Algorithmic Clustering and Analysis of Spatial Organization of Chromosomes Spatial organization of DNA is known to be pivotal for gene regulation. Thus understanding 3-D organization of genetic material is essential in understanding the functioning of gene regulation. Recently developed Hi-C techniques provide genome-wide average contact frequency data. We will develop convex optimization algorithms to "transform" Hi-C data and use it to build models of 3-D organization of genomic material. We will take a shape-packing approach and model the spatial organization of chromosomes as a minimum overlap ellipsoid problem constructing topological domains. We will infer noisy distance measures between these domains to understand the reachability among other domains. The process will be repeated for different cell types to characterize differences in gene regulation.
I am amazed by how computer science aids in tackling complex problems especially in genetics research. When I took 6.041 I got exposed to stochastic modelling of complex systems and loved it. Already trained in programming through internships and classes I now have the chance of combining curiosity theory and application in a comprehensive research project thanks to SuperUROP.