Algebraically informed models of biological sequence evolution. To make sense of the patterns they see in the natural world, biologists across fields as diverse as genetics, epidemiology and biogeography need an accurate picture of evolutionary history. DNA sequences provide an exciting means to establish this picture of the past, but to decode it successfully requires mathematical models of how DNA evolves. Mathematical inconsistencies have been identified with current approaches. In particular ....Algebraically informed models of biological sequence evolution. To make sense of the patterns they see in the natural world, biologists across fields as diverse as genetics, epidemiology and biogeography need an accurate picture of evolutionary history. DNA sequences provide an exciting means to establish this picture of the past, but to decode it successfully requires mathematical models of how DNA evolves. Mathematical inconsistencies have been identified with current approaches. In particular, understanding the effect of natural selection in different parts of the tree of life requires models that behave robustly in the face of shifting evolutionary processes. This project aims to use insights from algebraic methods to construct mathematically consistent models of wide biological utility.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE130100423
Funder
Australian Research Council
Funding Amount
$369,061.00
Summary
Group theory and phylogenetics: exploiting symmetry to uncover evolutionary history. Using advanced algebra, structural symmetries inherent in phylogenetic methods will be studied and improved approaches will be derived. DNA sequences contain a wealth of information about evolutionary events that occurred millions of years ago, but extracting this information requires the application of robust methods.
Interpreting biological sequence information: untangling hybridisation. Hybridisation is believed to be important during adaptive radiations where species rapidly colonise new niches and respond to new environments, e.g. in times of climate change. This project will create the statistical tools and software required for evolutionary biologists to understand how hybridisation has helped shape the Australian flora.