Statistical methodology for assessing homology of intronic regions of genes

Canadian Journal of Statistics

Volumn 26, Issue 3, 1998, Pages 455-465

  Hall, Deborah L ^a   Kafadar, Karen ^a   Malkinson, Alvin M ^a  

^a UNIVERSITY OF COLORADO   (United States)

Author keywords

Cluster analysis; Homology; Interrupted genes; Introns; Markov processes; Noncoding DNA; Oncognes; Sequence analysis; Transition matrix

Indexed keywords

EID: 0032221151     PISSN: 03195724     EISSN: None     Source Type: Journal    
DOI: 10.2307/3315769     Document Type: Article

References (34)

1. Altschul, S.F., Gish, W., Miller, W., Myers, E., and Lipman, D. (1990). Basic local alignment search tool. J. Molec. Biol. 215, 403-410.
2. Barrai, I., Scapoli, C., Barale, R., and Volina, (1990). S. Oligonucleotide correlations between infector and host genomes hint at evolutionary relationships. Nucleic Acids Res., 18(10), 3021-3025.
3. Billingsley, P., (1961). Statistical methods in Markov chains. Ann. Math. Statist., 32, 12-40.
4. Boguski, M. (1992). Computational sequence analysis revisited: New databases, software tools, and the research opportunities they engender. J. Lipid Res., 33, 957-972.
5. Figueroa, R., Sepulveda, A., Soto, M.A., and Toha, J. (1978). Informational analysis of MS2 and φX174 virus genomes. J. Theoret. Biol., 74, 203-207.
6. Flam, F. (1994). Hints of a language in junk DNA. Science, 266, 1320.
7. Friedman, J.M., Dill, F.J., Hayden, M.R., and McGillivray, B.C. (1992). Genetics. Harwal, Mediz, Penn.
8. Fuchs, C. (1980). On the distribution of the nucleotides in seven completely sequenced DNAs. Gene, 10, 371-373.
9. Garden, P.W. (1980). Markov analysis of viral DNA/RNA sequences. J. Theoret. Biol. 82, 679-684.
10. Gatlin, L.L. (1972). Information Theory and the Living System. Columbia Univ. Press, New York.
11. Gelfand, M., Kozhukhin, C.G., and Pevzner, P.A. (1992). Extendable words in nucleotide sequences. Comput. Appl. Biol. Sci., 8(2), 129-135.
12. Gentleman, J.F., Mullin, R.C. (1989). The distribution of the frequency of occurrence of nucleotide sequences, based on their overlap capability. Biometrics, 45(1), 35-52.
13. Hall, D.L. (1966). Methodology to determine homology and clustering as applied to intronic regions of regulatory cancer genes and non-regulatory genes. Ph.D. Thesis, University of Colorado Health Sciences Center.
14. Hasegawa, M., and Yano, T. (1975). The genetic code and the entropy of protein. Math. Biosci., 24, 182-196.
15. Hashimoto-Gotoh, T., Kikuno, R., Takahashi, K., and Honkawa, H. (1988). Possible role of the first intron of c-H-ras in gene expression: Anti-cancer elements in oncognes. Anticancer Res., 8, 851-860.
16. Hesketh, R. (1995). The Oncogene Handbook. Academic Press, London.
17. Hoel, P.G. (1954). A test for Markov chains. Biometrika, 41, 430-433.
18. Kelly, C. (1994). A test of the Markovian model of DNA evolution. Biometrics, 50, 653-664.
19. King, R.C., and Stansfield, W.D. (1990). A Dictionary of Genetics. Fourth Edition. Oxford Univ. Press, New York.
20. Kleffe, J., and Borodovsky, M. (1992). First and second moments of counts of words in random texts generated by Markov chains. Comput. Appl. Biosci., 8(5), 433-441.
21. Kleffe, J., and Langbecker, U. (1990). Exact computation of pattern probabilities in random sequences generated by Markov chains. Comput. Appl. Biosci., 6(4), 347-353.
22. Lake, J.A. (1994). Reconstruction evolutionary trees from DNA and protein sequences: Paralinear distances. Proc. Nat. Acad. Sci. U.S.A., 91, 1455-1459.
23. Lewin, B. (1994). Genes V. Oxford Univ. Press, New York.
24. Lewis, E.B., Knafels, J.D., Mathog, D.R., and Celniker, S.E. (1995). Sequence analysis of the cis-regulatory regions of the bithorax complex of Drosophila. Proc. Nat. Acad. Sci. U.S.A., 92, 8403-8407.
25. Malkinson, A.M., and You, M. (1994). The intronic structure of cancer-related genes regulates susceptibility to cancer. Molec. Carcinogen., 10, 61-65.
26. Millingan, G.W. (1995). An introduction to classification and clustering. Classification Society of North America Short Course CSNA-95, Session III: Cluster Validation and Comparison.
27. Milligan, G.W., and Cooper, M.C. (1985). An examination of procedures for determining the number of clusters in a data set. Psychometrika, 50(2), 159-179.
28. Phillips, G.J., Arnold, J., and Ivaric, R. (1987). Mono-through hexonucleotide composition of the Escherichia coli genome: A Markov chain analysis. Nucleic Acids Res., 15(6), 2611-2626.
29. SAS Institute Inc. (1989). SAS/Stat User's Gude. Release 6.03 Edition. SAS Institute, Cary, N.C., 283-357.
30. Smith, E.L., Hill, R.L., Lehman, R.I., Lefkowitz, R.J., Handler, P., and White, A. (1983). Principles of Biochemistry: General Aspects. Seventh Edition. McGraw-Hill, 179-237.
31. Telliez, J.-B., Plumb, M., Balmain, A., and Bailleul, B. (1995). Regulatory elements in the first nitron of the mouse Ha-ras gene. Molec. Carcinogenesis, 12, 137-145.
32. Tong, H. (1975). Determination of the order of a Markov chian by Akaike's information criterion. J. Appl. Probab., 12, 488-497.
33. Willis, C. (1991). Exons, Introns and Talking Genes. Basic Books, New York.
34. You, M., Wang, Y., Stoner, G.D., You, L., Maronpot, R., Reynolds, S.H., and Anderson, M. (1992). Parental bias of K-ras oncognes detected in lung tumors from mouse hybrids. Proc. Nat. Acad. Sci. U.S.A., 89, 5804-5808.