LECTURE: Change-point Modelling in Biological Sequences

Abstract: The change-point problem arises in wide variety of fields, including biomedical signal processing, speech and image processing, seismology, industry (e.g., fault detection) and financial mathematics. Multiple change-point models are also important in many biological applications and, particularly, in analysis of biomolecular sequences. The genomes of complex organisms, including the human genome, are known to vary in GC content along their length. That is, they vary in the local proportion of the nucleotides G and C, as opposed to the nucleotides A and T. Changes in GC content are often abrupt, producing well-defined regions. We model genome sequences as a multiple change-point process, that is, a process in which the sequential data are separated into segments by an unknown number of change-points, with each segment supposed to have been generated by a different process. In this talk, we consider various approaches to change-point modelling using Monte Carlo simulation to find estimates of change-points as well as parameters of the process on each segment.