Parallel Protein Structure Prediction by Multiobjective Optimization
PDP '09 Proceedings of the 2009 17th Euromicro International Conference on Parallel, Distributed and Network-based Processing
Considerations in engineering parallel multiobjective evolutionary algorithms
IEEE Transactions on Evolutionary Computation
Combining protein fragment feature-based resampling and local optimisation
PRIB'13 Proceedings of the 8th IAPR international conference on Pattern Recognition in Bioinformatics
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Proteins are one of the most vital macromolecules on the cellular level. In order to understand the function of a protein, its structure needs to be determined. For this purpose, different computational approaches have been introduced. Genetic algorithms can be used to search the vast space of all possible conformations of a protein in order to find its native structure. A framework for design of such algorithms that is both generic, easy to use and performs fast on distributed systems may help further development of genetic algorithm based approaches. We propose such a framework based on a parallel master-slave model which is implemented in C++ and Message Passing Interface. We evaluated its performance on distributed systems with a different number of processors and achieved a linear acceleration in proportion to the number of processing units.