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Applications of Geostatistics to the Quantitative Analysis of Genetic Instability in Carcinogenesis
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 Title & Authors
Applications of Geostatistics to the Quantitative Analysis of Genetic Instability in Carcinogenesis
Kim Hyoung-Moon;
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It has long been recognized that cancer is a genetic disease. To find this measures of genetic instability, stain cells with chromosome specific probes using chromosome in-situ hybridization technique is adopted. Even though in-situ hybridization technique is powerful, truncation of nuclei often results in under-representation of chromosome copies in slides due to the sectioning of tissue blocks. Because of this problem we suggest three different methods to analyze the cervical cancer data set. We observe that genetic instability is an increasing function of histology and our suggested model is the best in detecting genetic instability of tumorigenesis processes.
Tumorigenesis;Geostatistics;Smoothing;Random-coefficient model;
 Cited by
Andreeff, M. and Pinkel, D. (1999), Introduction to Fluorescence In Situ Hybridization: Principles and Clinical Applications, Wiley -Liss, Inc

Besag, J. (1974). Spatial Interaction and the Statistical Analysis of Lattice Systems. Journal of the Royal Statistical Society Ser. B, Vol. 36, 192-225

Brambilla, C. and Brambilla, E. (1999). Lung Tumors, Marcel Dekker, New York

Cressie, N.A.C. (1993). Statistics for Spatial Data(Revised Edition), John Wiley and Sons. New York

Diggle, P.J. (2003). Statistical Analysis of Spatial Point Patterns(second edition), Oxford University Press Inc., New York

Kim, S.Y., Lee, J.S., Ro, J.Y., Gay, M.L., Hong, W.K., and Hittelman, W.N. (1993). Interphase Cytogenetics in Paraffin Sections of Lung Tumors by Non-Isotopic in-Situ Hybridization. American Journal of Pathology, Vol. 142, 307-317

Hittelman, W.N. (2001). Genetic Instability in Epithelial Tissues at Risk for Cancer. Annals of the New York Academy of Sciences, Vol. 952, 1-12

Littell, R.C., Milliken, G.A., Stroup, W.W., and Wo, R.D. (1996). SAS System for Mixed Models, SAS Publishing

Stoyan, D. and Walder, O. (2000). On Variogram in Point Process Statistics, II: Models of Markings and Ecological Interpretation. Biometrical Journal, Vol. 42, 171-187 crossref(new window)