Found 20 matching student topics
Displaying 1–12 of 20 results
Stochastic patterns of tissue inclusions
Biological tissue growth involves the secretion of new tissue (extracellular matrix, collagen fibers) by cells. This secretion incorporates scattered inclusions such as proteins and minerals into the new tissue. During bone tissue growth, some of the tissue-secreting cells themselves become incorporated into the new tissue. The distribution of these tissue-embedded cells is believed to influence subsequent tissue growth processes.
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Stochastic patterns of inclusions during tissue growth
Biological tissue growth involves the secretion of new tissue (extracellular matrix, collagen fibers) by cells. This secretion incorporates scattered inclusions such as proteins and minerals into the new tissue. During bone tissue growth, some of the tissue-secreting cells themselves become incorporated into the new tissue. The distribution of these embedded cells is believed to influence subsequent tissue growth processes.
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Collisions with evolving surfaces
The density of impacts of particles colliding with an evolving surface is of particular interest for several industrial and biological applications. These include etching and deposition processes [1], the incorporation of molecules in a tissue during its growth, budding cell membranes, and biological tissue growth [2]. Impacts on an evolving surface are generated unevenly depending on the relative velocity between the particles and the surface. The distribution of impacts further evolves in a curvature-dependent manner due to the local distortions …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Mathematical modelling of heat conduction in skin
Scald burns from exposure to hot liquids are the most common cause of thermal injury in children. To assist in the development of burn prevention strategies, a theoretical understanding of how heat is conducted through skin is essential. One way to achieve this is to apply a mathematical model to interpret experimental data. Such models are commonly based on the Pennes bioheat equation, a partial differential equation that describes the temperature in the skin as a function of spatial depth …
- Study level
- Master of Philosophy, Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Efficient Bayesian computation for stochastic collective cell spreading models
New insights into biological processes such as skin cancer spread and wound healing can be obtained through collective cell-spreading experiments.These experiments involve placing cells in a dish and observing how the population of cells evolve under a variety of experimental treatments and conditions by taking images and using image processing tools.An important component for obtaining insight into these processes is the biological modelling and subsequent calibration of the model to real experimental data.Cells move and proliferate, give birth to other …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
The reduction of multi-scale porous electrode models using approximation methods
Two-phase porous electrodes are at the heart of many modern day energy storage technologies such as batteries and solar cells. To effectively simulate the operation of these structures a multi-scale mathematical modelling approach is required. This approach results in a system of stiff, coupled, nonlinear partial differential equations that require numerical solution.
- Study level
- Master of Philosophy, Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Computational models of interacting proteins inside a cell
Inside each living cell are vast networks of interacting proteins. These protein networks allow the cell to monitor and interpret its environment, and turn this information into a set of instructions that tell the cell what to do – when to divide, when to move/migrate, when to make new proteins, when to switch to an alternative energy source, etc.Although the human genome has now been sequenced, giving us the full set of instructions (genes) contained within the DNA molecule, we …
- Study level
- Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Modelling and simulation of industrial processes and products
Industrial processes and products can be described as 'multi-problems' in that they are often multi-scale, multi-phase and multi-component in nature. The analysis of such problems sits in the exciting nexus of applied mathematics, physical science and engineering science.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Complex networks as computational devices
Inside each living cell is a tiny universe unto itself: vast interconnected communication networks of signaling molecules (mostly proteins, including enzymes, scaffolds and small molecules ('second messengers'), that dynamically assemble and disassemble in order to interpret stimuli and signals generated both outside and within the cell.We are now beginning to decipher the extraordinary mathematical properties of cellular signalling networks. The remarkable characteristics of these complex networks enable them to represent a kind of 'brain for the cell - allowing the …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
The mathematics of robustness in molecular communication networks
Robustness, and the ability to function and thrive amid changing and unfavourable environments, is a fundamental requirement for living systems. In the past, it has been a mystery how large and complex biological networks can exhibit robust performance since complexity is generally associated with fragility.Exciting recent research here at QUT has suggested a resolution to this paradox through the discovery that robust adaptive signalling networks must be constructed from a small number of well-defined universal modules ("motifs"). The existence of …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
Creation of fibre meshworks at moving interfaces
Extracellular matrix (ECM) secreted by cells is composed of a meshwork of fibres infiltrated with proteins and/or minerals. This fibre meshwork often matures after its creation by rearranging its structure, e.g. according to local mechanical clues, or by the infiltration of new molecules [1]. In this project, the fibre meshwork will be represented by a continuous tensorial field [2].ReferencesBidan C et al. Gradual conversion of cellular stress patterns into pre-stressed matrix architecture during in vitro tissue growth, J R Soc …
- Study level
- Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty
How do collisions control tissue growth?
Biological tissue growth occurs mostly at or near the tissue's surface, where spatial interactions between the tissue and its surroundings can have strong influences onto the local rate of growth.This project will investigate how collisions between molecules or cells with an evolving tissue are dependent on the tissue shape and how these collisions may control tissue growth rate and tissue composition.
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Science and Engineering Faculty
- Lead unit
- Science and Engineering Faculty