Understanding how life arose on Earth is one of the most exciting scientific questions of our times. The genomics revolution has already started to influence our understanding of this by not only providing tsunami like amounts of data on which evolutionary relationships between species can be based but also by suggesting that the processes that drive evolution are more complex than originally thought. Embedded firmly within Computational Biology/Bioinformatics, Phylogenetics is a thriving area at the interface of Computer Science, Mathematics, and Biology, to name just a few, concerned with providing a theoretical framework for studying evolution.

A type of graph theoretical structure for studying evolution that has recently received a considerable amount of attention in the computer science and mathematics community is that of a phylogenetic network [1,2]. Over the years a number of different types of them have been introduced in the literature but they can be broadly classified as rooted and unrooted phylogenetic networks [1]. However not much is know about the interrelationship between rooted and unrooted phylogenetic networks. By building on the supervisor's expertise in phylogenetic networks (see e.g. [3] and [4]), the project aims to make a first inroad into rectifying this by developing theory and algorithmic tools that will help translate between the two types. Although an interest in evolution would be welcome it is not necessary.

D.H. Huson, R. Rupp, C.Scornavacca, Phylogenetic networks, Cambridge University Press, 2010.

http://www.lirmm.fr/~gambette/PhylogeneticNetworks/

P. Gambette, K.T. Huber, On encodings of phylogenetic networks of bounded level.  Journal of Mathematical Biology (2012),  65(1):157-180.

K.T. Huber, V. Moulton, Encoding and constructing 1-nested phylogenetic networks with trinets.