Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment

Multiple sequence alignment, known as NP-complete problem, is among the most important and challenging tasks in computational biology. For multiple sequence alignment, it is difficult to solve this type of problems directly and always results in exponential complexity. In this paper, we present a novel algorithm of genetic algorithm with ant colony optimization for multiple sequence alignment. The proposed GA-ACO algorithm is to enhance the performance of genetic algorithm (GA) by incorporating local search, ant colony optimization (ACO), for multiple sequence alignment. In the proposed GA-ACO algorithm, genetic algorithm is conducted to provide the diversity of alignments. Thereafter, ant colony optimization is performed to move out of local optima. From simulation results, it is shown that the proposed GA-ACO algorithm has superior performance when compared to other existing algorithms.

[1]  Yi Wang,et al.  An adaptive and iterative algorithm for refining multiple sequence alignment , 2004, Comput. Biol. Chem..

[2]  Andrew K. C. Wong,et al.  A genetic algorithm for multiple molecular sequence alignment , 1997, Comput. Appl. Biosci..

[3]  Tao Jiang,et al.  On the Complexity of Multiple Sequence Alignment , 1994, J. Comput. Biol..

[4]  H. Schwefel,et al.  \genetic Local Search Algorithms for the Traveling Salesman Problem," in Parallel Problem Solving from Nature Edited , 2022 .

[5]  Chou-Yuan Lee,et al.  Efficiently solving general weapon-target assignment problem by genetic algorithms with greedy eugenics , 2003, IEEE Trans. Syst. Man Cybern. Part B.

[6]  D. Higgins,et al.  RAGA: RNA sequence alignment by genetic algorithm. , 1997, Nucleic acids research.

[7]  J. Stoye.  Multiple sequence alignment with the Divide-and-Conquer method. , 1998, Gene.

[8]  Edmund K. Burke,et al.  Hybrid evolutionary techniques for the maintenance scheduling problem , 2000 .

[9]  Mitsuo Gen,et al.  Genetic algorithms and engineering design , 1997 .

[10]  Toshio Shimizu,et al.  Multiple Sequence Alignment Using a Genetic Algorithm , 1996 .

[11]  Gary B. Fogel,et al.  A Clustal alignment improver using evolutionary algorithms , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[12]  S. Su,et al.  A genetic algorithm with domain knowledge for weapon‐target assignment problems , 2002 .

[13]  Olivier Poch,et al.  A comprehensive comparison of multiple sequence alignment programs , 1999, Nucleic Acids Res..

[14]  Erwin Pesch,et al.  Genetic Local Search in Combinatorial Optimization , 1994, Discret. Appl. Math..

[15]  Bernd Freisleben,et al.  Fitness landscape analysis and memetic algorithms for the quadratic assignment problem , 2000, IEEE Trans. Evol. Comput..

[16]  J. Davies,et al.  Molecular Biology of the Cell , 1983, Bristol Medico-Chirurgical Journal.

[17]  Kumar Chellapilla,et al.  Multiple sequence alignment using evolutionary programming , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[18]  Licheng Jiao,et al.  A novel genetic algorithm based on immunity , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[19]  Marco Dorigo,et al.  The ant colony optimization meta-heuristic , 1999 .

[20]  Olivier Poch,et al.  RASCAL: Rapid Scanning and Correction of Multiple Sequence Alignments , 2003, Bioinform..

[21]  Pablo Moscato.  A memetic approach for the travelling salesman problem implementation of a computational ecology for , 1992 .

[22]  M. A. McClure,et al.  Comparative analysis of multiple protein-sequence alignment methods. , 1994, Molecular biology and evolution.

[23]  Thomas Stützle,et al.  Ant Colony Optimization Theory , 2004 .

[24]  D. Lipman,et al.  The multiple sequence alignment problem in biology , 1988 .

[25]  S F Altschul,et al.  Weights for data related by a tree. , 1989, Journal of molecular biology.

[26]  Liming Cai,et al.  Evolutionary computation techniques for multiple sequence alignment , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[27]  D. E. Goldberg,et al.  Genetic Algorithm in Search , 1989 .

[28]  D. Higgins,et al.  SAGA: sequence alignment by genetic algorithm. , 1996, Nucleic acids research.

[29]  R. Doolittle,et al.  Progressive sequence alignment as a prerequisitetto correct phylogenetic trees , 2007, Journal of Molecular Evolution.

[30]  Moon-Jung Chung,et al.  Multiple sequence alignment using simulated annealing , 1994, Comput. Appl. Biosci..

[31]  Jens Stoye,et al.  DCA: an efficient implementation of the divide-and-conquer approach to simultaneous multiple sequence alignment , 1997, Comput. Appl. Biosci..

[32]  Jun S. Liu,et al.  Detecting subtle sequence signals: a Gibbs sampling strategy for multiple alignment. , 1993, Science.

[33]  D. Higgins,et al.  T-Coffee: A novel method for fast and accurate multiple sequence alignment. , 2000, Journal of molecular biology.

[34]  S. Altschul,et al.  A tool for multiple sequence alignment. , 1989, Proceedings of the National Academy of Sciences of the United States of America.

[35]  Patrick D. Surry,et al.  Formal Memetic Algorithms , 1994, Evolutionary Computing, AISB Workshop.

[36]  Jorng-Tzong Horng,et al.  A genetic algorithm for multiple sequence alignment , 2005, Soft Comput..

[37]  S. Altschul.  Gap costs for multiple sequence alignment. , 1989, Journal of theoretical biology.

[38]  Chou-Yuan Lee,et al.  An immunity-based ant colony optimization algorithm for solving weapon-target assignment problem , 2002, Appl. Soft Comput..

[39]  J. Thompson,et al.  CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. , 1994, Nucleic acids research.

[40]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[41]  John A. Miller,et al.  An evaluation of local improvement operators for genetic algorithms , 1993, IEEE Trans. Syst. Man Cybern..