Abi Singh, University of Delaware

Inside living cells, the inherent probabilistic nature of biochemical processes drives random fluctuations (noise) in the levels of biomolecules, such as RNAs and proteins. Modeling stochastic fluctuations in biomolecule levels is essential to understand how noise affects biological function and phenotype. I will introduce state-of-the-art computational tools for stochastic modeling, analysis and inferences of complex biomolecular circuits. Mathematical methods will be combined with experiments to study infection dynamics of two viral systems in single cells. First, I will show how stochastic fluctuations result in viral burst size (number of viruses produced per cell) variations in the bacterial virus, lambda phage. Next, I will describe our efforts in stochastic analysis of the Human Immunodeficiency Virus (HIV) genetic circuitry. Our results show that stochastic expression of key viral regulatory proteins can drive HIV into latency, a drug-resistant state of the virus.