- About this Journal ·
- Aims and Scope ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
ISRN Artificial Intelligence
Volume 2012 (2012), Article ID 178658, 6 pages
Simulated Annealing with Previous Solutions Applied to DNA Sequence Alignment
Facultad de Sistemas, Universidad Autónoma de Coahuila, Saltillo, Coahuila, 25280 México, Mexico
Received 1 July 2012; Accepted 25 July 2012
Academic Editors: M. F. Abbod, M. Arif, and P. Trunfio
Copyright © 2012 Ernesto Liñán-García and Lorena Marcela Gallegos-Araiza. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- R. M. Karp, “Mapping the genome: some combinatorial problems arising in molecular biology,” in Proceedings of the 25th Annual ACM Symposium on the Theory of Computing, pp. 278–285, May 1993.
- E. S. Lander, R. Langridge, and D. M. Saccocio, “Mapping and interpreting biological information,” Communications of the ACM, vol. 34, no. 11, pp. 33–39, 1991.
- L. Wang and T. Jiang, “On the complexity of multiple sequence alignment,” Journal of Computational Biology, vol. 1, no. 4, pp. 337–348, 1994.
- C. H. Papadimitriou and K. Steiglitz, Combinatorial Optimization: Algorithms and Complexity, Dover Publications, Mineola, NY, USA, 1998.
- J. Setubal and J. Meidanis, Introduction to Computational Molecular Biology, PWS Publishing, 1997.
- O. Gotoh, “An improved algorithm for matching biological sequences,” Journal of Molecular Biology, vol. 162, no. 3, pp. 705–708, 1982.
- S. B. Needleman and C. D. Wunsch, “A general method applicable to the search for similarities in the amino acid sequence of two proteins,” Journal of Molecular Biology, vol. 48, no. 3, pp. 443–453, 1970.
- I. Ö. Bucak and V. Uslan, “An analysis of sequence alignment: Heuristic algorithms,” in Proceedings of the 32nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC'10), pp. 1824–1827, September 2010.
- L. Chen, L. Zou, and J. Chen, “An efficient ant colony algorithm for multiple sequences alignment,” in Proceedings of the 3rd International Conference on Natural Computation (ICNC '07), pp. 208–212, August 2007.
- J. Kim, S. Pramanik, and M. J. Chung, “Multiple sequence alignment using simulated annealing,” Computer Applications in the Biosciences, vol. 10, no. 4, pp. 419–426, 1994.
- S.-M. Chen and C.-H. Lin, “Multiple DNA sequence alignment based on genetic simulated annealing techniques,” International Journal of Information and Management Sciences, vol. 18, no. 2, pp. 97–111, 2007.
- C. Notredame, D. G. Higgins, and J. Heringa, “T-coffee: a novel method for fast and accurate multiple sequence alignment,” Journal of Molecular Biology, vol. 302, no. 1, pp. 205–217, 2000.
- V. Cerny, “Thermodynamical approach to the traveling salesman problem: an efficient simulation algorithm,” Journal of Optimization Theory and Applications, vol. 45, no. 1, pp. 41–51, 1985.
- S. Kirkpatrick, C. D. Gelatt, and M. P. Vecchi, “Optimization by simulated annealing,” Science, vol. 220, no. 4598, pp. 671–680, 1983.
- E. Aarts and J. Korst, Simulated Annealing and Boltzmann Machines: a Stochastic Approach to Combinatorial Optimization And Neural Computing, Wiley-Interscience Series in Discrete Mathematics and Optimization, John Wiley & Sons, Chichester, UK, 1989.
- L. Ingber, “Simulated annealing: practice versus theory,” Mathematical and Computer Modelling, vol. 18, no. 11, pp. 29–57, 1993.
- U. Kjærulff, “Optimal decomposition of probabilistic networks by simulated annealing,” Statistics and Computing, vol. 2, no. 1, pp. 7–17, 1992.
- P. J. Van Laarhoven and E. H. L. Aarts, Simulated Annealing: Theory and Applications, Kluwer Academic Publishers, 1987.
- J. Frausto-Solis, E. F. Román, D. Romero, X. Soberon, and E. Liñán-García, “Analytically tuned simulated annealing applied to the protein folding problem,” Lecture Notes in Computer Science, vol. 4488, no. 2, pp. 370–377, 2007.
- J. Frausto-Solis, X. Soberon-Mainero, and E. Liñán-García, “MultiQuenching annealing algorithm for protein folding problem,” Lecture Notes in Computer Science, vol. 5845, pp. 578–589, 2009.
- J. Frausto-Solís, H. Sanvicente-Sánchez, and F. Imperial-Valenzuela, “Andymark: an analytical method to establish dynamically the length of the Markov chain in simulated annealing for the satisfiability problem,” Lecture Notes in Computer Science, vol. 4247, pp. 269–276, 2006.
- H. Sanvicente-Sánchez and J. Frausto-Solís, “A method to establish the cooling scheme in simulated annealing like algorithms,” Lecture Notes in Computer Science, vol. 3045, pp. 755–763, 2004.