Abstract
Multiple sequence alignment is one of fundamental problems in bioinformatics, and to design a targeted and effective algorithm for multiple DNA, RNA or protein sequences. The research is to find out the maximum similarity matching between them, whether it should be homologous. In this paper, the invasive weed optimization (IWO) algorithm is combined with GA for multiple sequence alignment, in which IWO algorithm is used to improve the ability of global search. Furthermore, the optimal preservation strategy is used into the proposed algorithm. Comparing two test sequence sets, the results show that the proposed algorithm is effective and reliable.
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Acknowledgment
This work is supported by the National Natural Science Foundation of China (Nos. 61425002, 61751203, 61772100, 61702070, 61672121, 61572093), Program for Changjiang Scholars and Innovative Research Team in University (No. IRT_15R07), the Program for Liaoning Innovative Research Team in University (No. LT2015002).
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Gao, C., Wang, B., Zhou, C., Zhang, Q., Yin, Z., Fang, X. (2018). Hybrid Invasive Weed Optimization and GA for Multiple Sequence Alignment. In: Qiao, J., et al. Bio-inspired Computing: Theories and Applications. BIC-TA 2018. Communications in Computer and Information Science, vol 952. Springer, Singapore. https://doi.org/10.1007/978-981-13-2829-9_8
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DOI: https://doi.org/10.1007/978-981-13-2829-9_8
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