My research interests delve into developing a quantitative understanding of complex biological systems by joining systems-level biological investigation with mathematical modeling. During my career, I have researched a multitude of different biological events, including:
- Cell polarization and symmetry breaking
- Entrainment of gene expression oscillations
- Gene regulatory networks
- Stochasticity and multi-stability in gene expression
- Temporal analysis of transcriptome during muscle differentiation and vertebral segmentation
To complete these research projects, I utilized a variety of tools and approaches, such as single-cell microscopy measurements, genome-wide procedures, computational simulations, time-resolved perturbation tests and mathematical modeling. Additionally, I have extensive expertise in systems-level analysis of biological systems. In my lab, I work collaboratively with an interdisciplinary team from various backgrounds, including biology, physics and engineering.
My research team and I aim to identify the systems-level machinery governing vertebral segmentation, which is a groundbreaking case of spatial pattern formation during embryonic development. We have an overarching goal of determining how gene expression noise is cushioned by gene regulatory networks to attain robustness in developmental pattern formation.
Stochastic processes occur regularly in biological systems. For instance, among genetically identical bacteria, gene expression levels can be significantly different between individual bacteria within the population. The cause of this difference is due to the random nature of biochemical reactions. During my graduate work, I researched the impact of these fluctuations, known as biochemical noise, on macroscopic variations in gene expression. Our stochastic computational model found consistent results showing the proteins are developed in random, sharp bursts. These findings provide the first results for the microscopic biochemical source of phenotypic noise.
In my research lab, my team and I have incorporated these methods to study the scale and sources of expression noise in the levels of the vertebrate segmentation clock genes. We exhibited that segmentation clock transcription levels have low amplitude and high heterogeneity. We found that variability in the clock gene expression is blocked by Notch signaling and a negative feedback loop. We also uncovered that chromosome linkage reduces uncorrelated transcriptional variability and delivers phenotypic robustness for a developmental pattern formation.
I received the Merck/Massachusetts Institute of Technology computational biology fellowship in 2000. I then pursued a Cancer Research UK, Marie Curie and European Molecular Biology Organization (EMBO) postdoctoral fellowships from 2005 to 2007. I have more than 15 years of experience in the developmental biology field and began my work at the Cincinnati Children’s Hospital Medical Center in 2017. My research has been published in various journals, including Nature Genetics, Cell Reports and Nature.