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...
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ISBN:
(纸本)9780769546766
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 then deciding if two residues should be aligned. Finding a good set of weights can be a hard problem and simulated annealing can be used to find a good set but can take a long time. In this paper, we propose a parallelization strategy for simulated annealing optimizing a Fragment Based Alignment in linearspace (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.
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