A hybrid genetic algorithm with chemical reaction optimization for multiple sequence alignment.

Multiple Sequence alignment is the ultimate challenging tasks of biological science. It is used for comparison or difference or similarities in these sequences of data. Here, we applied a pragmatic Genetic Algorithm (GA) u0026 Chemical Reaction Optimization (CRO) apparently the most suitable and familiar expansion technique and influenced by the natural genetic structure. Inquiring the magnificent alignment of a biological sequence set is classified as an NP-hard optimization problem for that, GA-CRO algorithms are capable to drive this complication. To find good results, we are going to show the benchmark dataset, the suggested approach is compared with those of the current tools like the SB-PIMA, SAGA, RBT-GA and GAPAM, HMMT. The simulation results recommend that our method be a viable solution with the other methods in terms of efficiency with the appropriate selection of parameters.