Information Technology Reference
In-Depth Information
3. Lina, S., Chien, F.: Cluster analysis of genome-wide expression data for feature extraction.
Expert Systems with Applications 36(2-2), 3327-3335 (2009)
4. Stadlera, Z.K., Come, S.E.: Review of gene-expression profiling and its clinical use in
breast cancer. Critical Reviews in Oncology/Hematology 69(1), 1-11 (2009)
5. Affymetrix. GeneChip® Human Genome U133 Arrays,
http://www.affymetrix.com/support/technical/datasheets/
hgu133arrays_datasheet.pdf
6. Sawa, T., Ohno-Machado, L.: A neural network based similarity index for clustering DNA
microarray data. Computers in Biology and Medicine 33(1), 1-15 (2003)
7. Bianchia, D., Calogero, R., Tirozzi, B.: Kohonen neural networks and genetic classifica-
tion. Mathematical and Computer Modelling 45(1-2), 34-60 (2007)
8. Baladandayuthapani, V., Ray, S., Mallick, B.K.: Bayesian Methods for DNA Microarray
Data Analysis. Handbook of Statistics 25(1), 713-742 (2005)
9. Avogadri, R., Valentini, G.: Fuzzy ensemble clustering based on random projections for
DNA microarray data analysis. Artificial Intelligence in Medicine 45(2-3), 173-183 (2009)
10. Kolodner, J.: Case-Based Reasoning. Morgan Kaufmann, San Francisco (1993)
11. Riverola, F., Díaz, F., Corchado, J.M.: Gene-CBR: a case-based reasoning tool for cancer
diagnosis using microarray datasets. Computational Intelligence 22(3-4), 254-268 (2006)
12. Corchado, J.M., De Paz, J.F., Rodríguez, S., Bajo, J.: Model of Experts for decision sup-
port in the diagnosis of leukemia patients. Artificial Intelligence in Medicine 46, 179-200
(2009)
13. Bichindaritz, I.: Role and Significance of Case-based Reasoning in the Health Sciences.
KI 23(1), 12-17 (2009)
14. Bichindaritz, I., Marling, C.: Case-based reasoning in the health sciences: What's next?
Artificial Intelligence in Medicine 36(2), 127-135 (2006)
15. Furao, S., Ogura, T., Hasegawa, O.: An enhanced self-organizing incremental neural net-
work for online unsupervised learning. Neural Networks 20(8), 893-903 (2007)
16. Kaufman, L., Rousseeuw, P.J.: Finding Groups in Data: An Introduction to Cluster Analy-
sis. Wiley, New York (1990)
17. Saravanan, N., Cholairajana, S., Ramachandran, K.I.: Vibration-based fault diagnosis of
spur bevel gear box using fuzzy technique. Expert Systems with Applications 36(2-2),
3119-3135 (2009)
18. Borg, I., Groenen, P.: Modern multidimensional scaling theory and applications. Springer,
Heidelberg (1997)
19. Kruskal, J.B.: Multidimensional scaling by optimizing goodness of fit to nonmetric hy-
pothesis. Psychometrika 29(1), 1-27 (1964)
20. Ture, M., Tokatli, F., Kurt, I.: Using Kaplan-Meier analysis together with decision tree
methods (C&RT, CHAID, QUEST, C4.5 and ID3) in determining recurrence-free survival
of breast cancer patients. Expert Systems with Applications 36(2), 2017-2026 (2009)
21. Quackenbush, J.: Computational analysis of microarray data. Nature Review Genet-
ics 2(6), 418-427 (2001)
22. Lipshutz, R.J., Fodor, S.P.A., Gingeras, T.R., Lockhart, D.H.: High density synthetic oli-
gonucleotide arrays. Nature Genetics 21(1), 20-24 (1999)
23. Taniguchi, M., Guan, L.L., Basarab, J.A., Dodson, M.V., Moore, S.S.: Comparative analy-
sis on gene expression profiles in cattle subcutaneous fat tissues. Comparative Biochemis-
try and Physiology Part D: Genomics and Proteomics 3(4), 251-256
24. Avogadri, R., Valentini, G.: Fuzzy ensemble clustering based on random projections for
DNA microarray data analysis. Artificial Intelligence in Medicine 45(2-3), 173-183 (2009)
Search WWH ::




Custom Search