Abstract
For multiple sequence alignment problem in molecular biological sequence analysis, a hybrid genetic algorithm and an associated software package called HGA-COFFEE are presented. The COFFEE function is used to measure individual fitness, and five novel genetic operators are designed, a selection operator, two crossover operators and two mutation operators. One of the mutation operators is designed based on the COFFEE’s consistency information that can improve the global search ability, and another is realized by dynamic programming method that can improve individuals locally. Experimental results of the 144 benchmarks from the BAliBASE show that the proposed algorithm is feasible, and for datasets in twilight zone and comprising N/C terminal extensions, HGA-COFFEE generates better alignment as compared to other methods studied in this paper.
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Liu, Lf., Huo, Hw., Wang, Bs. (2005). HGA-COFFEE : Aligning Multiple Sequences by Hybrid Genetic Algorithm. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_56
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DOI: https://doi.org/10.1007/11527503_56
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
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