A fast quantum mechanical algorithm for database search
STOC '96 Proceedings of the twenty-eighth annual ACM symposium on Theory of computing
Explorations in quantum computing
Explorations in quantum computing
Multiple sequence alignment using tabu search
APBC '04 Proceedings of the second conference on Asia-Pacific bioinformatics - Volume 29
Algorithms for quantum computation: discrete logarithms and factoring
SFCS '94 Proceedings of the 35th Annual Symposium on Foundations of Computer Science
IEEE Transactions on Evolutionary Computation
Multiple sequence alignment by quantum genetic algorithm
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Quantum-inspired evolutionary algorithms: a survey and empirical study
Journal of Heuristics
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This paper describes a novel approach to deal with multiple sequence alignment (MSA). MSA is an essential task in bioinformatics which is at the heart of denser and more complex tasks in biological sequence analysis. MSA problem still attracts researcher’s attention despite the significant research effort spent to solve it. We propose in this paper a quantum evolutionary algorithm to improve solutions given by CLUSTALX package. The contribution consists in defining an appropriate representation scheme that allows applying successfully on MSA problem some quantum computing principles like qubit representation and superposition of states. This representation scheme is embedded within an evolutionary algorithm leading to an efficient hybrid framework which achieves better balance between exploration and exploitation capabilities of the search process. Experiments on a wide range of data sets have shown the effectiveness of the proposed framework and its ability to improve by many orders of magnitude the CLUSTALX’s solutions.