A hybrid genetic algorithm for the protein folding problem using the 2D-HP lattice model

Studies in Computational Intelligence

Volumn 92, Issue , 2008, Pages 121-140

  Lopes, Heitor S ^a   Scapin, Marcos P ^a  

^a UNIVERSIDADE TECNOLÓGICA FEDERAL DO PARANÁ   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 41449092413     PISSN: 1860949X     EISSN: None     Source Type: Book Series    
DOI: 10.1007/978-3-540-76286-7_6     Document Type: Article

References (32)

1. Berger B, Leight T (1998) Protein folding in the hydrophobic-hydrophilic (HP) model is NP-complete. J Comput Biol 5:27-40
2. Unger R, Moult J (1993) On the applicability of genetic algorithms to protein folding. In: Proc. of IEEE 26th Hawaii Int. Conf. on System Sciences, vol. I, pp. 715-725
3. Unger R, Moult J (1993) A genetic algorithm for three dimensional protein folding simulations. In: Proc. of the 5th Annual Int. Conf. on Genetic Algorithms, pp. 581-588
4. Patton AL, Punch III WF, Goodman ED (1995) A standard GA approach to native protein conformation prediction. In: Proc. of the 6th Int. Conf. on Genetic Algorithms, pp. 574-581
5. Pedersen JT, Moult J (1997) Protein folding simulations with genetic algorithms and a detailed molecular description. J Mol Biol 269:240-259
6. Krasnogor N, Pelta D, Lopez PEM, Canal E (1998) Genetic algorithm for the protein folding problem: A critical view. In: Proc. of Engineering of Intelligent Systems, pp. 353-360
7. Day RO, Lamont GB, Pachter R (2003) Protein structure prediction by applying an evolutionary algorithm. In: Proc. of Int. Parallel and Distributed Processing Symp., pp. 155-162
8. Bitello R, Lopes HS (2006) A differential evolution approach for protein folding. In: Proc. IEEE Symp. on Computational Intelligence in Bioinformatics and Computational Biology, pp. 1-5
9. Shmygelska A, Hoos HH (2005) An ant colony optimisation algorithm for the 2D and 3D hydrophbic polar protein folding problem. BMC Bioinformatics 6:30-52
10. Dill KA (1985) Theory for the folding and stability of globular proteins. Biochemistry 24:1501-1509
11. Jiang T, Cui Q, Shi G, Ma S (2003) Protein folding simulations of the hydrophobic-hydrophilic model by combining tabu search with genetic algorithms. J Chem Phys 119:4592-4596
12. König R, Dandekar T (1999) Improving genetic algorithms for protein folding simulations by systematic crossover. Biosystems 50:17-25
13. Dill KA, Bromberg S, Yue K, Fiebig KM, Yee DP, Thomas PD, Chan HS (1995) Principles of protein folding - a perspective from simple exact models. Protein Sci 4:561-602
14. Crescenzi P, Goldman D, Papadimitriou C, Piccolboni A, Yannakakis M (1998) On the complexity of protein folding. J Comput Biol 5:423-465
15. Michalewicz Z (1996) Genetic Algorithms + Data Structures = Evolution Programs, 3rd edition. Springer, Berlin
16. Piccolboni A, Mauri G (1998) Application of evolutionary algorithms to protein folding prediction. Lect Notes Comput Sci 1363:123-136
17. Krasnogor N, Hart WE, Smith J, Pelta DA (1999) Protein structure prediction with evolutionary algorithms. In: Proc. Int. Genetic and Evolutionary Computation Conf., pp. 1596-1601
18. Koza JR (1992) Genetic Programming: On the Programming of Computers by Means of Natural Selection. MIT, Cambridge
19. Beer FP, Johnston ER (1980) Vector Mechanics for Engineers - Statics. McGraw Hill, New York
20. Cox GA, Mortimer-Jones TV, Taylor RP, Johnston RL (2004) Development and optimisation of a novel genetic algorithm for studying model protein folding. Theor Chem Acc 112:163-178
21. Hoque MT, Chetty M, Dooley LS (2006) A guided genetic algorithm for protein folding prediction using 3D hydrophobic-hydrophilic model. In: Proc. IEEE Congr. on Evolutionary Computation, pp. 2339-2346
22. Lesh N, Mitzenmacher M, Whitesides S (2003) A complete and effective move set for simple protein folding. In: Proc. 7th Ann. Int. Conf. Research in Computational Molecular Biology, pp. 188-195
23. Lehninger AL, Nelson DL, Cox MM (1998) Principles of Biochemistry, 2nd edition. Worth, New York
24. Croes GA (1958) A method for solving traveling salesman problems. Oper Res 6:791-812
25. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE (2000) The protein data bank. Nucleic Acids Res 28:235-242
26. Deb K (2000) Multi-Objective Optimization Using Evolutionary Algorithms. Wiley, Chichester
27. Unger R, Moult J (1993) Genetic algorithms for protein folding simulations. J Mol Biol 231:75-81
28. Chikenji G, Kikuchi M, Iba Y (1999) Multi-self-overlap ensemble for protein folding: Ground state search and thermodynamics. Phys Rev Lett 83:1886-1889
29. Liang F, Wong WH (2001) Evolutionary Monte Carlo for protein folding simulations. J Chem Phys 115:3374-3380
30. Maruo MH, Lopes HS, Delgado MRBS (2005) Self-adapting evolutionary parameters: Encoding aspects for combinatorial optimization problems. Lect Notes Comput Sci 3448:154-165
31. Armstrong Jr. NB, Lopes HS, Lima CRE (2007) Reconfigurable Computing for Accelerating Protein Folding Simulations. Lect Notes Comput Sci 4419:314-32
32. Tantar A-A, Melab N, Talbi E-G, Parent B, Horvath D (2007) A parallel hybrid genetic algorithm for protein structure prediction on the grid. Future Gen Comput Syst 23(3):398-409