Prediction of influential proteins and enzymes of certain diseases using a directed unimodular hypergraph-Reference-Cited by-同舟云学术

Prediction of influential proteins and enzymes of certain diseases using a directed unimodular hypergraph

Published:2023 Issue:1 Volume:21 Page:325-345
ISSN:1551-0018
Container-title:Mathematical Biosciences and Engineering
language:
Short-container-title:MBE

Author:

Gopalakrishnan Sathyanarayanan¹,Venkatraman Swaminathan²

Affiliation:

1. Department of Mathematics, Srinivasa Ramanujan Centre, School of Arts, Sciences, Humanities and Education, SASTRA Deemed University, Thanjavur, India

2. Department of Mathematics, School of Arts, Sciences, Humanities and Education, SASTRA Deemed University, Thanjavur, India

Abstract

<abstract><p>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.</p></abstract>

Publisher

American Institute of Mathematical Sciences (AIMS)

Subject

Applied Mathematics,Computational Mathematics,General Agricultural and Biological Sciences,Modeling and Simulation,General Medicine

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