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A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
Published on: October 13, 2023
Prediction of influential proteins and enzymes of certain diseases using a directed unimodular hypergraph
Sathyanarayanan Gopalakrishnan1, Swaminathan Venkatraman2
1Department of Mathematics, Srinivasa Ramanujan Centre, School of Arts, Sciences, Humanities and Education, SASTRA Deemed University, Thanjavur, India.
Abstract:
Protein-protein interaction (PPI) analysis based on mathematical modeling is an efficient means of identifying hub proteins, corresponding enzymes and many underlying structures. In this paper, a method for the analysis of PPI is introduced and used to analyze protein interactions of diseases such as Parkinson's, COVID-19 and diabetes melitus. A directed hypergraph is used to represent PPI interactions. A novel directed hypergraph depth-first search algorithm is introduced to find the longest paths. The minor hypergraph reduces the dimension of the directed hypergraph, representing the longest paths and results in the unimodular hypergraph. The property of unimodular hypergraph clusters influential proteins and enzymes that are related thereby providing potential avenues for disease treatment.
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