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Dr. Zofia Jones

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Numerical modelling on a cell-scale

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Research Style

Research Experience

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Personal Interests

Contact Information

Research Style

I managed to get a bit bored with Physics. I decided to dive into mathematical biology, more because of the promises of being able to use more varied mathematical approaches rather than a burning interest in biology. However, I found I enjoyed trying to find theoretical frameworks to understand biological questions. Often the detail of it all seems overwhelming and the theoretical side can get lost. However I have brain-stormed extensively about the theory involved in cell biology and also ecology. I find that a solid understanding of these principles can provide a useful source of direction for research be it theoretical, computational and experimental.

I find that qualitative and quantitative thinking are both necessary. Technical knowledge is essential, but focusing on an overly technical brute force approach can make you lose sight of the broader context and the full scope of possibility in this field of research. It is easy to get stuck after the bioinformatics is done. The fun is to mix and match the various possible modelling approaches to fit the question at hand. The challenge is to figure out precisely how to do it.

Communication is key. In mathematical biology, work often only makes sense in the right context and to the right audience. Principles which seem obvious to mathematicians and biologists respectively do not necessarily overlap.

You can't solve everything by throwing more time at it. Overwork, too many late nights and ignoring your personal life make you less creative, unfocused and possibly even a bit stupid. Noone really knows how research will work out and everyone is under similar pressures. Good manners and structured communication avoid a lot of problems.

Research Experience

Metabolic modelling of microorganisms

The biggest question in the modelling of microbial communities is to explain their observed diversity in the light of evolutionary principles. Evolutionary principles related to microorganisms often involve trade-offs. The most common trade-off being growth rate vs efficiency. Using the principles of energy budget theory, it is clear that such trade-offs exist. My challenge is to start to understand how different phenotypes present themselves using the information available in metabolic models. This is challenging as the information contained in metabolic models is essentially the digetive tract of an organism, rather than the mechanisms involved in homeostasis. However, the quality of information extracted from these models can be maximised via discrete optimisation and sampling techniques. Working on some data sets has let me demonstrate some essential data processing and analysis skills.

Omics data interpretation

I worked on linking their 16s rRNA genome sequencing data of microorganisms linked with malodour with the base of scientific understanding built up over several years. I highlighted ways in which the data could be used to start to understand the functional groups present by demonstrating the presence of distinct subgroups of communities using machine learning techniques. This groups have since been re-identified by the Dirichlet methods being developed in Glasgow.

Mathematical modelling of nanotoxicology

My PhD was in the construction of mathematical models relevant to Nanotoxicology with the Health and Safety Laboratories (HSL) at Buxton. I developed models clarifying the role of Reactive Oxidative Species (ROS) signalling in apoptosis pathways involving TNF-alpha, NF-kappaB and Jun-c. I also worked on modelling phagocytosis using physics style energy minimisation principles.

Qualifications

Links

Personal Interests

Generally interested in "belief systems", what drives people and what makes us co-operate. Can read anything about politics, religion, alternative politics, alternative religion, symbolism, metaphor, colour theory ...

Contact Information

School of Engineering,
Rankine Building,
University of Glasgow,
Glasgow

E-mail: zofia.jones@glasgow.ac.uk
Phone: +44 (0) 141 330 6027