Computational methods to measure DNA replication with single-molecule resolution

In the time it takes you to read this sentence, your body will produce millions of new cells. It is critical that each of them replicated their DNA accurately; errors in DNA replication can lead to genome instability and cancer. Cancerous cells often show different patterns of replication compared with healthy human cells, making DNA replication an important therapeutic target.  However, studying DNA replication at scale is a challenging problem: Existing methods either measure how a population of cells replicate, which “averages out” rare but important behaviour, or they work with single-molecule resolution but have low throughput.  

The Boemo Group (https://www.boemogroup.org) is a computational biology laboratory developing artificial intelligence software that measures the movement of replication forks from Oxford Nanopore sequencing data.  This method provides a high-throughput, inexpensive, accurate, and automated way to measure replication fork movement. The student will develop novel algorithms and computational approaches to track the movement of replication forks in both human cells and infectious microorganisms.  The student will also develop cutting-edge mathematical models of DNA replication that can be used to predict targets for replication-based therapies. This project will be highly collaborative and there will be the opportunity to learn, or improve upon, software engineering in Python/C/C++, GPU computing, deep learning with TensorFlow, the processing and management of large datasets.