doi: 10.7763/IJMO.2012.V2.143
An Enhanced Solution to the Protein Folding Problem Using a Hybrid Genetic Algorithm with G-Bit Improvement Strategy
M. V. Judy
1
,
B Ramadoss
2
- 1 Amrita School of Arts and Sciences, Kochi, Kerala India.
- 2 Master of Computer Application department, National Institute of technology, Trichy, India
Abstract
The protein-folding problem (PFP) that is predicting the functional conformation of a protein from its amino acid sequence remains as a central problem in computational biology and it is a combinatorial optimization problem. Genetic algorithms (GA) have proved to be a successful method for predicting the protein structure. In this paper, we propose a novel hybrid genetic algorithm and we implement it for protein folding problem. In this approach, we simply allow the genetic algorithm to run to substantial convergence and then permit the local optimization procedure to take over. Genetic algorithm finds the hills and a more canonical method of local search; the Gradient like-bit wise (G-bit) improvement is used to climb the hill. We have demonstrated the superiority of our hybrid genetic algorithm for several instances of the protein-folding problem, which not only finds the optimum solution, but also finds them faster than the traditional genetic algorithms.
Keywords
- Evolutionary algorithms
- G-bit improvement
- Hybrid GA
- protein structure prediction
How to Cite
M. V. Judy and B Ramadoss, "An Enhanced Solution to the Protein Folding Problem Using a Hybrid Genetic Algorithm with G-Bit Improvement Strategy," International Journal of Modeling and Optimization, vol. 2, no. 3, pp. 356-359, 2012. https://doi.org/ 10.7763/IJMO.2012.V2.143
Copyright & License
Copyright © 2012 by the authors. 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 (CC BY 4.0).