Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply ....Real-time phylogenetics for food-borne outbreak surveillance. The project aims to introduce, for the first time, real-time evolutionary analysis of agricultural pathogens so that outbreaks affecting crops and the food supply can be managed precisely and rapidly. An expert team will implement a large-scale data analytics framework in user-friendly software that integrates Australian infectious disease genomics data with global data. Underpinning this work are new theory and algorithms that apply Sequential Monte Carlo to update phylogenetic analyses continuously as new data arrives. Expected outcomes include new knowledge of statistical algorithms for evolutionary analysis, relevant to biological disciplines beyond infectious disease; and enhanced capacity for infectious disease analysis. Read moreRead less
Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic m ....Understanding somatic mutation in plants: new methods, new software, new data. Somatic mutations accumulate as plants grow, affecting everything from short-term ecological interactions to long-term evolutionary dynamics. These mutations have important consequences for plant industry and conservation, but because they are so hard to measure almost nothing is known about them. This project aims to develop new methods and software to detect, analyse, and compare the genome-wide history of somatic mutation in individual plants, providing an unprecedented level of detail into an important but understudied source of biological variation. By applying these methods to an iconic experimental population, This project aims to provide the first insights into the genome-wide causes and consequences of somatic mutation in plants.Read moreRead less