Fighting fungal pathogens with big data: new computational approaches for effector discovery and crop disease management
Fungal plant-pathogens are a major contributor to crop yield loss. In this thesis we developed state of the art computational methods to predict molecular determinants of pathogen virulence. We have also performed the first population genetic and pan-genomic analysis of a major wheat pathogen in WA,...
| Main Author: | |
|---|---|
| Format: | Thesis |
| Published: |
Curtin University
2021
|
| Online Access: | http://hdl.handle.net/20.500.11937/85748 |
| Summary: | Fungal plant-pathogens are a major contributor to crop yield loss. In this thesis we developed state of the art computational methods to predict molecular determinants of pathogen virulence. We have also performed the first population genetic and pan-genomic analysis of a major wheat pathogen in WA, Parastagonospora nodorum. This thesis has provided a valuable suite of methods and insights into plant pathogen genetics, ranging from the molecular level to the population level. |
|---|