Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Keywords |
|---|---|---|
2011 | ICA3PP (2) | parallel master-slave model,possible conformation,linear acceleration,genetic algorithm,cellular level,vast space,message passing interface,different number,protein optimisation,generic parallel genetic algorithm,native structure,different computational approach |
Field | DocType | Volume |
Protein structure prediction,Parallel genetic algorithm,Computer science,Parallel computing,Theoretical computer science,Message Passing Interface,Acceleration,Genetic algorithm,Distributed computing | Conference | 7017 |
ISSN | Citations | PageRank |
0302-9743 | 1 | 0.38 |
References | Authors | |
4 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lukas Folkman | 1 | 20 | 2.83 |
| Wayne J. Pullan | 2 | 232 | 12.73 |
| Bela Stantic | 3 | 198 | 38.54 |