School of Computing Science


Rebecca Mancy

PhD student in Computing Science

Room 322, Sir Alwyn Williams Building, Lilybank Gardens, Glasgow, G12 8QQ
tel: +44 (0)141 330 8138 / +44 (0)141 330 1625
email: Rebecca.Mancy@glasgow.ac.uk

I have several roles in the University of Glasgow and thus several web pages. This is my Computing Science page. For my other roles, please see below:

Research Interests

Since October 2010 I have been a PhD student in the Inference Group in the School of Computing Science. I am working with Simon Rogers and Patrick Prosser and my work is funded by EPSRC.

The aim of my work is to use computational modelling techniques to understand complex biological systems capable of evolution. Specifically, I am interested in evolvability – the propensity to evolve - and am interested in the minimal required conditions for adaptive evolvability to emerge within a Darwinian paradigm.

The standard theory of biological evolution relies on three principal mechanisms: genetic heritability, introduction of variation and selection. Of these, the introduction of variation, of which the ultimate source is considered to be mutation, is normally considered to be random with respect to fitness, implying that evolutionary fate is ultimately restricted by external processes that cause mutation and selection. More recent accounts of evolutionary processes leave room for some endogenous control of mutation. For example, it is known that mutation probabilities vary between species and across the genome in ways that appear to be adaptive. However, the way in which these patterns has arisen is currently unknown.

The project will employ existing models to formally investigate and describe the conditions under which adaptive evolvability emerges. Specifically, I will investigate the effect on the emergence of adaptive evolvability under different conditions in the model set-up (changes in the fitness landscape or fitness function, parameter changes). The project therefore contributes to the answer of a fundamental question in biology – that of the extent to which evolutionary processes are endogenously controlled. The work may also provide the basis for the development of new evolutionary-inspired algorithms of relevance to computing science and engineering.