Ertugrul M. Ozbudak, PhD's, overriding interest is to achieve a quantitative understanding of complex biological systems by integrating systems-level biological experimentation with mathematical modeling. He has worked on different biological phenomena, such as: stochasticity and multistability in gene expression, cell polarization and symmetry breaking, entrainment of gene expression oscillations, gene regulatory networks and analysis of transcriptome during muscle differentiation and vertebral segmentation. He has utilized genome-wide techniques, single-cell microscopy measurements, time-resolved perturbation experiments, mathematical modeling and computational simulations to accomplish these projects.
Stochastic mechanisms are common in biological systems. His earlier PhD studies investigated the effects of these microscopic fluctuations (biochemical noise) on macroscopic variations in gene expression (phenotypic noise). His follow-up studies showed that cells could utilize positive feedback loops to exploit the stochastic gene expression to achieve bistability at the population level. These work were among the first multidisciplinary studies focused on stochastic gene expression and triggered the blossoming of the “stochastic gene expression” field.
Afterwards, Dr. Ozbudak investigated the systems-level properties of the vertebrate segmentation clock. He has performed computational modeling and time-resolved perturbation experiments to demonstrate that Notch signaling keeps the oscillations of neighboring cells synchronized. The period of the segmentation clock oscillations gets longer as cells are displaced along the posterior-to-anterior axis, which results in traveling waves of clock gene expression sweeping in the unsegmented tissue. By combining molecular-level computational modeling and quantitative experimentation, they showed that a gradient of gene expression time-delays along the axis underlies the traveling segmentation clock waves.
Segmentation of vertebral column; pattern formation; cell differentiation; systems biology; computational modeling
Associate Professor, UC Department of Pediatrics