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dc.contributor.authorJones, Darcy Adam Bain
dc.contributor.supervisorJames K. Haneen_US
dc.date.accessioned2021-09-29T00:15:34Z
dc.date.available2021-09-29T00:15:34Z
dc.date.issued2021en_US
dc.identifier.urihttp://hdl.handle.net/20.500.11937/85748
dc.description.abstract

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.

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dc.publisherCurtin Universityen_US
dc.titleFighting fungal pathogens with big data: new computational approaches for effector discovery and crop disease managementen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentSchool of Molecular and Life Sciencesen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US
curtin.contributor.orcidJones, Darcy Adam Bain [0000-0002-6459-6259]en_US


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