An analysis of dynamic mutation operators for conformational sampling

Studies in Computational Intelligence

Volumn 210, Issue , 2009, Pages 291-323

  Tantar, Alexandru Adrian ^a   Melab, Nouredine ^a   Talbi, El Ghazali ^a  

^a INRIA   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 77952768362     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-642-01262-4_11     Document Type: Article

References (49)

1. Alba, E., Tomassini, M.: Parallelism and evolutionary algorithms. IEEE Trans. Evolutionary Computation 6(5), 443-462 (2002)
2. Alba, E., Gluque, E. G. T., Melab, N.: Metaheuristics and parallelism. In: Alba, E. (ed.) Parallel Metaheuristics. Wiley Series on Parallel and Distributed Computing. Wiley, Chichester (2005)
3. Anfinsen, C. B., Haber, E., Sela, M., White, F. H.: The Kinetics of Formation of Native Ribonuclease During Oxidation of the Reduced Polypeptide Chain. Proceedings of the National Academy of Sciences of the United States of America 47(9), 1309-1314 (1961)
4. Blundell, T. L., Sibanda, B. L., Sternberg, M. J., Thornton, J. M.: Knowledge-based prediction of protein structures and the design of novel molecules. Nature 326(6111), 347-352 (1987)
5. Branke, J., Chick, S. E., Schmidt, C.: New developments in ranking and selection: an empirical comparison of the three main approaches. In: WSC 2005: Proceedings of the 37th Conference on Winter Simulation, pp. 708-717. ACM, New York (2005)
6. Branke, J., Chick, S. E., Schmidt, C.: Selecting a selection procedure. Management Science 53(12), 1916-1932 (2007)
7. Byrd, R. H., Lu, P., Nocedal, J., Zhu, C. Y.: A limited memory algorithm for bound constrained optimization. SIAM Journal on Scientific Computing 16(6), 1190-1208 (1995)
8. Cahon, S., Melab, N., Talbi, E. G.: Paradiseo: A framework for the reusable design of parallel and distributed metaheuristics. Journal of Heuristics 10(3), 357-380 (2004)
9. Cahon, S., Melab, N., Talbi, E. G.: An enabling framework for parallel optimization on the computational grid. In: CCGRID, pp. 702-709 (2005)
10. Cantu-Paz, E.: Efficient and Accurate Parallel Genetic Algorithms. Kluwer Academic Publishers, Norwell (2000)
11. Cappello, F., Caron, E., Dayde, M., Desprez, F., Jegou, Y., Primet, P., Jeannot, E., Lanteri, S., Leduc, J., Melab, N., Mornet, G., Namyst, R., Quetier, B., Richard, O.: Grid'5000: a large scale and highly reconfigurable grid experimental testbed. In: The 6th IEEE/ACM International Workshop on Grid Computing, pp. 99-106 (2005)
12. Chen, C., Lin, J., Yücesan, E., Chick, S. E.: Simulation budget allocation for further enhancing the efficiency of ordinal optimization. Journal of Discrete Event Dynamic Systems: Theory and Applications 10, 251-270 (2000)
13. Chen, C. H.: A lower bound for the correct subset-selection probability and its application to discrete event system simulations. IEEE Transactions on Automatic Control 41(8), 1227-1231 (1996)
14. Chick, S. E., Inoue, K.: New results on procedures that select the best system using crn. In: Simulation Conference Proceedings, vol. 1, pp. 554-561 (2000)
15. Cozzone, A. J.: Proteins: Fundamental chemical properties. Encyclopedia of Life Sciences, pp. 1-10. Macmillan Publishers Ltd, Nature Publishing Group (2002), www.els.net
16. Dauber-Osguthorpe, P., Roberts, V. A., Osguthorpe, D. J., Wolff, J., Genest, M., Hagler, A. T.: Structure and energetics of ligand binding to proteins: Escherichia coli dihydrofolate reductase-trimethoprim, a drug-receptor system. Proteins: Structure, Function, and Genetics 4(1), 31-47 (1988)
17. Dill, K. A.: Theory for the folding and stability of globular proteins. Biochemistry 24(6), 1501-1509 (1985)
18. Gropp, W.: Mpich2: A new start for mpi implementations. In: Proceedings of the 9th European PVM/MPI Users' Group Meeting on Recent Advances in Parallel Virtual Machine and Message Passing Interface, p. 7. Springer, London (2002)
19. Gropp, W., Lederman, S. H., Lumsdaine, A., Lusk, E., Nitzberg, B., Saphir, W., Snir, M.: MPI: The Complete Reference, The MPI-2 Extensions, vol. 2. MIT Press, Cambridge (1998)
20. Heinrich, J.: A guide to the Pearson Type IV distribution (2004)
21. Herrera, F., Lozano, M., Verdegay, J. L.: Fuzzy connective based crossover operators to model genetic algorithms population diversity. Tech. Rep. DECSAI-95110, University of Granada (1995)
22. Herrera, F., Lozano, M., Verdegay, J.: Dynamic and heuristic fuzzy connectives-based crossover operators for controlling the diversity and convengence of real-coded genetic algorithms (1996)
23. Herrera, F., Lozano, M., Verdegay, J. L.: Fuzzy connectives based crossover operators to model genetic algorithms population diversity. Fuzzy Sets Syst. 92(1), 21-30 (1997)
24. Herrera, F., Lozano, M., Sánchez, A. M.: A taxonomy for the crossover operator for realcoded genetic algorithms: An experimental study. International Journal of Intelligent Systems 18(3), 309-338 (2003)
25. Hestenes, M. R.: Iterative methods for solving linear equations. Report 52-9, NAML (1951); Reprinted in the Journal of Optimization Theory and Applications 11, 323-334 (1973)
26. Hestenes, M. R., Stiefel, E.: Methods of conjugate gradients for solving linear systems. Journal of Research of the National Bureau of Standards 49(6), 409-436 (1952)
27. Ingber, L.: Adaptive simulated annealing (ASA): Lessons learned. Control and Cybernetics 25, 33-54 (1996) (Pubitemid 126087766)
28. Ingber, L.: Adaptive simulated annealing (asa) and path-integral (pathint) algorithms: Generic tools for complex systems. Tech. rep., Lester Ingber Research, Chicago, IL (2001)
29. Joy, S., Nair, P. S., Hariharan, R., Pillai, M. R.: Detailed comparison of the protein-ligand docking efficiencies of gold, a commercial package and arguslab, a licensable freeware. Silico Biology 6(6), 601-605 (2006)
30. Linlin Qiu, S. J. H.: Internal friction in the ultrafast folding of the tryptophan cage. Chemical Physics 1(312), 327-333 (2005)
31. Michalewicz, Z.: Genetic algorithms + data structures = evolution programs, 2nd edn. Springer, New York (1994)
32. Morris, G. M., Goodsell, D. S., Halliday, R. S., Huey, R., Hart, W. E., Belew, R. K., Olson, A. J.: Automated docking using a lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry 19(14), 1639-1662 (1999)
33. Nagahara, Y.: The PDF and CF of Pearson type IV distributions and the ML estimation of the parameters. Statistics & Probability Letters 43(3), 251-264 (1999)
34. Nagahara, Y.: A method of simulating multivariate nonnormal distributions by the pearson distribution system and estimation. Computational Statistics & Data Analysis 47(1), 1-29 (2004)
35. Neumaier, A.: Molecular modeling of proteins and mathematical prediction of protein structure. SIAM Review 39(3), 407-460 (1997)
36. Parent, B., Tantar, A., Melab, N., Talbi, E. G., Horvath, D.: Grid-based evolutionary strategies applied to the conformational sampling problem. In: IEEE Congress on Evolutionary Computation pp. 291-296 (2007)
37. Ponder, J. W., Case, D. A.: Force fields for protein simulations. Advances in Protein Chemistry 66, 27-85 (2003)
38. Rabow, A. A., Scheraga, H. A.: Improved genetic algorithm for the protein folding problem by use of a Cartesian combination operator. Protein Sci. 5(9), 1800-1815 (1996)
39. Rosin, C. D., Halliday, R. S., Hart, W. E., Belew, R. K.: A comparison of global and local search methods in drug docking. In: Bäck, T. (ed.) Proceedings of the Seventh International Conference on Genetic Algorithms (ICGA 1997). Morgan Kaufmann, San Francisco (1997)
40. Schmidt, C., Branke, J., Chick, S. E.: Integrating techniques from statistical ranking into evolutionary algorithms. In: Rothlauf, F., Branke, J., Cagnoni, S., Costa, E., Cotta, C., Drechsler, R., Lutton, E., Machado, P., Moore, J. H., Romero, J., Smith, G. D., Squillero, G., Takagi, H. (eds.) EvoWorkshops 2006. LNCS, vol. 3907, pp. 752-763. Springer, Heidelberg (2006)
41. Snow, C. D., Qiu, L., Du, D., Gai, F., Hagen, S. J., Pande, V. S.: Trp zipper folding kinetics by molecular dynamics and temperature-jump spectroscopy. Proc. Natl. Acad. Sci. U S A 101(12), 4077-4082 (2004)
42. Stewart, C. A., Müller, M. S., Lingwall, M.: Progress towards petascale applications in biology: Status in 2006. In: Euro-Par Workshops, pp. 289-303 (2006)
43. Talbi, E. G.: A taxonomy of hybrid metaheuristics. Journal of Heuristics 8(5), 541-564 (2002)
44. Tantar, A. A., Melab, N., Talbi, E. G.: A grid-based genetic algorithm combined with an adaptive simulated annealing for protein structure prediction. Soft Computing 12(12), 1185-1198 (2008)
45. Tantar, A. A., Melab, N., Talbi, E. G., Parent, B., Horvath, D.: A parallel hybrid genetic algorithm for protein structure prediction on the computational grid. Future Generation Computer Systems (in press)
46. Tavares, J., Tantar, A. A., Melab, N., Talbi, E. G.: The influence of mutation on proteinligand docking optimization: a locality analysis. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 589-598. Springer, Heidelberg (2008)
47. Thomsen, R.: Flexible ligand docking using evolutionary algorithms: investigating the effects of variation operators and local search hybrids. Biosystems 72 (1-2), 57-73 (2003)
48. Yao, X., Liu, Y., Lin, G.: Evolutionary programming made faster. IEEE Transactions on Evolutionary Computation 3(2), 82-102 (1999)
49. Zhu, C., Byrd, R. H., Lu, P., Nocedal, J.: Algorithm 778: L-BFGS-B: Fortran subroutines for large-scale bound-constrained optimization. ACM Trans. Math. Softw. 23(4), 550-560 (1997)