Using PPI-GA for identifying protein complexes in protein-protein interaction networks

The major focus of an interdisciplinary field of study termed proteomics is a comprehensive analysis of proteins to evaluate their genetic variety, examine their distinctions, and respond to stresses. Proteomics' major goal is to use protein chemistry, bioinformatics, and biology to detect and measure proteins as well as analyze their post-translational modifications and interactions. Any disruption in the interacting network of proteins can lead to biological abnormalities and diseases like Alzheimer's and cancer. The majority of existing computational approaches for detecting protein complexes are based on certain topological properties of protein-protein networks (PPI). In this paper, it initially provides a novel encoding technique for representing the clarification and solution, and next we recommend the concept of PPI-GA, an innovative clustering based algorithm which is based on genetic approach algorithm which employs a innovative multi based objective excellence function to find out the protein complexes. A different two gold based standard and the real-world based datasets are been used to evaluate proposed algorithm. The obtained result shows that the suggested method can discover key protein complexes and that it offers more accurate results than existing protein complex identification techniques