Open AccessIdentification of significant protein in protein-protein interaction of Alzheimer disease using top-k representative skyline query
Author(s) -
Mohammad Romano Diansyah,
Wisnu Ananta Kusuma,
Annisa Annisa
Publication year - 2021
Publication title -
jurnal teknologi dan sistem komputer
Language(s) - English
Resource type - Journals
eISSN - 2620-4002
pISSN - 2338-0403
DOI - 10.14710/jtsiskom.2021.13985
Subject(s) - disease , alzheimer's disease , protein–protein interaction , centrality , dominance (genetics) , identification (biology) , psen1 , protein interaction networks , computer science , computational biology , bioinformatics , biology , medicine , presenilin , mathematics , genetics , statistics , gene , botany
Alzheimer's disease is the most common neurodegenerative disease. This study aims to analyze protein-protein interaction (PPI) to provide a better understanding of multifactorial neurodegenerative diseases and can be used to find proteins that have a significant role in Alzheimer's disease. PPI data were obtained from experimental and computational predictions and analyzed using centrality measures. The Top-k RSP method was applied to find significant proteins in PPI networks using the dominance rule. The method was applied to the PPI data with the interaction sources from the experimental and experiment+prediction. The results indicate that APP and PSEN1 are significant proteins for Alzheimer's disease. This study also showed that both data sources (experiment+prediction) and the Top-k RSP algorithm proved useful for PPI analysis of Alzheimer's disease.