Analysis of Protein-Protein Interaction Using Skyline Query on Parkinson Disease

Abstract

Significant protein is an important protein needed by the body for growth. Protein disorders can cause organ diseases or dysfunction. In carrying out their functions, proteins interact with each others to form protein-protein interaction (PPI) networks. To find the most important protein in a network, centrality measures can be used with various criteria according to the parameter specified. This study uses skyline query, an algorithm for finding non-dominated data, to get optimal results for problems with various criteria. Some centrality measures are used as attributes to represent the PPI network features. The aim of this study is to find significant proteins of Parkinson, one of the fastest growing diseases in the world. The results find 14 proteins, according to the literature, 12 of them are related Parkinson Disease. These proteins are PARK2, SNCA, ATP13A2, TP53, MAPT, FYN, HSF1, DRD2, VEGFA, AKT1, MPO, and SLC18A2.