Two methods for improving performance of an HMM and their application for gene finding

Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology, ISMB 1997

Volumn , Issue , 1997, Pages 179-186

  Krogh, Anders ^a,b  

^a TECHNICAL UNIVERSITY OF DENMARK   (Denmark)

^b WELLCOME TRUST SANGER INSTITUTE   (United Kingdom)

Author keywords

gene finding; Hidden Markov model; maximum likelihood; statistical sequence analysis

Indexed keywords

FORECASTING; GENES; MAXIMUM LIKELIHOOD ESTIMATION;

CODING REGION; GENE FINDING; HIDDEN-MARKOV MODELS; IMPROVING PERFORMANCE; MA XIMUM LIKELIHOODS; MAXIMUM-LIKELIHOOD; SEQUENCE ANALYSIS; SPLICE SITE; STATISTICAL SEQUENCE ANALYSE; SUBMODELS;

HIDDEN MARKOV MODELS;

DNA;

ALGORITHM; ARTICLE; BIOLOGICAL MODEL; COMPARATIVE STUDY; EVALUATION; FACTUAL DATABASE; GENE; GENETICS; HUMAN; MOLECULAR GENETICS; NUCLEOTIDE SEQUENCE; PROBABILITY; STATISTICAL MODEL;

ALGORITHMS; BASE SEQUENCE; DATABASES, FACTUAL; DNA; EVALUATION STUDIES; GENES; HUMANS; LIKELIHOOD FUNCTIONS; MARKOV CHAINS; MODELS, GENETIC; MOLECULAR SEQUENCE DATA;

EID: 0030623944     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (21)

1. Borodovsky, M., and Mclninch, J. 1993. GENMARK: Parallel gene recognition for both DNA strands. Computers and Chemistry 17(2):123-133.
2. Brunak, S.; Engelbrecht, J.; and Knudsen, S. 1991. Prediction of human mRN A donor and acceptor sites from the DNA sequence. Journal of Molecular Biology 220(l):49-65.
3. Bürge, C, and Karlin, S. 1997. Prediction of complete gene structure in human genomic DNA. Journal of Molecular Biology 268. To appear.
4. Burset, M., and Guigo, R. 1996. Evaluation of gene structure prediction programs. Genomics 34(3);353-367.
5. Guigo, R.; Knudsen, S.; Drake, N.; and Smith, T. 1992. Prediction of gene structure. Journal of Molecular Biology 226(l):141-57.
6. Henderson, J.; Salzberg, S.; and Fasman, K. 1997. Finding genes in DNA with a hidden Markov model. To appear in Journal of Computational Biology.
7. Juang, B., and Rabiner, L. 1991. Hidden Markov models for speech recognition. Technomet-rics 33(3):251-272.
8. Krogh, A.; Brown, M,; Mian, I. S.; Sjolander, K.; and Haussler, D. 1994. Hidden Markov models in computational biology: Applications to protein modeling. Journal of Molecular Biology 235:1501-1531.
9. Krogh, A.; Mian, I. S.; and Haussler, D. 1994. A hidden Markov model that finds genes in e. coli DNA. Nucleic Acids Research 22:4768-4778.
10. Krogh, A. 1994. Hidden Markov models for labeled sequences. In Proceedings of the 12th lAPR International Conference on Pattern Recognition, 140-144. Los Alamitos, California: IEEE Computer Society Press.
11. 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. In States, D.; Agarwal, P.; Gaasterland, T.; Hunter, L.; and Smith, R., eds., Proc. Conf. on Intelligent Systems in Molecular Biology, 134-142. Menlo Park, CA: AAAI Press.
12. Kulp, D.; Haussler, D.; Reese, M. G.; and Eeckman, F. H. 1997. Integrating database homology in a probabilistic gene structure model. In Altman, R. B.; Dunker, A. K.; Hunter, L.; and Klein, T. E., eds.. Proceedings of the Pacific Symposium on Biocomputing. New York: World Scientific.
13. Normandin, Y., and Morgera, S. D. 1991. An improved MMIE training algorithm for speaker-independent, small vocabulary, continuous speech recognition. In Proc. ICASSP, 537-540.
14. Rabiner, L. R. 1989. A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77(2):257-286.
15. Reese, M. G.; Eeckman, F. H.; Kulp, D.; and Haussler, D. 1997. Improved splice site detection in Genie. In Waterman, M., ed., Proceedings of the First Annual International Conference on Computational Molecular Biology (RECOMB). New York: ACM Press.
16. Riis, S., and Krogh, A. 1997. Hidden neural networks: A framework for HMM/NN hybrids. In Proceedings ofICASSP'97. New York, USA: IEEE. To appear.
17. Schwarz, R., and Chow, Y.-L. 1990. The N-best algorithm: An efficient and exact procedure for finding the N most likely hypotheses. In Proceedings of ICASSP'90, 81-84.
18. Snyder, E., and Stormo, G. 1995. Identification of protein coding regions in genomic DNA. Journal of Molecular Biology 248(1):1-18.
19. Solovyev, V.; Salamov, A.; and Lawrence, C. 1995. Identification of human gene structure using linear discriminant functions and dynamic programming. In Rawlings, C; Clark, D.; Altman, R.; Hunter, L.; Lengauer, T.; and Wodak, S., eds., Proc. of Third Int. Conf. on Intelligent Systems for Molecular Biology, volume 3, 367-375. Menlo Park, CA: AAAI Press.
20. Stormo, G. D., and Haussler, D. 1994. Optimally parsing a sequence into different classes based on multiple types of evidence. In Proc. of Second Int. Conf. on Intelligent Systems for Molecular Biology, 369-375.
21. Uberbacher, E., and Mural, R. 1991. Locating protein-coding regions in human DNA sequences by a multiple sensor - neural network approach. Proceedings of the National Academy of Sciences of the United States of America 88(24):11261-11265.