Understanding Alzheimer's disease with Network Biology

Alzheimer's disease (AD) is a complex disease showing dysregulation of several key pathways and an abnormal increase in levels of beta amyloid (A beta) and hyperphosphorylated tau. Although AD is the most common type of memory loss among the elderly, its pathogenesis is not well understood. Mathematical modeling offers a unique opportunity to gain a better understanding of the AD disease process by combining the current knowledge within a quantitative framework. Using a network model for AD, we discuss how the transition from a normal, healthy brain to an AD brain network can be modeled using a Markov model.