My Field Of Research

An introduction

PhD Thesis: Computational Statistics in Molecular Phylogenetics

The science of Systematics is the study and organization of biological diversity whilst Phylogenetics is the study or estimation of the evolutionary history that underlies that biological diversity. Both extinct and extant organisms can be the objects of study because evolutionary history unites all life on Earth — every organism that has ever lived is just a twig on the Tree of Life. Unfortunately, history is not something we can see. It has only happened once and only leaves behind clues as to what happened.

These clues include the physical characteristics and geographical location of living species, as well as the fossil record. Another such clue is the structure of biological molecules, and Molecular Phylogenetics, also known as molecular systematics, is the use of this information to gain insight on an organism's evolutionary relationships, and the evolutionary processes that created it. This is possible because every living organism contains DNA, RNA, and proteins. Closely related organisms generally have a high degree of agreement in the molecular structure of these substances, while the molecules of organisms distantly related usually show a pattern of dissimilarity. The result of a molecular phylogenetic analysis is expressed in a Phylogenetic Tree and they come in all shapes and sizes.

Computational Statistics is an area of specialisation within statistics that involves the development of computationally-intensive methods for mining large, nonhomogeneous, multi-dimensional datasets so as to discover knowledge in the data. As in all areas of statistics, probability models are important, and an important activity in computational statistics is model building and evaluation. Hence my PhD could be described as the application of computational statistics to molecular phylogenetics, or simply: Computational Phylogenetics. Specifically, I am involved in investigating, developing and/or critiquing statistical techniques, mathematical models and methods, and computational algorithms and programs, that are used in molecular phylogenetics.