AIBN Virtual Seminar Series: Developing image-based predictive models for the characterisation of cellular senescence in mesenchymal stem cells

We are pleased to host AIBN PhD Student, Ebony Watson from the Mar Group to talk about her PhD work as part of the AIBN Virtual Seminar Series. Please take this opportunity and join us virtually.

Date: Thursday, 1 October

Time: 12pm - 12:40pm

Venue: Online Via Zoom

The seminar is free, but registration is essential. To register please click here.

Abstract

Senescence is a dynamic cellular stress response that is hypothesised to act as the causal nexus of ageing through its extensive pro-inflammatory secretory phenotype. Cells entering senescence undergo extensive morphological, transcriptional, and metabolic changes, which vary significantly by cell-type, tissue, the inducing stressor, and time since the induction of senescence. This extreme heterogeneity has made identifying and characterising the senescence response a considerable challenge, presenting a major obstacle in the research and development of therapeutics for cellular senescence.

Through utilising computer vision and machine learning techniques, we are developing predictive models of cellular senescence in mesenchymal stem cells from extensive high-content imaging data taken across multiple time points and lineage differentiations. By applying interpretability methods to extract actionable information from the final models, we hope to establish a robust and specific phenotype of cellular senescence that can be utilised for the classification of senescent cells, as well as identifying novel subtypes and transitional states.

Bio

Ebony Watson received her Bachelor of Science (Honours) degree in Genetics from the University of Queensland in 2018. In January 2019, she commenced her PhD with Associate Professor Jessica Mar at the Institute for Bioengineering and Nanotechnology, University of Queensland. Ebony’s research is focused on investigating the mechanisms behind ageing and age-associated diseases through the application of machine learning and image analysis techniques.

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