Data-intensive biology and medicine.

Lab head: Ellis Patrick
Location: Westmead Institute for Medical Research / School of Mathematics and Statistics

Our interests center on both the application and the development of statistical and machine learning methodology to analyse high-dimensional experiments and studies that measure the behaviour of thousands of molecules, cells, samples or subjects.Our lab works on projects spanning multiple diseases including melanoma, ovarian cancer, acute myeloid leukemia, Alzheimer's disease, multiple scleroris and HIV. We also work with various high-throughput technologies included bulk and single-cell RNA-Seq, SWATH-MS, flow cytometry, CyTOF, cyclic IF imaging and imaging mass cytometry.

Given the complexity of these experiments and research questions, there is a significant demand for scientists in our lab that value the subtlety of translating between biological and analytical concepts to form suitable and targeted hypotheses.

Lab members: Madeleine Otway Nick Canete Jasmine Yuan

A fresh perspective - High parameter imaging and novel high throughput analytics to study HIV kinetics

Primary supervisor: Ellis Patrick

For the first time, imaging technologies have reached a maturity such that it is now possible to image the interaction of cells with indivdual HIV virions with high resolution and throughput. While the technologies have matured, the possible hypotheses that could be generated with this data are still in their infancy. In this project we can apply or develop cutting edge statistical machine learning tools to gain novel insight into the kinetics of HIV and various other diseases.

Discipline: Applied Medical Sciences, Westmead
Co-supervisors: Andrew Harman
Keywords: Bioinformatics, Imaging mass cytometry, HIV