WEHI RAA Seminar Series hosted by the Research Assistants Association

Seminar 1 – Patrick Lam

Spatial Proteomics Imaging at CDI

Patrick Lam is a WEHI Imaging Lab member with broad expertise across the areas of histology, microscopy, and image analysis. Here at the Centre for Dynamic Imaging (CDI), he plays a key role in the set-up and ongoing maintenance of the state-of-the-art spatial proteomics imaging platforms. As demand from internal and external researchers grows, Patrick focuses on case-based protocol development, optimisation, and project coordination to help users generate high-quality unprecedented spatial data in a timely and cost-efficient manner. In his day-to-day role, he also supports instrumentation including operation, training, troubleshooting, and maintenance of a wide range of advanced microscopes within the facility.  Spatial proteomics imaging is a cutting-edge microscopy technology that enables researchers to explore complex biological systems while preserving spatial context—such as tissue architecture, cellular composition and relative locations, and cell–cell or cell–matrix interactions (by proximities). This approach reveals tissue heterogeneity by capturing differences in cell types, protein expression, and cellular functional states.

At the CDI at WEHI, three imaging platforms are available, each with unique advantages and limitations. Together, these platforms provide the ability to obtain unprecedented biological insights—whether through high-plex 2D imaging (up to 40 protein targets), multiplex 3D imaging (up to 15 protein targets), or region-targeted biased/unbiased bulk proteomics approaches, with the options to incorporate RNAscope analysis. Image analysis pipelines utilising machine learning have been developed within the Centre to ensure that researchers can extract the maximum value from their acquired data for their research objectives.

Seminar 2 – Michael Mckay

Image analysis for Spatial Proteomics

Michael Mckay is an Image Analyst in the Bioimage Analysis Core (BAC) of the Walter and Eliza Hall Institute of Medical Research (WEHI). His primary focus is on spatial proteomics, where he helps research scientists turn complex, multiplex imaging data into meaningful biological insights, particularly in the context of cancer and immune-related diseases. He works extensively with Python for machine learning, deep learning, and image processing, and integrates other programming languages as needed for analysis. He also uses tools like QuPath and Nextflow, where he develops and maintains pipelines for multiplex image analysis.

Seminar 3 – Ishrat Zaman

Embracing Uncertainty – Improving Reproducibility in Whole-Brain Light-Sheet Analysis

Ishrat Zaman is a bioimage analyst in the Bioimage Analysis Core (BAC) at WEHI. With a background in both computational biology and wet-lab research, she collaborates with scientists across disciplines to extract meaningful insights from complex microscopy data. She has worked extensively with imaging-based spatial transcriptomics datasets from diverse tissue types, as well as whole-organ lightsheet datasets, with a particular focus on whole-brain imaging. Ishrat is passionate about neuroinformatics as well as bridging the gap between wet-lab experimentation and computational analysis, developing tailored analysis tools and reproducible pipelines that enable researchers to address complex biological questions.

Davis Auditorium

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Including Q&A session

All welcome!