Multiple DNA sequences alignment by means of genetic algorithm
Design and application of hybrid intelligent systems
Parallelization of multiple genome alignment
HPCC'05 Proceedings of the First international conference on High Performance Computing and Communications
Pareto Optimal Pairwise Sequence Alignment
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Dot matrices and genetics algorithms for MSA
Proceedings of the 2013 Summer Computer Simulation Conference
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Multiple biomolecular sequence alignment is among the most important and challenging tasks in computational biology. It is characterized by great complexity in processing time. In this paper, a multiple-sequence alignment system is reported which combines the techniques of genetic algorithms and pairwise dynamic programming. Genetic algorithms are stochastic approaches for efficient and robust search. By converting biomolecular sequence alignment into a problem of searching for an optimal or a near-optimal point in a solution space, a genetic algorithm is used to find match blocks very efficiently. A pairwise dynamic programming is then applied to the subsequences between the match blocks. Combining the strengths of the two methods, the system achieves high efficiency and high alignment quality. In this paper, the system is described in detail. The system's performance is analyzed and the experimental results are presented