Chromosome Organization and Gene Regulation in 3D
Over the past decades great progress has been made in high-resolution genome sequencing; this has led to an explosion of gene expression data from different species and cell types. Reconstructing gene regulatory networks from this data is an important area of research and will help us understand the differences between different cell types and their different gene expression patterns. Linking the spatial and biochemical dimensions is crucial in order to understand the mechanisms that allow different cells to differentially turn on expression programs. The primary goal of this project is to link whole-genome contact maps (Hi-C data) with gene expression data (RNA-seq and ChIP-seq) to develop more powerful methods to infer cell-type specific gene regulatory networks.

I’m exited to participate in the SuperUROP program and gain more experience in computational biology. This project combines my interests in math computing and biology.