Luke Cooper

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Luke Cooper

PhD Candidate

Room 372f , Life Science Building

Homology detection, alignment, and ancestral state reconstruction of genetic networks

Using the mathematics of graph theory and recent advancements in network science, a deep understanding of complex biological processes can be obtained. The study of biomolecular networks aims to develop methods of identifying groups of biomolecules (modules) that share involvement in biological processes and determining the function of particular modules.

Due to the increasing volume of available gene expression and protein interaction data for plant species in recent years, methods of extracting useful biological and evolutionary information from inferred biomolecular networks are in increasing demand. In particular, the development of methods to detect homology from a pair of inferred biomolecular networks could allow a deeper understanding of the evolutionary relationships between species than is provided by a DNA sequence alignment. The ability to detect homology in biomolecular networks of many species will allow us to better understand the modules underlying complex traits unique to particular species, and how specific environmental factors are linked to the conservation or deletion of genes that are present in ancestral states.

We aim to develop methods of phylogenetic tree reconstruction and homology detection with biomolecular networks, analogous to current methods of tree reconstruction using DNA sequence data, utilising methods of network alignment and measures of distance between networks.

You can connect with Luke on Google Scholar