Scott Ronquist

Scott Ronquist


Areas of Interest

I’m a Computational Biology PhD student with a background in chemical engineering. The goal of my work is to advance cellular reprogramming methods by using data-guided mathematics to understand the genome network dynamics that control cell function. Towards this goal, our lab collects high-throughput sequencing data and genome imaging data on various human cell types. These data include structural genome information such as chromosome conformation capture (Hi-C), protein-chromatin binding locations (ChIP-seq), and fluorescent in situ hybridization imaging (FISH imaging), as well as functional genome information such as gene transcription and protein quantification (RNA-seq and Proteomics, respectively). Analysis of how these interconnected aspects change over time adds further depth to the already high dimensional data. To make sense of this information, I apply engineering and mathematical concepts to extract underlying genomic networks that are critical to cell function. This information can then be used to determine where and when to put control in the genome to manipulate the cell type, with the end goal of creating an optimal algorithm for cellular reprogramming. 


  • B.S.E., University of Michigan (Chemical Engineering)