A Graph-Based Genetic Algorithm for the Multiple Sequence Alignment Problem

We developed a new approach for the multiple sequence alignment problem based on Genetic Algorithms (GA). A new method to represent an alignment is proposed as a multidimensional oriented graph, which dramatically decreases the storage complexity. Details of the proposed GA are explained, including new structure-preserving genetic operators. A sensitivity analysis was done for adjusting running parameters of the GA. Performance of the proposed system was evaluated using a benchmark of hand-aligned sequences (Balibase). Overall, the results obtained are comparable or better to those obtained by a well-known software (Clustal). These results are very promising and suggest more efforts for further developments.

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