Biomarker prediction in autism spectrum disorder using a network-based approach

Abstract

Background Autism is a neurodevelopmental disorder that is usually diagnosed in early childhood. Timely diagnosis and early initiation of treatments such as behavioral therapy are important in autistic people. Discovering critical genes and regulators in this disorder can lead to early diagnosis. Since the contribution of miRNAs along their targets can lead us to a better understanding of autism, we propose a framework containing two steps for gene and miRNA discovery. Methods The first step, called the FA_gene algorithm, finds a small set of genes involved in autism. This algorithm uses the WGCNA package to construct a co-expression network for control samples and seek modules of genes that are not reproducible in the corresponding co-expression network for autistic samples. Then, the protein–protein interaction network is constructed for genes in the non-reproducible modules and a small set of genes that …

Fatemeh Zare

Associate Professor

My research interests include bioinformatics, computational biology and artificial intelligence.