Shannon entropy approach reveals relevant genes in Alzheimer's disease.

ABSTRACT: Alzheimer's disease (AD) is the most common type of dementia and affects millions of people worldwide. Since complex diseases are often the result of combinations of gene interactions, microarray data and gene co-expression analysis can provide tools for addressing complexity. Our study aimed to find groups of interacting genes that are relevant in the development of AD. In this perspective, we implemented a method proposed in a previous work to detect gene communities linked to AD. Our strategy combined co-expression network analysis with the study of Shannon entropy of the betweenness. We analyzed the publicly available GSE1297 dataset, achieved from the GEO database in NCBI, containing hippocampal gene expression of 9 control and 22 AD human subjects. Co-expressed genes were clustered i

SUBMITTER: Monaco A 

PROVIDER: S-EPMC6938408 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature