Data Science Seminar by Julia Brettschneider (Warwick)06 Mar 2023, by Sponsored events in
19 April 2023 at 13:00 – 14:00
Lecture Theatre 2.41, Fry Building, School of Mathematics, University of Bristol, UK[Lunch will be served at 12:30 in room 2.01 before the seminar]
Dead Pixels, Protein Species, and COVID-19 Infections from a Point Process Perspective
Point processes are a rich and flexible class of models, that can be put to use to answer quantitative questions in science and engineering. Determining the best way to map a real-world application to the models is not always straight forward and the interpretation of any findings needs to be done in light of the subject matter interpretation of the point process model.
We have used point processes for quality assessment of digital X-ray detectors, based one dead pixel formation. We have developed distribution-free procedures, to quantify the significance of calculated differences between point pattern structures in fluorescent microscopic images of protein abundance.
The method is illustrated by experimental data shedding light on the interplay between subcellular structures called microtubules and chemicals involved in mitosis. Other applications in microscopy relate to the question of colocalisation, which is of interest for understanding the protein interaction. We further used a specific class of point processes, Hawkes processes, to fit COVID infection and death data.
Julia Brettschneider is Associate Professor of Statistics at the University of Warwick. She obtained her PhD in Mathematics from Humboldt University Berlin working on probability theory before she moved to postdoc positions working with genomic data at Eurandom (Eindhoven, Netherlands) and at the University of California at Berkeley (USA). Before starting in Warwick, she worked as Assistant Professor in the Department of Math/Stats and the Department of Epidemiology at Queen’s University in Kingston (Ontario, Canada).
In cooperation with the Jean Golding Institute, University of Bristol
Registration: More information and registration on the Bristol Data Science Seminar Series