Applications of cancer biology to statistics and combinatorics


Dr Chris Greenman, University of East Anglia

Date & Time:

Thursday, 14 May 2015, 14:00

Old Road Campus Research Building, Room 71abc, Headington OX3 7DQ
Cancer Bioinformatics Seminar Series

I. Single cell microscopy enables individual cells to be tracked as they divide, giving detailed information on the lifetimes of single cells, and the identity if their daughter cells. This gives detailed information that we can use to describe the growth of a colony of cells. We use this information to parameterize a model of cell homeostasis in epithelial tissue, and describe how these models may be perturbed in pre-cancerous lesions. This work has led to an elegant unification of two old statistical problems. The Kolmogorov Master equation describes branching processes and has seen many applications ranging from queues to chemical equations. The McKendrick equation describes age-dependent populations and has seen many applications in demography. We describe a hierarchy of equations that incorporates both systems.

II. Genomic rearrangements are a major source of variation in cancer genomes. We firstly examine next generation sequencing data and describe some of the problems associated with (i) describing how DNA segments combine into chromosomes, and (ii) the evolutionary steps that have taken place to produce the observed data. We secondly describe some combinatorial patterns that emerge from these processes, which tell us that even with perfect sequence data, we still cannot necessarily describe how the genomes have evolved.

About Us
We aim to enhance clinical and basic cancer research in Oxford with the ultimate goal of increasing cancer cure rates.
In Oxford, we have a great wealth of broad-ranging expertise and a powerful network of cancer researchers.
Study With Us
Our graduate training programmes for both scientists and clinicians are internationally recognised.