of gene expression Drug Discovery Today 8 3 2003 134-141
5. Ben-Dor A. Bruhn L. Friedman N. Nachman I. Schummer M. Yakhini N. Tissue classification with gene expression profiles J. Comput. Biol. 7 2000 559-584
6. Cho S.-B. Self-organizing map with dynamical node splitting: application to handwritten digit recognition Neural Comput. 9 6 1997 1345-1355
7. Chung-Faye G.A. Kerr D.J. Young L.S. Searle P.F. Gene therapy strategies for colon cancer Mol. Med. Today 6 2 2000 82-87
8. M. Conrad, Computation: Evolutionary, neural, molecular, 2000 IEEE Symposium on Combinations of Evolutionary Computation and Neural Networks, 2000, pp. 1-9.
9. N. Cristianini, J. Shawe-Taylor, An Introduction to Support Vector Machines, Cambridge University Press, Cambridge, 2000.
10. Derisi J. Iyer V. Brosn P. Exploring the metabolic and genetic control of gene expression on a genomic scale Science 278 1997 680-686
11. Eisen M.B. Spellman P.T. Brown P.O. Bostein D. Cluster analysis and display of genome-wide expression patterns Proc. Natl. Acad. Sci. USA 95 1998 14863-14868
12. Fogel D.B. Chellapilla K. Verifying Anaconda's expert rating by competing against Chinook: Experiments in co-evolving a neural checkers player Neurocomputing 42 1-4 2002 69-86
13. Furey T.S. Cristianini N. Duffy N. Bednarski D.W. Schummer M. Haussler D. Support vector machine classification and validation of cancer tissue samples using microarray expression data Bioinformatics 16 10 2000 906-914
14. Getz G. Levine E. Domany E. Coupled two-way clustering analysis of gene microarray data Proc. Natl. Acad. Sci. USA 97 22 2000 12079-12084
15. Goldberg D.E. Genetic Algorithms in Search, Optimization and Machine Learning 1989 Addison-Wesley Reading, MA
16. Guyon I. Weston J. Barnhill S. Vapnik V. Gene selection for cancer classification using support vector machine Mach. Learning 46 1-3 2002 389-422
17. GraphViz, Graph Visualization Project, http://www.graphviz.org/.
18. Hampton G.M. Frierson H.F.Jr. Classifying human cancer by analysis of gene expression Trends Mol. Med. 9 1 2003 5-19
19. Harrington C.A. Rosenow C. Retief J. Monitoring gene expression using DNA microarrays Curr. Opinion Microbiol. 3 2000 285-291
20. Haykin S.S. Neural Networks: A Comprehensive Foundation 2nd Edition 1998 Prentice-Hall Englewood Cliffs, NJ
21. Kitano H. Designing neural networks using genetic algorithms with graph generation system Complex Syst. 4 4 1990 461-476
22. Lipshutz R.J. Fodor S.P.A. Gingeras T.R. Lockhart D.J. High density synthetic oligonucleotide arrays Nat. Genet. 21 1999 20-24
23. S.-I. Lee, J.-H. Ahn, S.-B. Cho, Exploiting diversity of neural ensembles with speciated evolution, International Joint Conference on Neural Networks, Vol. 2, 2001, pp. 808-313.
24. W. Li, I. Grosse, Gene selection criterion for discriminant microarray data analysis based on extreme value distributions, RECOMB03: Proceedings of the Seventh Annual International Conference on Computational Biology, 2003.
25. Li Y. Campbell C. Tipping M. Bayesian automatic relevance determination algorithms for classifying gene expression data Bioinformatics 18 2002 1332-1339
26. Li L. Weinberg C.R. Darden T.A. Pedersen L.G. Gene selection for sample classification based on gene expression data: Study of sensitivity to choice of parameters of the GA/KNN method Bioinformatics 17 12 2001 1131-1142
27. Mitchell T.M. Machine Learning 1997 McGraw-Hill New York
28. Mladenic D. Grobelnik M. Feature selection on hierarchy of web documents Decision Support Syst. 35 1 2003 45-87
29. D. Montana, L. Davis, Training feedforward neural networks using genetic algorithms, Proceedings of the 11th International Conference on Artificial Intelligence, 1989, pp. 762-767.
30. Nguyen D.V. Rocke D.M. Tumor classification by partial least squares using microarray gene expression data Bioinformatics 18 1 2002 39-50
31. J.R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, Los Altos, CA, 1992.
32. Rew D.A. DNA microarray technology in cancer research Eur. J. Surg. Oncol. 27 5 2001 504-508
33. Sarkar I.N. Planet P.J. Bael T.E. Stanley S.E. Siddall M. DeSalle R. Figurski D.H. Characteristic attributes in cancer microarrays J. Biomed. Inf. 35 2 2002 111-122
34. R. Shamir, R. Sharan, Algorithmic approaches to clustering gene expression data, in: T. Jiang, T. Smith, Y. Xu, M.Q. Zhang (Eds.), Current Topics in Computational Biology, MIT Press, Cambridge, MA, 2001.
35. D.W. Taylor, D.W. Corne, D.L. Taylor, J. Harkness, Predicting alarms in supermarket refrigeration systems using evolved neural networks and evolved rulesets, Congress on Evolutionary Computation, 2002, pp. 1988-1993.
36. Wuju L. Momiao X. Tclass: Tumor classification system based on gene expression profiles Bioinformatics 18 2002 325-326
37. Xiong M. Li W. Zhao J. Jin L. Boerwinkle E. Feature (Gene) selection in gene expression-based tumor classification Mol. Genet. Metabolism 73 3 2001 239-247
38. Yao X. Evolving artificial neural networks Proc. IEEE 87 9 1999 1423-1447
39. Yao X. Liu Y. A new evolutionary system for evolving artificial neural networks IEEE Trans. Neural Networks 8 3 1997 694-713