BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Predictor@Home: A "Protein Structure Prediction Supercomputer' Based on Global Computing
IEEE Transactions on Parallel and Distributed Systems
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
A parallel hybrid genetic algorithm for protein structure prediction on the computational grid
Future Generation Computer Systems
Multiobjective Optimization in Bioinformatics and Computational Biology
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Advances in Rosetta protein structure prediction on massively parallel systems
IBM Journal of Research and Development
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Considerations in engineering parallel multiobjective evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Off-lattice protein structure prediction with homologous crossover
Proceedings of the 15th annual conference on Genetic and evolutionary computation
| Hi-index | 0.00 |
Protein structure prediction (PSP) is an open problem with many useful applications in disciplines such as medicine, biology and biochemistry. As this problem presents a vast search space and the analysis of each protein structure requires a significant amount of computing time, it is necessary to take advantage of high-performance parallel computing platforms as well as to define efficient search procedures in the space of possible protein conformations. In this paper we compare two parallel procedures for PSP which are based on different multi-objective optimization approaches, i.e. PAES (Knowles and Corne in Proc. Congr. Evol. Comput. 1:98---105, 1999) and NSGA2 (Deb et al. in IEEE Trans. Evol. Comput. 6:182---197, 2002). Although both procedures include techniques to take advantage of known protein structures and strategies to simplify the search space through the so-called rotamer library and adaptive mutation operators, they present different profiles with respect to their implicit parallelism.