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Adapting methods from statistical ecology and applying them to molecular data in cancer


Project Description

There are a number of questions that arise from proteomic and RNA studies in cancer that have clear parallels in the world of ecology. This is particularly the case as more frequently tumours are either sampled multiple times spatially (in either a designed or convenience fashion) or are analysed in a non-destructive manner that preserves all spatial data (but sometimes for a greatly reduced number of molecule types).

These questions include
• How many molecular ’species’ are present?
• What is the abundance of a particular species in a sample for which we have imperfect sampling, and what can we infer about the dynamics?
• To what degree do two species have the opportunity to interact?
• etc.

This project will look to develop and apply methods to answer these and similar questions, drawing on the large corpus of work addressing analogous problems in statistical ecology.

Funding Notes

Multiple sources of scholarship funding are potentially available, including university, research council (EPSRC) and research group. Some are open to international students, some to EU and some UK only.

Applicants should have a good first degree in mathematics, statistics or another discipline (e.g., biology, computer science), with substantial statistical component. A masters-level degree is an advantage.

Further details of the application procedure, including contact details for the Postgraduate Officer, are available at View Website

How good is research at University of St Andrews in Mathematical Sciences?

FTE Category A staff submitted: 30.60

Research output data provided by the Research Excellence Framework (REF)

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