Analyzing protein-protein interactions of coronavirus using markov clustering with cuckoo search and ant lion optimization

Proteins are complex organic compounds made up of smaller units called amino acids that bonded together in long chains. Protein interacts with other proteins or molecules and becomes essential the structure, function, regulation organisms' cells. The Protein-Protein Interaction (PPI) results a considerably large network. Consequently, there is need to find method simplify network for easy interpretation protein-protein interaction. One most common methods Markov Clustering (MCL). MCL has been applied solve graph clustering problems based on stochastic flow simulation. three main stages process, namely expansion, inflation, pruning. Although produces fast well-balanced non-hierarchical clustering, it limitation where depend inflation parameter being inputted manually. In this study, we develop combine (MCL) Cuckoo Search (CS) Ant Lion Optimization (ALO) Algorithm. CS ALO algorithm obtain an optimized automatically. PPI SARS-CoV-2 related coronavirus datasets used research presented form graph. experiment shows CS-MCL forms 47 clusters, while ALO-MCL yields 14 cluster dataset.