Alzheimer's Disease is a complex and multifactorial neurodegenerative disorder characterized by the progressive loss of cognitive function. While the exact cause of AD is not fully understood, genetic factors are known to play a significant role. Gene regulatory networks (GRNs) play a crucial role in understanding the molecular mechanisms underlying Alzheimer's Disease (AD). The major projects in this group involve the computationally intensive analysis of large-scale data to understand the association of genotype with phenotypes, in particular to identify genes that are differentially expressed in AD patients compared to healthy individuals. By analyzing the changes in gene expression patterns, we can pinpoint specific genes and regulatory elements that are associated with the disease. This information is crucial for understanding the genetic basis of AD. In addition to the analysis of GRN, Genome-scale metabolic models will be employed to identify metabolic biomarkers associated with Alzheimer's Disease. By analyzing metabolomic data from AD patients and controls, we can identify metabolites that are consistently altered in AD and may serve as diagnostic or prognostic markers.