Genetic algorithms and dynamic weighted sum method for RNA alignment

In this paper, we present a new method based on the genetic algorithm (GA) and the weighted sum method (WSM) for aligning RNA sequences. This new approach has been developed in two steps. First, we have developed a multi-objective optimization algorithm using three objective functions: Entropy, Weighted Fully Matched Column (WFMC), and the Base Pair Score (BPS) [1]. Subsequently, the WSM was used to transform this multi-objective optimization approach into a mono-objective one. The weights of WSM are dynamically generated. To evaluate the performance of the proposed method, a comparative study has been performed using some of the best known methods of the sequence alignment and the Bralibase benchmark (Benchmark of RNA alignment). This comparative study clearly shows that the results obtained with this new approach are better than those obtained by the other methods.