Science

I am a molecular geneticist with a particular interest in understanding mechanisms of developmental biology through quantitative analysis of imaging, transcriptomics, and computational modeling.

The promise of using mathematical and physical principles to better understand development has inspired researchers from Thompson and Waddington through to Turing, Wolpert, and beyond. Computational modeling of developmental processes has a surprisingly long history, as these figures from a 1972 paper by Lawrence, Crick, and Munro demonstrate. I am excited to be part of an approach that is foundational to the coming era of developmental, cellular, and molecular biology.

My postdoctoral work focused on understanding the formation of the jaw, one of the defining features of the vertebrate clade to which humans, along with all mammals, birds, reptiles, amphibians, and fish belong. Issues with jaw development are among the most common human congenital disorders.

Jaw development is a complex phenomenon that involves successive processes of cell migration, specification, patterning, differentiation, and three-dimensional morphogenesis. I use a combination of approaches to understand these processes in a zebrafish model: FISH and HCR for in situ qualitative and semi-quantitative gene expression measurement, live imaging transgenic embryos on scanning confocal, spinning-disk, and light-sheet microscopes for cell migration and behavior analysis, and NanoString and RNA-seq for transcriptional profiling. In this figure I tracked live neural crest cells migrating towards pharyngeal arches during early jaw development in a zebrafish embryo.

In addition to the published collaborative research I have undertaken with colleagues who are experts in mathematical modeling, I have sought to improve my skills in computational analysis of the type of medium-scale datasets generated by my bench research. I hope to both improve my own abilities in data science, and to better collaborate with others as I gain understanding of the tools and methods of computational biology.

I primarily work in Python, utilizing the NumPy, SciPy, pandas, Matplotlib, and scikit-learn packages. I have also used ImageJ scripting, and the Seurat package in R. This figure shows a snippet of code where I examine the correlation of the divergence of migrating cells' trajectories with their initial distances from each other.

My graduate work involved studying planar cell polarity (PCP), the organization of cellular and tissue features in directional planes. An easily-observed example of PCP is the consistent orientation of hair on any given region of skin, but PCP is also essential for proper embryonic development. Errors in PCP can result in brain, kidney, inner ear, and other congenital disorders.

I studied PCP primarily in a fly model and secondarily in a mouse model. The insect compound eye is a neurocrystalline lattice with well-defined polarity, and I used it to clarify the Ft/Ds genetic network, a signaling pathway that regulates PCP in many animals including humans, by extensive quantitative analysis of changes in polarity in an array of genetic mutants. In this figure I show how the polarity of genetically normal tissue can be reversed by the presence of nearby mutant tissue.