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Evolutionary algorithm based on quantum computing and multiple sequence alignment method

Author: LinQiuLi
Tutor: HuoHongWei
School: Xi'an University of Electronic Science and Technology
Course: Computer Software and Theory
Keywords: Bioinformatics Multiple sequence alignment Adaptive Genetic Algorithm Quantum evolutionary algorithm AGAMSA QEAMSA
CLC: TP301.6
Type: Master's thesis
Year: 2006
Downloads: 194
Quote: 2
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Abstract


Multiple sequence alignment (Multiple Sequence alignment-MSA) is the most important bioinformatics , but also one of the most challenging tasks . Although many of the current comparison method proposed, but in terms of accuracy and efficiency is still not perfect, therefore , need to be further improved compared to the existing methods and to explore new methods compared . This paper studied the existing alignment method, proposed by adaptive genetic algorithm (Adaptive Genetic Algorithm-AGA) and quantum evolutionary algorithm (Quantum Evolution Algorithm-QEA) to solve the MSA problem . Thesis presents two comparison methods : AGAMSA and QEAMSA. AGAMSA MSA problem genetic algorithm is one of the ways , the difference is : the algorithm for the MSA problem, using only the space coding method reduces the storage space ; designed five new genetic operators , and 22 kinds of SAGA algorithm operators were reduced compared to the complexity of operations , but also improve the convergence speed ; introduction of adaptive strategies to balance the convergence speed and the contradiction between the global optimum . QEAMSA proposed a new method of comparison , which is a reconstruction algorithm to do the basic QEA : the new Q-bit representation of the problem represented by MSA , designed for the problem to the individual quantum update method ; in order to avoid QEA strong randomness disadvantages operator introduces an optimized , so QEA MSA used to solve the problem better . Finally, two algorithms are tested Balibase respectively compared to the library five test cases with different characteristics subset Ref1 ~ Ref5, the test results and the currently accepted CLUSTALX and SAGA geometric methods have been published on the test results were comparison , the results showed that : AGAMSA and QEAMSA right Ref1 and Ref5 test results inferior CLUSTALX and SAGA and other methods ; right Ref2 ~ Ref4 test results better than CLUSTALX and SAGA and other methods. For all of the test subset , QEAMSA are superior AGAMSA. Experimental results show that : AGAMSA and QEAMSA are valid for multiple sequence alignment method is more suitable for comparison with orphans alignments and contains N / C terminal alignments .

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