An Evolutionary Optimization for Multiple Sequence Alignment

Abstract- Multiple Sequence Alignment is one of the most useful tools in bioinformatics. It is widely used to identify conservation of protein domains, RNA secondary structure and classification of biological sequences. However, it is recognized as one of the most challenging tasks in bioinformatics. Evolutionary algorithms are providing competitive solutions for engineering optimization. Genetic algorithms are relatively new optimization technique that can be applied to various problems, including those that are NP-hard. We implemented conventional Genetic Algorithm on this problem using a research on Evolutionary Computation System (ECM) using MAT lab. To date, the Genetic Algorithm successfully prevented premature and brought in improvement in Multiple Sequence Alignment for short sequences. However, for the dataset with long sequences, there is no significant improvement. The proposed project work provides evolutionary optimization for MSA with long sequences