Postdoc, University of Amsterdam
Hi, my name is Claire Miller and I am an applied mathematician in the area of computational biology. I recently began a postdoctoral position at the University of Amsterdam as a part of the INSIST project, with the goal of conducting in-silico clinical trials for acute ischemic stroke. In my PhD (at the University of Melbourne) I developed a multiscale model of epidermal (skin) tissue to understand how the tissue regulates its height. I have found that the challenge, and the appeal, of computational biology is building a mathematical system that is able to sufficiently, and demonstrably, represent highly complex biological systems with a limited knowledge of the parameters.
Prior to my PhD I worked on the development of fire progression models at CSIRO in Melbourne, Australia. There is an obvious need for these types of models in Australia as bushfires are so common and can be so devastating. The interesting feature of this project was the need for creative ways to solve problems where the balance between computational speed and model accuracy is critical to the value of the model.
My experience in research has motivated me to pursue work in multidisciplinary teams/projects, and has shown the great benefits of connections between academia and industry. I believe it is through such teams and connections that we are able to have a targeted impact on society. For further information, I have details on each research project below, refer to my CV, or feel free to contact me.
The following is a list of all my publications in reverse chronological order. For citation information and abstracts please refer to my Google Scholar.
Article in submission – Claire Miller, Edmund Crampin, James Osborne. Maintaining the stem cell niche in multicellular models of epithelia. Preprint available on arXiv:1811.10781 [q-bio.TO].
Claire Miller, Matt Plucinski, Alec Stephenson, Carolyn Huston, Kay Charman, Mahesh Prakash, Andrew Sullivan, Simon Dunstall. Electrically caused wildfires in Victoria, Australia are over-represented when fire danger is elevated. Landscape and Urban Planning 167:267-274 (2017).
James Hilton, Claire Miller, Jason Sharples, Andrew Sullivan. Curvature effects in the dynamic propagation of wildfires. International Journal of Wildland Fire 25(12):1238-1251 (2016).
James Hilton, Claire Miller, Andrew Sullivan. A power series formation for two-dimensional wildfire shapes. International Journal of Wildland Fire 25(9):970-979 (2016).
James Hilton, Claire Miller, Andrew Sullivan, Chris Rucinski. Effects of spatial and temporal variation in environmental conditions on simulation of wildfire spread. Environmental Modelling and Software 67:118-127 (2015).
Claire Miller, James Hilton, Andrew Sullivan, Mahesh Prakash. SPARK – A bushfire spread prediction tool. Environmental Software Systems; Infrastructures, Services and Applications, pp. 262-271 (2015).
James Hilton, Claire Miller, Matt Bolger, Lachlan Hetherton, Mahesh Prakash. An Integrated Workflow Architecture for Natural Hazards, Analytics and Decision Support. Environmental Software Systems; Infrastructures, Services and Applications, pp. 333-342 (2015).
Gary Delaney, James Hilton, Paul Cleary, Claire Miller. The role of inter-grain friction in determining the mechanical and structural properties of superellipsoid packings. Powders and Grains 2013: Proceedings of the 7th International Conference on Micromechanics of Granular Media (2013).
Thesis title: Understanding the regulation of epidermal tissue structure by molecular and cellular processes using multi-scale models.
Supervisors: Dr James Osborne and Prof. Edmund Crampin.
The skin forms the body’s protective barrier against the world, with the epidermis providing the outer-most layer of this defense. The epidermis is a complex system combining sub-cellular, cellular, and tissue level processes to maintain its structure. If we want to understand what happens during biological malfunction, such as in skin disease or cancers, it is important to first understand normal function.
In my PhD, I have developed a multi-cellular model of the inter-follicular (between hair follicles) epidermis. The model uses overlapping spheres to model cell interactions and a stochastic rule-based method to model cell proliferation. I am using this model to help understand how the epidermis regulates itself in homeostasis. Specifically, I am interested in regulation of epidermal tissue height. The main aspects to steady state tissue height are maintenance of a stem cell population in the basal layer, and a steady rate of cell loss from the top of the tissue. I have looked at both these aspects in detail in my project.
The maintenance of the basal layer is an area I look at in my first paper, available on arxiv (arXiv:1811.10781 [q-bio.TO]). In this paper, I describe an artefact in commonly used epithelial modelling methods that can cause erroneous loss of stem cells from the basal layer. I describe how this loss occurs from the model, and suggest a method to counteract it. I show that, using this method, higher population sizes can be maintained in the basal layer of the epidermis in our models. The method suggested is reflective of a mechanism that has been observed during division in different tissues: the regulation of mitotic spindle orientation.
The second aspect to maintaining tissue height is the regulation of cell loss from the top of the tissue. I have been investigating how to regulate this and am implementing a degradation of cell-cell adhesion as a way to control cell loss. I am investigate the implentation of this degradation loss both as a simple scaling of adhesion as a cell gets older, and also by implementing a system of ODEs in each cell to represent the subcellular interactions that are thought to cause the loss of adhesion.
My model is built using the Chaste libraries. For more details I refer you to https://www.cs.ox.ac.uk/chaste/.
In Australian landscapes, bushfires can cause devestating damage to communities as well as fatalities. If we want to best combat these fires, understanding where they are likely to spread is critical. Getting this information as quickly as possible is vital to decision makers.
When I was at CSIRO I worked on a team developing a fire spread prediction model. The model was developed for use in operational situations and was implemented using a level set method. The rate of spread model that determined the level set function was based on empirical data. For more information about the model, I refer you to the following papers: model implementation, and a high level description of the prediction tool. Alternatively see the Spark website.
The model was also developed for fire research. This included understanding the effect of uncertainty in inputs to model output, and investigating different rate of spread functions. Papers on this research: the effect of variation in inputs, and the effect of including curvature in the spread function
A lot of my work in this area was around data collection for input into the model. This included stabilisation and conversion of video footage of fires into 2 dimensional fire lines, and sourcing of fuel data from different sources such as government data or satellite data.
In addition, I did some research into understanding why powerline fires tended to be more significant than other ignition types. The paper that came from this work can be accessed here.
Outside of my research, I love getting outdoors. I try and spend as many weekends as possible either multi-day hiking, bouldering, or skiing in the winter. I also have a website about multi-day hiking in Australia: https://www.glampliteoz.com.
My current local time is .