Identifying SNP-SNP interactions in Late Onset Alzheimer’s Disease and Predicting breast cancer cell lines oxidative phosphorylation levels from gene expression data
Title: Identifying SNP-SNP interactions in Late Onset Alzheimer’s Disease
Charalampos Floudas, M.D.
Abstract: Alzheimer’s disease (AD) is a neurodegenerative disease that is estimated to be responsible for 60-70% of cases of dementia. While the genetic basis of early onset, familial AD is well understood, sporadic, late-onset AD (LOAD) has complex genetics. Genome-Wide Association Studies (GWAS), which study the association of single nucleotide polymorphisms (SNPs) with disease, have provided insights in the genetics of LOAD, but there remains a lot to be learned. The study of interactions among SNPs has shown promise in increasing our knowledge on the genetics of LOAD, but current methods have difficulties handling the large datasets of GWAS. We have developed a Bayesian Networked based method of interacting SNP-SNP pairs identification that has been evaluated on simulated data. We present the results of the application of the method on two LOAD GWAS datasets and of the evaluation of the identified SNP-SNP pairs for biological plausibility using a variety of biological knowledge sources.
Title: Predicting breast cancer cell lines oxidative phosphorylation levels from gene expression data
Lucas Santana dos Santos, BSc