Parallel Simulated Annealing for Fragment Based Sequence Alignment

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.