Splice site prediction using stochastic regular grammars

Genetics and Molecular Research

Volumn 6, Issue 1, 2007, Pages 105-115

  Kashiwabara, A Y ^a   Vieira, D C G ^b   Machado Lima, A ^a   Durham, A M ^a  

^a UNIVERSITY OF SÃO PAULO   (Brazil)

^b Bolsa de Mercadorias e Futuros (BMandF)   (Brazil)

Author keywords

Gene prediction; Machine learning; Splice sites; Stochastic grammars

Indexed keywords

ALGORITHM; ARTICLE; BINDING SITE; CLASSIFICATION ALGORITHM; DNA SEQUENCE; DNA SPLICING; FALSE POSITIVE RESULT; GENE IDENTIFICATION; GENE LOCATION; PREDICTOR VARIABLE; RNA SPLICING; STOCHASTIC MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; HUMANS; MODELS, MOLECULAR; RNA SPLICING; STOCHASTIC PROCESSES;

EID: 34248390133     PISSN: None     EISSN: 16765680     Source Type: Journal    
DOI: None     Document Type: Article

References (27)

1. Abe N and Warmuth MK (1992). On the computational complexity of approximating distributions by probabilistic automata. Machine Learning 9: 205-260.
2. Aho A, Sethi J and Ullman J (1986). Compilers: principles, techniques, and tools. Addison-Wesley Longman Publishing Co., Inc., Boston.
3. Baldi P and Brunak S (1998). Bioinformatics: the machine learning approach. MIT Press, Cambridge.
4. Blum A, Kalai A and Langford J (1999). Beating the hold-out: bounds for k-fold and progressive crossvalidation. Proceedings of the Twelfth Annual Conference on Computational Learning Theory, July 7-9. ACM Press, Santa Cruz, 203-208.
5. Brunak S, Engelbrecht J and Knudsen S (1991). Prediction of human mRNA donor and acceptor sites from the DNA sequence. J. Mol. Biol. 220: 49-65.
6. Burge C and Karlin S (1997). Prediction of complete gene structures in human genomic DNA. J. Mol. Biol. 268: 78-94.
7. Carrasco RC and Oncina J (1994). Learning stochastic regular grammars by means of a state merging method. Proceedings of the Second International Colloquium. September 21-23. ICG, Alicante, 139-152.
8. Dietterich T (1995). Overfitting and undercomputing in machine learning. ACM Comput. Surv. 27: 326-327.
9. Eddy SR and Durbin R (1994). RNA sequence analysis using covariance models. Nucleic Acids Res. 22: 2079-2088.
10. Guigo R, Knudsen S, Drake N, Smith T (1992). Prediction of gene structure. J. Mol. Biol. 226: 141-157.
11. Hubbard T, Birney E, Bruskiewich R, Clamp M, et al. (1999). Abstracts of papers presented at the 1999 meeting on genome sequencing and biology. Cold Spring Harbor Laboratory Press, Cold Spring Harbor.
12. Hughey R and Krogh A (1996). Hidden Markov models for sequence analysis: extension and analysis of the basic method. Comput. Appl. Biosci. 12: 95-107.
13. Krogh A (1997). Two methods for improving performance of a HMM and their application for gene finding. Proceedings of the 5th International Conference on Intelligent Systems for Molecular Biology. June 21-26. AAAI Press, Halkidiki, 179-186.
14. Krogh A and Vedelsby J (1995). Neural network ensembles, cross validation, and active learning. In: Advances in neural information processing systems (Tesauro G, Touretzky DS and Leen TK, eds.). The MIT Press, Cambridge, 231-238.
15. Machado-Lima A (2002). Laboratório de geração de classificadores de seqüências. Master's thesis, Instituto de Matemática e Estatística da Universidade de São Paulo, USP, São Paulo.
16. Mathe C, Sagot MF, Schiex T and Rouze P (2002). Current methods of gene prediction, their strengths and weaknesses. Nucleic Acids Res. 30: 4103-4117.
17. Murthy SK, Kasif S and Salzberg S (1994). A system for induction of oblique decision trees. J. Artificial Intelligence Res. 2: 1-32.
18. Oncina J and Garcia P (1992). Inferring regular languages in polynomial update time. In: Pattern recognition and image analysis (de la Blanca NP, Sanfeliu A and Vidal E, eds.). World Scientific Publishing, Singapore, 49-61.
19. Reese MG, Eeckman FH, Kulp D and Haussler D (1997). Improved splice site detection in Genie. J. Comput. Biol. 4: 311-323.
20. Ron D, Singer Y and Tishby N (1996). The power of amnesia: learning probabilistic automata with variable memory length. Machine Learning 25: 117-150.
21. Ron D, Singer Y and Tishby N (1998). On the learnability and usage of acyclic probabilistic finite automata. J. Comput. Syst. Sci. 56: 133-152.
22. Sakakibara Y, Brown M, Underwood RC, Mian IS, et al. (1994). Stochastic context-free grammars for modeling RNA. Proceedings of the 27th Annual Hawaii International Conference on System Sciences (Hunter L), January 4-7. IEEE Computer Society Press, Honolulu, 284-293.
23. Salamov AA and Solovyev VV (2000). Ab initio gene finding in Drosophila genomic DNA. Genome Res. 10: 516-522.
24. Staden R (1984). Computer methods to locate signals in nucleic acid sequences. Nucleic Acids Res. 12: 505-519.
25. Uberbacher EC and Mural RJ (1991). Locating protein-coding regions in human DNA sequences by a multiple sensor-neural network approach. Proc. Natl. Acad. Sci. USA 88: 11261-11265.
26. Zhang MQ and Marr TG (1993). A weight array method for splicing signal analysis. Comput. Appl. Biosci. 9: 499-509.
27. Zhang L and Luo L (2003). Splice site prediction with quadratic discriminant analysis using diversity measure. Nucleic Acids Res. 31: 6214-6220.