A decision tree system for finding genes in DNA

Journal of Computational Biology

Volumn 5, Issue 4, 1998, Pages 667-680

  Salzberg, Steven ^a,d   Delcher, Arthur L ^b   Fasman, Kenneth H ^c   Henderson, John ^d  

^a J CRAIG VENTER INSTITUTE   (United States)

^b LOYOLA UNIVERSITY MARYLAND   (United States)

^c ASTRAZENECA   (United Kingdom)

^d Johns Hopkins University   (United States)

Author keywords

Decision trees; Dynamic programming; Gene finding; Markov models

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; COMPUTER SYSTEM; DATA BASE; DECISION THEORY; DNA DETERMINATION; DNA SEQUENCE; EXON; PRIORITY JOURNAL; VERTEBRATE;

VERTEBRATA;

EID: 0032449018     PISSN: 10665277     EISSN: None     Source Type: Journal    
DOI: 10.1089/cmb.1998.5.667     Document Type: Article

References (33)

1. Birney, E., Thompson, J., and Gibson, T. 1996. PairWise and SearchWise: finding the optimal alignment in a simultaneous comparison of a protein profile against all DNA translation frames. Nucleic Acids Res. 24, 2730-2739.
2. Breiman, L., Friedman, J., Olshen, R., and Stone, C. 1984. Classification and Regression Trees. Wadsworth International Group, Belmont, CA.
3. Burge, C., and Karlin, S. 1997. Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268, 78-94.
4. Burset, M., and Guigo, R. 1996. Evaluation of gene structure prediction programs. Genomics 34(3), 353-367.
5. Fickett, J., and Tung, C.-S. 1992. Assessment of protein coding measures. Nucleic Acids Res. 20(24), 6441-6450.
6. Gelfand, M., Mironov, A., and Pevzner, P. 1996. Spliced alignment: a new approach to gene recognition. Proc. Natl. Acad. Sci. U.S.A. 93, 9061-9066.
7. Gelfand, M., Podolsky, L., Astakhova, T., and Roytberg, M. 1996. Recognition of genes in human DNA sequences. J. Comput. Biol. 3(2), 223-234.
8. Guigo, R., Knudsen, S., Drake, N., and Smith, T. 1992. Prediction of gene structure. J. Mol. Biol. 226, 141-157.
9. Henderson, J., Salzberg, S., and Fasman, K. 1997. Finding genes in human DNA with a hidden Markov model. J. Comput. Biol. 4(2), 127-141.
10. Hutchinson, G., and Hayden, M. 1992. The prediction of exons through an analysis of spliceable open reading frames. Nucleic Acids Res. 20, 3453-3462.
11. Kleffe, J., Hermann, K., Vahrson, W., Wittig, B., and Brendel, V. 1998. GeneGenerator - A flexible algorithm for gene prediction and its application to maize sequences. Bioinformatics 14(3), 232-243.
12. Kozak, M. 1987. An analysis of 5′-noncoding sequences from 699 vertebrate messenger RNAs. Nucleic Acids Res. 15(20), 8125-8148.
13. Kozak, M. 1992. A consideration of alternative models for the initiation of translation in eukaryotes. Crit. Rev. Biochem. Mol. Biol. 27, 385-402.
14. Kulp, D., Haussler, D., Reese, M.G., and Eeckman, F.H. 1996. A generalized hidden Markov model for the recognition of human genes in DNA, 134-141. In ISMB-96: Proceedings of the Fourth International Conference on Intelligent Systems for Molecular Biology. AAAI Press, Menlo Park, CA.
15. Mount, S. 1996. AT-AC introns: an ATtACk on dogma. Science 271(5256), 1690-1692.
16. Mount, S., Burks, C., Hertz, G., Stormo, G., White, O., and Fields, C. 1992. Splicing signals in Drosophila: intron size, information content, and consensus sequences. Nucleic Acids Res. 20, 4255-4262.
17. Mount, S., Peng, X., and Meier, E. 1995. Some nasty little facts to bear in mind when predicting splice sites. In Gene-Finding and Gene Structure Prediction Workshop (unpublished). Philadelphia.
18. Murthy, S.K., Kasif, S., and Salzberg, S. 1994. A system for induction of oblique decision trees. J. Artif. Intell. Res. 2, 1-33.
19. Quinlan, J.R. 1993. C4.5: Programs for Machine Learning. Morgan Kaufmann Publishers, San Mateo, CA.
20. Reese, M., Eeckman, F., Kulp, D., and Haussler, D. 1997. Improved splice site detection in Genie. J. Comput. Biol. 4(3), 311-323.
21. Salzberg, S. 1995. Locating protein coding regions in human DNA using a decision tree algorithm. J. Comput. Biol. 2(3), 473-485.
22. Salzberg, S. 1997. A method for identifying splice sites and translational start sites in eukaryotic mRNA. Comput. Appl. Biosci. 13(4), 365-376.
23. Sankoff, D. 1992. Efficient optimal decomposition of a sequence into disjoint regions, each matched to some template in an inventory. Math. Biosci. 111, 279-293.
24. Senapathy, P., Shapiro, M., and Harris, N. 1990. Splice junctions, branch points, and exons: sequence statistics, identification, and applications to genome project. Methods Enzymol. 183, 252-278.
25. Snyder, E.E., and Stormo, G.D. 1993. Identification of coding regions in genomic DNA sequences: an application of dynamic programming and neural networks. Nucleic Acids Res. 21(3), 607-613.
26. Snyder, E.E., and Stormo, G.D. 1995. Identification of coding regions in genomic DNA. J. Mol. Biol. 248, 1-18.
27. Solovyev, V., Salamov, A., and Lawrence, C. 1994. Predicting internal exons by oligonucleotide composition and discriminant analysis of spliceable open reading frames. Nucleic Acids Res. 22, 5156-5163.
28. Sze, S.-H., and Pevzner, P. 1997. Las Vegas algorithms for gene recognition: suboptimal and error-tolerant spliced alignment. J. Comput. Biol. 4(3), 297-309.
29. Thomas, A., and Skolnick, M. 1994. A probabilistic model for detecting coding regions in DNA sequences. IMA J. Math. Appl. Med. Biol. 11, 149-160.
30. Wu, T. 1996. A segment-based dynamic programming algorithm for predicting gene structure. J. Comput. Biol. 3(3), 375-394.
31. Xu, Y., Mural, R., Einstein, J., Shah, M., and Uberbacher, E. 1996. Grail: a multi-agent neural network system for gene identification. Proc. IEEE 84(10), 1544-1552.
32. Xu, Y., Mural, R., and Uberbacher, E. 1994. Constructing gene models from accurately predicted exons: an application of dynamic programming. Comput. Appl. Biosci. 10(6), 613-623.
33. Xu, Y., and Uberbacher, E. 1997. Automated gene identification in large-scale genomic sequences. J. Comput. Biol. 4(3), 325-338.