Mar Group Honours Projects

 Supervisor Associate Professor Jessica Mar

Advances in single cell next generation sequencing methods have led to an explosion of new bioinformatics methods. Yet, many questions in biology remain unanswered. This project focuses on developing statistical and computational methods that operate on single cell RNA-sequencing data so that we can learn more about biology through single cell techniques.

 Supervisor Associate Professor Jessica Mar

Ageing is a process that is characterized by heterogeneity in biological systems. Anecdotally, we know that how a person ages can differ dramatically from person to person. At the molecular level, the dysregulation of key signalling pathways and disruption to individual cell functions occur during ageing and give rise to symptoms we associate with ageing. This project aims to use gene expression datasets, many of them which are publicly-available, to add new knowledge into the genes and signalling processes that are involved during the ageing process. There is also scope to understand how ageing interventions, like senolytics or caloric restriction impact our transcriptomes and whether they can inspire us to identify new manipulations or anti-ageing therapeutics.

 Supervisor Associate Professor Jessica Mar

The promise of big data is to reveal compelling insights into medical biology. But a major challenge for realizing this goal is the intractable presence of noise. This project focuses on benchmarking different kinds of bioinformatics methods to understand the optimal ways to handle noise in the data to obtain concrete results in biology.

 Supervisor Associate Professor Jessica Mar

Identifying new regulators of human disease is important for developing therapeutics, diagnostics, and understanding disease mechanisms. This project involves the analysis of gene expression variability to identify new regulators of human disease and learn more about how biology systems break down in the presence of different diseases.

 Supervisor Associate Professor Jessica Mar

Humans display an inspiring degree of resilience in the presence of disease and infection. But this robustness is only up until a point. This project models robustness in biological systems to understand which regulators in the genome are important for providing resilience against a perturbation and also the points of fragility that cause systems to lose homeostasis. Existing studies have shown that modelling the expression variability of genes can be useful for understanding robustness and this project will use examples from viral infection, cancer drug resistance, and others.