Abstract
This paper proposes an evolutionary tree-base (progressive multiple sequence alignment) method using a genetic algorithm (GA) for solving multiple sequence alignment problems. In our evolutionary tree-base method, chromosomes are represented as guide trees. Two kinds of crossover are proposed for chromosomes of tree structure; subtree selection crossover and tree uniform order crossover. They can generate new chromosomes with inheriting tree structure of parents. The indirect representation of multiple alignments, namely, the guide tree representation of chromosomes, and the proper genetic operations make searching drastically efficient. Experimental results for benchmark problems from BAIiBASE and the NCBI database show that the proposed method is superior to SAGA (a well-known GA-base approach, 1996), T-Coffee (sensitive progressive method, 2000), MUSCLE (progressive/iterative method, 2004), MAFFT (progressive/iterative method, 2005), and ProbCons (probabilistic/consistency method, 2005) with regard to quality of solutions.
Original language | English |
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Title of host publication | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 |
Pages | 3886-3893 |
Number of pages | 8 |
DOIs | |
Publication status | Published - Dec 1 2007 |
Externally published | Yes |
Event | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore Duration: Sept 25 2007 → Sept 28 2007 |
Other
Other | 2007 IEEE Congress on Evolutionary Computation, CEC 2007 |
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Country/Territory | Singapore |
Period | 9/25/07 → 9/28/07 |
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Software
- Theoretical Computer Science