  Hub genes play an essential role in biological systems because of their
interaction with other genes. A vocabulary used in bioinformatics called Gene
Ontology (GO) describes how genes and proteins operate. This flexible ontology
illustrates the operation of molecular, biological, and cellular processes
(Pmol, Pbio, Pcel). There are various methodologies that can be analyzed to
determine semantic similarity. Research in this study, we employ the jack-knife
method by taking into account 4 well-liked Semantic similarity measures namely
Jaccard similarity, Cosine similarity, Pairsewise document similarity, and
Levenshtein distance. Based on these similarity values, the protein-protein
interaction network (PPI) of Malaria GO (Gene Ontology) data is built, which
causes clusters of identical or related protein complexes (Px) to form. The hub
nodes of the network are these necessary proteins. We use a variety of
centrality measures to establish clusters of these networks in order to
determine which node is the most important. The clusters' unique formation
makes it simple to determine which class of Px they are allied to.
