Bio: Yun S. Song is a professor of EECS and Statistics. He received the BS degrees in mathematics and physics from MIT, and a PhD in physics from Stanford University. After his PhD, he spent a year at the Mathematical Institute at the University of Oxford, where he decided to change fields. He became a postdoctoral researcher in the Department of Statistics at Oxford, and started doing research in computational biology and mathematical population genetics. From 2004 to 2007, he was a postdoctoral researcher at UC Davis in the Department of Computer Science, and the Section of Evolution and Ecology.
Translation of mRNA into protein is a fundamental biological process mediated by the flow of ribosomes on mRNA transcripts. With multiple factors that can potentially affect its efficiency, this transport process is highly complex and heterogeneous: different mRNAs can have different initiation rates, local elongation rates can vary substantially along the mRNA, and multiple ribosomes can simultaneously translate the same mRNA, potentially leading to interference. In this talk, I will present new theoretical results on a probabilistic model of mRNA translation which allowed us to identify the key parameters that govern the overall rate of protein synthesis, sensitivity to initiation rate changes, and efficiency of ribosome usage. I will then describe our ongoing study, which combines in vitro translation experiments with mathematical modeling, to elucidate the role of the 5′ UTR (particularly uAUGs and uORFs) in regulating translation initiation in eukaryotes.
Mark your calendar for the MICDE SciFM 2024 Conference on April 2nd & 3rd, 2024!