A Heterogeneous Graph Model for Repurposing Drugs against Echinococcosis
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Abstract
Through this research work, we aimed to use a graph model to determine important drug substances that are proper for the Echinococcosis hydatid disease. Also, that model can be used in convergence with other similar diseases due to the genes of the Echinococcus granulosus that causes this parasitic disease, and to analyze it by applying graph algorithms to the established model. Furthermore, there is an urgent need to create a basic model for machine learning and artificial intelligence methods in health and pharmaceuticals. Also, the collection of genes and proteins registered in the official internationally recognized gene-disease databases, as well as the data of drugs and pharmaceutical products used for the specific disease, is the first step in the understanding and development of interdisciplinary science. In this paper, we define a heterogeneous graph with multiple types of nodes and edges as a basic model for future studies, as well as the methods and algorithms used in the study, considering the interrelationship between Echinococcus granulosus genes, proteins, diseases, and drugs.
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echinococcus, drug interaction network, graph theory, data analysis
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