Complex network study of the immune epitope database for parasitic organisms

Abstract

Abstract: Background: Complex network approach allows the representation and analysis of complexsystems of interacting agents in an ordered and effective manner, thus increasing the probability of discoveringsignificant properties of them. In the present study, we defined and built for the first time acomplex network based on data obtained from Immune Epitope Database for parasitic organisms. Wethen considered the general topology, the node degree distribution, and the local structure (triadic census)of this network. In addition, we calculated 9 node centrality measures for observed network and reporteda comparative study of the real network with three theoretical models to detect similarities or deviationsfrom these ideal networks.Result: The results obtained corroborate the utility of the complex network approach for handling informationand data mining within the database under study.Conclusion: They confirm that this type of approach can be considered a valuable tool for preliminaryscreening of the best experimental conditions to determine whether the amino acid sequences beingstudied are true epitopes or not.