Name
Abstract | ||
|---|---|---|
Finding a biologically relevant sequence alignment may be difficult since several sequence alignments are possible, taking different parameters in consideration. A perceptron neuron can be used to associate weights to a set of alignment characteristics and to decide if two residues should be aligned. Finding a good set of weights can be a hard problem and simulated annealing can be used for this purpose but it can take a long time. In this paper, we propose a parallelization strategy for simulated annealing optimizing a Fragment Based Alignment in Linear Space (FBALS). The results were superior to the competing algorithm and the obtained speedups were compatible with the number of processing cores, indicating a good parallel strategy. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/IPDPSW.2012.80 | Parallel and Distributed Processing Symposium Workshops & PhD Forum |
Keywords | Field | DocType |
sequence alignment,simulated annealing,parallel simulated annealing,alignment characteristic,competing algorithm,good set,associate weight,parallelization strategy,good parallel strategy,linear space,biologically relevant sequence alignment,perceptron,perceptrons,biology,silicon,mathematical model,parallel processing,dynamic programming | Sequence alignment,Simulated annealing,Dynamic programming,Computer science,Parallel computing,Parallel processing,Linear space,Algorithm,Adaptive simulated annealing,Theoretical computer science,Perceptron | Conference |
ISSN | ISBN | Citations |
2164-7062 | 978-1-4673-0974-5 | 0 |
PageRank | References | Authors |
0.34 | 16 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jan Mendonca Correa | 1 | 9 | 1.28 |
| Alba Cristina Magalhaes Alves De Melo | 2 | 253 | 33.90 |
| Ricardo P. Jacobi | 3 | 90 | 16.50 |
| Azzedine Boukerche | 4 | 4301 | 418.60 |