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Grammar-Based Classifier System for Recognition of Promoter Regions

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Adaptive and Natural Computing Algorithms (ICANNGA 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4431))

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Abstract

Identifying bacterial promoters is an important step towards understanding gene regulation. In this paper, we address the problem of predicting the location of promoters in Escherichia coli. Language of bacterial sequence can be described using formal system such a context-free grammar, and problem of promoter region recognition replaced by grammar induction. The accepted method for this problem is to use grammar-based classifier system (GCS).

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References

  1. Angluin, D.: Queries and concept learning. Machine Learning 2(4), 319–342 (1988)

    Google Scholar 

  2. Blattner, F., Plunkett, G., Bloch, C., Perna, N., Burland, V., Riley, M., Collado-Vides, J., Glasner, J., Rode, C., Mayhew, G.: at all: The complete genome sequence of Escherichia coli k-12. Science 277, 1453–1462 (1997)

    Article  Google Scholar 

  3. Collado-Vides, J.: Grammatical model of the regulation of gene expression. Proc. Natl. Acad. Sci. USA 89, 9405–9409 (1992)

    Article  Google Scholar 

  4. Dupont, P.: Regular Grammatical Inference from Positive and Negative Samples by Genetic Search. In: Carrasco, R.C., Oncina, J. (eds.) ICGI 1994. LNCS, vol. 862, pp. 236–245. Springer, Heidelberg (1994)

    Google Scholar 

  5. Durbin, R., Eddy, S., Krogh, A., Mitchison, G.: Biological Sequence Analysis. Cambridge University Press, Cambridge (1998)

    MATH  Google Scholar 

  6. Gold, E.: Language identification in the limit. Information Control 10, 447–474 (1967)

    Article  MATH  Google Scholar 

  7. de la Higuera, C.: Current trends in grammatical inference. In: Amin, A., Pudil, P., Ferri, F.J., Iñesta, J.M. (eds.) SPR 2000 and SSPR 2000. LNCS, vol. 1876, pp. 28–31. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  8. Holland, J.: Adaptation. In: Rosen, R., Snell, F.M. (eds.) Progress in theoretical biology, Plenum, New York (1976)

    Google Scholar 

  9. Huijsen, W.: Genetic Grammatical Inference: Induction of Pushdown Automata and Context-Free Grammars from Examples Using Genetic Algorithms. M.Sc.- thesis, Dept. of Computer Science, University of Twente, Enschede, The Netherlands (1993)

    Google Scholar 

  10. Kammeyer, T.E., Belew, R.K.: Stochastic Context-Free Grammar Induction with a Genetic Algorithm Using Local Search. Technical Report CS96-476, Cognitive Computer Science Research Group, Computer Science and Engineering Department, University of California at San Diego (1996)

    Google Scholar 

  11. Keller, B., Lutz, R.: Evolutionary induction of stochastic context-free grammars. Pattern Recognition Journal 38, 1393–1406 (2005)

    Article  MATH  Google Scholar 

  12. Korkmaz, E.E., Ucoluk, G.: Genetic Programming for Grammar Induction. In: Proc. of the Genetic and Evolutionary Conference, GECCO-2001, Morgan Kaufmann Publishers, San Francisco (2001)

    Google Scholar 

  13. Lankhorst, M.M.: A Genetic Algorithm for the Induction of Nondeterministic Pushdown Automata. Computing Science Reports CS-R 9502, Department of Computing Science, University of Groningen (1995)

    Google Scholar 

  14. Lanzi, P.L., Riolo, R.L.: A Roadmap to the Last Decade of Learning Classifier System Research. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 1999. LNCS (LNAI), vol. 1813, pp. 33–62. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  15. Lee, L.: Learning of Context-Free Languages: A Survey of the Literature. Report TR-12-96, Harvard University, Cambridge, Massachusetts (1996)

    Google Scholar 

  16. Leung, S.W., Mellish, C., Robertson, D.: Basic gene grammars and dna-chart parser for language processing of Escherichia coli promoter dna sequences. Bioinformatics 17, 226–236 (2001)

    Article  Google Scholar 

  17. Lewin, B.: Genes VII. Oxford University Press, Oxford (2000)

    Google Scholar 

  18. Losee, R.M.: Learning Syntactic Rules and Tags with Genetic Algorithms for Information Retrieval and Filtering: An Empirical Basis for Grammatical Rules. In: Information Processing & Management (1995)

    Google Scholar 

  19. Lucas, S.: Context-Free Grammar Evolution. In: First International Conference on Evolutionary Computing, pp. 130–135 (1994)

    Google Scholar 

  20. Mishra, R., Chatterji, D.: Promoter search and strength of a promoter: two important means for regulation of gene expression in Escherichia coli. J. Biosci. 18, 1–11 (1993)

    Article  Google Scholar 

  21. Murphy, P.M., Aha, D.W.: UCI Repository of Machine Learning Databases. Department of Information and Computer Science, University of California at Irvine, Irvine, CA (1992)

    Google Scholar 

  22. O’Neill, M.: Escherichia coli promoters: neural networks develop distinct descriptions in learning to search for promoters of different spacing classes. Nucleic Acids Res. 20, 3471–3477 (1992)

    Article  MathSciNet  Google Scholar 

  23. Pereira, F., Warren, D.: Definite clause grammars for language analysis. Artif. Intell. 13, 231–278 (1980)

    Article  MATH  MathSciNet  Google Scholar 

  24. Rice, P., Elliston, K., Gribskov, M.: DNA. In: Girbskov, M., Devereux, J. (eds.) Sequence Analysis Primer, pp. 1–59. Stockton Press, Basingstoke (1991)

    Google Scholar 

  25. Rosenblueth, D., Thieffry, D., Huerta, A., Salgado, H., Collado-Vides, J.: Syntactic recognition of regulatory regions in Escherichia coli. Comput. Appl. Biosci. 12, 415–422 (1996)

    Google Scholar 

  26. Sakakibara, Y.: Grammatical Inference in Bioinformatics. IEEE Transactions on Pattern Analysis and Machine Intelligence 27(7), 1051–1062 (2005)

    Article  Google Scholar 

  27. Searls, D.: Investigating the linguistics of DNA with definite clause grammars. In: Lusk, E., Overbeek, R. (eds.) Logic Programming: Proceedings of the North America Conference on Logic Programming, vol. 1, pp. 189–208. MIT Press, Cambridge (1989)

    Google Scholar 

  28. Searls, D.: The linguistics of DNA. Am. Sci. 80, 579–591 (1992)

    Google Scholar 

  29. Searls, D.: The computational linguistics of biological sequences. In: Hunter, L. (ed.) Artificial Intelligence and Molecular Biology, pp. 47–120. MIT Press, Cambridge (1993)

    Google Scholar 

  30. Searls, D.: Linguistic approaches to biological sequences. Bioinformatics 13, 333–344 (1997)

    Article  Google Scholar 

  31. Shavlik, J., Towell, G., Noordewier, M.: Using neural networks to refine existing biological knowledge. Int. J. Genome Res. 1, 81–107 (1992)

    Google Scholar 

  32. Smith, T.C., Witten, I.H.: Learning Language Using Genetic Algorithms. In: Wermter, S., Scheler, G., Riloff, E. (eds.) IJCAI-WS 1995. LNCS, vol. 1040, Springer, Heidelberg (1996)

    Google Scholar 

  33. Stolzmann, W.: An Introduction to Anticipatory Classifier Systems. In: Lanzi, P.L., Stolzmann, W., Wilson, S.W. (eds.) IWLCS 1999. LNCS (LNAI), vol. 1813, pp. 175–194. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  34. Towell, G., Shavlik, J.: Extracting refined rules from knowledge-based neural networks. Machine Learning 13, 71–101 (1993)

    Google Scholar 

  35. Unold, O.: Context–free grammar induction using evolutionary methods. WSEAS Trans. on Circuits and Systems 3(2), 632–637 (2003)

    Google Scholar 

  36. Unold, O., Cielecki, L.: Grammar-based Classifier System. In: Hryniewicz, O., et al. (eds.) Issues in Intelligent Systems: Paradigms, pp. 273–286. EXIT Publishing House, Warsaw (2005)

    Google Scholar 

  37. Unold, O.: Playing a toy-grammar with GCS. In: Mira, J., Álvarez, J.R. (eds.) IWINAC 2005. LNCS, vol. 3562, pp. 300–309. Springer, Heidelberg (2005)

    Google Scholar 

  38. Unold, O.: Context-free grammar induction with grammar-based classifier system. Archives of Control Science, vol. 15 (LI) 4, 681–690 (2005)

    Google Scholar 

  39. Wilson, S.W.: Classifier Fitness Based on Accuracy. Evolutionary Computation 3(2), 147–175 (1995)

    Article  Google Scholar 

  40. Wyard, P.: Context Free Grammar Induction Using Genetic Algorithms. In: Belew, R.K., Booker, L.B. (eds.) Proceedings of the Fourth International Conference on Genetic Algorithms, San Diego, CA, pp. 514–518. Morgan Kaufmann, San Francisco (1991)

    Google Scholar 

  41. Zhou, H., Grefenstette, J.J.: Induction of Finite Automata by Genetic Algorithms. In: Proceedings of the 1986 International Conference on Systems, Man and Cybernetics, pp. 170–174 (1986)

    Google Scholar 

  42. Younger, D.: Recognition and parsing of context-free languages in time n3. University of Hawaii Technical Report, Department of Computer Science (1967)

    Google Scholar 

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Authors and Affiliations

  1. The Institute of Computer Engineering, Control and Robotics, Wroclaw University of Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland

    Olgierd Unold

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  1. Olgierd Unold
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Bartlomiej Beliczynski Andrzej Dzielinski Marcin Iwanowski Bernardete Ribeiro

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Unold, O. (2007). Grammar-Based Classifier System for Recognition of Promoter Regions. In: Beliczynski, B., Dzielinski, A., Iwanowski, M., Ribeiro, B. (eds) Adaptive and Natural Computing Algorithms. ICANNGA 2007. Lecture Notes in Computer Science, vol 4431. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71618-1_89

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  • DOI: https://doi.org/10.1007/978-3-540-71618-1_89

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-71589-4

  • Online ISBN: 978-3-540-71618-1

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