Constraint based methods for biological sequence analysis

Journal of Universal Computer Science

Volumn 12, Issue 11, 2006, Pages 1500-1520

  Bavarian, Maryam ^a   Dahl, Veronica ^a  

^a SIMON FRASER UNIVERSITY   (Canada)

Author keywords

Concept formation; Constraint handling rule grammars; Constraint handling rules; Gene prediction; Protein structure; RNA secondary structure

Indexed keywords

EID: 33846043039     PISSN: 0958695X     EISSN: 09486968     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (31)

1. Abramson, H., Dahl, V.,Logic Grammars, Springer-Verlag, 1989.
2. Andronescu, M., Fejes, A.P., Hutter, F., Hoos, H.H.,Condon, A., A new algorithm for RNA secondary structure design, Journal of Mol. Bio. 336(3), 607-624, 2004.
3. Baldi, P., Bioinformatics: the machine learning approach, Cambridge, Mass. :MIT Press, 1998.
4. Barranco-Mendoza, A., Stochastic and Heuristic Modelling for Analysis of the Growth of Pre-Invasive Lesions and for a Multidisciplinary Approach to Early Cancer Diagnosis, Ph.D. Thesis, Simon Fraser University, Burnaby, BC, 2005.
5. Barranco-Mendoza, A., Persaoud, D.R. and Dahl, V. A property-based model for lung cancer diagnosis, 8th Annual Int. Conf. on Computational Molecular Biology, RECOMB 2004, San Diego, California, March 27-31 (accepted poster), 2004.
6. Bavarian, M., Dahl, V., RNA secondary structure design using Constraint Handling Rules, WCB 2005.
7. Bes, G. and Blache, P., Proprieties et analyse d'un langage, In Proc. TALN99, 1999.
8. Bes, G., Dahl, V., Guillot, D., Lamadon, L., Milutinovici. I. and Paulo, J., A parsing system for balanced parenthesis in NL texts. Poster and Demo at the Lorraine-Saarland Workshop on Prospects and Advances in the Syntax/Semantics Interface, Loria-Nancy, 2003.
9. Blache, P. and Balfourier, J. M., Property Grammars: a Flexible Constraint-based Approach to Parsing, In Proc. IWPT-2001, 2001.
10. Christiansen, H., CHR as Grammar Formalism, a First Report, In Sixth Annual Workshop of the ERCIM Working Group on Constraints, Apt, K.R., Bartak, R., Monfroy, E., Rossi, F., (eds.), Prague, 2001.
11. Christiansen, H., Logical Grammars Based on Constraint Handling Rules,(Poster abstract). In Proc. 18th International Conference on Logic Programming, Stuckey, P. (ed.) Lecture Notes in Computer Science, 2401, Springer-Verlang, p. 481, 2002.
12. Christiansen, H. CHR Grammars, International Journal in Theory and Practice of Logic Programming, special issue on Constraint Handling Rules, 2005.
13. Cohen, J., Computational Molecular Biology: A Premising Application Using Logic Programming and Constraint Logic Programming, Lecture Notes in Artificial Intelligence, 1999.
14. Dahl, V. and Blache, P., Directly Executable Constraint Based Grammars,In Proc. Journees Francophones de Programmation en Logique avec Contraintes, Angers, France, 149-166, 2004.
15. Dahl, V. and Tarau, P.,Assumptive Logic Programming, In Proc. ASAI 2004, Cordoba, Argentina, 2004.
16. Dahl, V., Tarau, P., and Li, R., Assumption Grammars for Processing Natural Language. In Proc. Fourteenth International Conference on Logic Programming, MIT Press, 256-270, 1997.
17. Dahl, V. and Voll, K., Concept Formation Rules: An Executable Cognitive Model of Knowledge Construction, In Proc. First International Workshop on Natural Language Understanding and Cognitive Sciences (NLUCS'04), Porto, Portugal, April 2004.
18. Frühwirth, T., User-Defined Constraint Handling, Poster, International Conference on Logic Programming (ICLP 93), Budapest, Hungary, MIT Press, June 1993.
19. Frühwirth, T. W., Theory and Practice of Constraint Handling Rules,In Journal of Logic Programming, 37:95-138, 1998.
20. Hofacker, I.L., Fontana, W., Stadler, P.F., Bonhoeffer, S., Tacker, M., Schuster, P., Fast Folding and Comparison of RNA Secondary Structures, Monatshefte f. Chemie 125:167-188, 1994.
21. Muggleton, S., Inductive logic programming, Proceedings of the ILP-91 international workshop, Vianna, de Castelo, Portugal, 2-4 March 1991.
22. Muggleton, S.,King,R.D., Sternberg.,M. J.E.,Protein secondary structure, prediction using logic-based machine learning, Protein Engineering, 5:647-657, 1992.
23. Overbeek, R.A., Invited Tutorial: Logic Programming and Genetic Sequence Analysis, JICSLP, Washington, DC,1992.
24. Sakakibara, Y., Brown, M., Hughey, R., Mian, S., Sjolander, K., Underwood, R., Haussler, D. Stochastic Context-Free Grammars for tRNA Modeling, Nucleic Acids Research. 1994 Nov 25;22(23):5112-20.
25. Searls, D.B., The computational linguistics of biological sequences, Artificial intelligence and molecular biology, American Association for Artificial Intelligence, p 47-120, 1993.
26. Searls, D.B., Grand challenges in computational biology, In Computational methods in molecular biology, S. L. Salzberg, D. B. Searls and s. Kasif, Eds. Elsevier Amsterdam, The Netherlands, 1998.
27. Schulze-Kremer, S., Molecular bioinformatics: algorithms and applications, Water de Gruyter, New York 1996, p12.
28. Voll, K., A Methodology of Error Detection: Improving Speech Recognition in Radiology, PhD thesis, Simon Fraser University, 2006.
29. Waterman, M. S., Introduction to computational molecular biology: Maps, sequences and genome,Chapman&Hall, p327-340, 1995.
30. Zahariev, M., Dahl, V. and Levesque, A. (Technical Report), Efficient Algorithms for the Discovery of Oligonucleotide signatures for DNA Sequences and Groups of Sequences.
31. Zuker, M., Sciences 244, 48-52, 1989.