Improved Firefly Optimization for Pairwise Network Alignment with its Biological Significance of Predicting GO Functions and KEGG Pathways

Global pairwise biological network alignment is a pervasive technique in bioinformatics and computational biology. Even now, the computation of network alignment is a challenging effort for delivering an efficient and statistically significant results. Thus, the optimization algorithms have been used to get the precise results of protein network alignment. In this work, an Improved Firefly Optimization Algorithm method was used to align the biological protein networks in a pairwise technique which resulted in an optimal solution. By utilizing the final outcome of network alignment, the function of proteins in a network and KEGG pathways was also obtained and found that the aligned proteins have more functions that are common in nature.