MicroRNA expression profile based cancer classification using Default ARTMAP

Neural Networks

Volumn 22, Issue 5-6, 2009, Pages 774-780

  Xu, Rui ^a   Xu, Jie ^b   Wunsch II, Donald C ^a  

^a Missouri University of Science and Technology   (United States)

^b Northwestern University   (United States)

Author keywords

Cancer classification; Default ARTMAP; miRNA expression profile; Particle swarm optimization

Indexed keywords

CANCER CLASSIFICATION; CANCER DIAGNOSIS; CLASSIFICATION ACCURACY; CLINICAL PARAMETERS; DEFAULT ARTMAP; EXPRESSION DATA; EXPRESSION PROFILING; HIGH DIMENSIONALITY; HIGH-THROUGHPUT; HUMAN CANCER; MESSENGER RNAS (MRNA); MICRORNA EXPRESSION; MICRORNAS; MIRNA EXPRESSION PROFILE; NON-CODING RNAS; PERFORMANCE OF CLASSIFIER; TUMOR SUPPRESSORS;

CLASSIFIERS; LEARNING SYSTEMS; NUCLEIC ACIDS; ONCOGENIC VIRUSES; RNA;

PARTICLE SWARM OPTIMIZATION (PSO);

MESSENGER RNA; MICRORNA;

ACCURACY; ARTICLE; CANCER CLASSIFICATION; CANCER RESEARCH; CARCINOGENESIS; CLASSIFIER; DNA MICROARRAY; FUZZY SYSTEM; GENE EXPRESSION PROFILING; HUMAN; MALIGNANT NEOPLASTIC DISEASE; NONHUMAN; ONCOGENE; PRIORITY JOURNAL; RNA FINGERPRINTING; TUMOR SUPPRESSOR GENE;

ALGORITHMS; ANIMALS; FEMALE; FUZZY LOGIC; HUMANS; MALE; MICE; MICRORNAS; NEOPLASMS; NEURAL NETWORKS (COMPUTER); OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS;

EID: 68149166736     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2009.06.018     Document Type: Article

References (37)

1. Ambros V. The functions of animal microRNAs. Nature 431 (2004) 350-355
2. Amis, G., & Carpenter, G. (2007). Default ARTMAP 2. In Proceedings of international joint conference on neural networks (pp. 777-782)
3. Bartel D. MicroRNAs: Genomics, biogenesis, mechanism, and function. Cell 116 (2004) 281-297
4. Calin G., and Croce C. MicroRNA-cancer connection: The beginning of a new tale. Cancer Research 66 (2006) 7390-7394
5. Calin G., Ferracin M., Cimmino A., Di Leva G., Shimizu M., Wojcik S., et al. A microRNA signature associated with prognosis and progression in chronic lymphocytic leukemia. The New England Journal of Medicine 353 (2005) 1793-1801
6. Carpenter, G. (2003). Default ARTMAP. In Proceedings of the international conference on neural networks (pp. 1396-1401)
7. Carpenter G., and Grossberg S. A massively parallel architecture for a self-organizing neural pattern recognition machine. Computer Vision, Graphics, and Image Processing 37 (1987) 54-115
8. Carpenter G., Grossberg S., Markuzon N., Reynolds J., and Rosen D. Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps. IEEE Transactions on Neural Networks 3 (1992) 698-713
9. Carpenter G., Grossberg S., and Rosen D. Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system. Neural Networks 4 (1991) 759-771
10. Carpenter G., Milenova B., and Noeske B. Distributed ARTMAP: A neural network for fast distributed supervised learning. Neural Networks 11 (1998) 793-813
11. del Valle Y., Venayagamoorthy G., Mohagheghi S., Hernandez J., and Harley R. Particle swarm optimization: Basic concepts, variants and applications in power systems. IEEE Transactions on Evolutionary Computation 12 (2008) 171-195
12. Duda R., Hart P., and Stork D. Pattern Classification. 2nd ed. (2001), Wiley & Sons, New York, NY
13. Golub T., Slonim D., Tamayo P., Huard C., Gaasenbeek M., Mesirov J., et al. Molecular classification of cancer: Class discovery and class prediction by gene expression monitoring. Science 286 (1999) 531-537
14. Grossberg S. Adaptive pattern recognition and universal encoding II: Feedback, expectation, olfaction, and illusions. Biological Cybernetics 23 (1976) 187-202
15. He H., Jazdzewski K., Li W., Liyanarachchi S., Nagy R., Volinia S., et al. The role of microRNA genes in papillary thyroid carcinoma. Proceedings of the National Academic Sciences USA 102 (2005) 19075-19080
16. Iorio M., Ferracin M., Liu C., Veronese A., Spizzo R., Sabbioni S., et al. MicroRNA gene expression deregulation in human breast cancer. Cancer Research 65 (2005) 7065-7070
17. Kennedy, J., & Eberhart, R. (1997). A discrete binary version of the particle swarm optimization. In Proceedings of conference on system, man, and cybernetics (pp. 4104-4108)
18. Kennedy J., Eberhart R., and Shi Y. Swarm intelligence (2001), Academic Press, San Diego, CA
19. Kohonen T. Self-organizing maps. 3rd ed. (2001), Springer, Berlin
20. Lu J., Getz G., Miska E., Alvarez-Saavedra E., Lamb J., Peck D., et al. MicroRNA expression profiles classify human cancers. Nature 435 (2005) 834-838
21. Mulder S., and Wunsch II D. Million city traveling salesman problem solution by divide and conquer clustering with adaptive resonance neural networks. Neural Networks 16 (2003) 827-832
22. Oulas A., Reczko M., and Poirazi P. MicroRNAs and cancer-The search begins!. IEEE Transactions on Information Technology in Biomedicine 13 (2009) 67-77
23. Parsons O., and Carpenter G. ARTMAP neural networks for information fusion and data mining: Map production and target recognition methodologies. Neural Networks 16 (2003) 1075-1089
24. Platt J. Fast training of support vector machines using sequential minimal optimization. In: Schoelkopf B., Burges C., and Smola A. (Eds). Advances in kernel methods - support vector learning (1999), MIT Press, Cambridge, MA 185-208
25. Quinlan J. C4.5: Programs for machine learning (1993), Morgan Kaufmann, San Francisco, CA
26. Ramaswamy S., Tamayo P., Rifkin R., Mukherjee S., Yeang C., Angelo M., et al. Multiclass cancer diagnosis using tumor gene expression signatures. Proceedings of the National Academic Sciences USA 98 (2001) 15149-15154
27. Rumelhart D., Hinton G., and Williams R. Learning internal representations by error propagation. In: Rumelhart D., McClelland J., and The PDP Research Group (Eds). Parallel distributed processing (1986), MIT Press, Cambridge, MA 318-362
28. Specht D. Probabilistic neural networks. Neural Networks 3 (1990) 109-118
29. Vapnik V. The nature of statistical learning theory (1995), Springer-Verlag, New York, NY
30. Volinia S., Calin G., Liu C., Ambs S., Cimmino A., Petrocca F., et al. A microRNA expression signature of human solid tumors defines cancer gene targets. Proceedings of the National Academic Sciences USA 103 (2006) 2257-2261
31. Witten I., and Frank E. Data mining: Practical machine learning tools and techniques. 2nd ed. (2005), Morgan Kaufmann, San Francisco, CA
32. Xu R., Anagnostopoulos G., and Wunsch II D. Multi-class cancer classification using semi-supervised ellipsoid ARTMAP and particle swarm optimization with gene expression data. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4 (2007) 65-77
33. Xu, R., Xu, J., & Wunsch II, D. (2009). Using default ARTMAP for cancer classification with microRNA expression signatures. In Proceedings of international joint conference on neural networks (pp. 3398-3404)
34. Xu R., and Wunsch II D. Clustering (2008), John Wiley & Sons/IEEE Press, Hoboken, NJ
35. Xu R., Wunsch II D., and Frank R. Inference of genetic regulatory networks with recurrent neural network models using particle swarm optimization. IEEE/ACM Transactions on Computational Biology and Bioinformatics 4 (2007) 681-692
36. Yanaihara N., Caplen N., Bowman E., Seike M., Kumanoto K., Yi M., et al. Unique microRNA molecular profiles in lung cancer diagnosis and prognosis. Cancer Cell 9 (2006) 189-198
37. Zheng Y., and Kwoh C. Cancer classification with microRNA expression patterns found by an information theory approach. Journal of Computers 1 (2006) 30-39