This project aims to advance technical developments and foster a deeper theoretical understanding of the epigenetic changes associated with age.
This project will work with and develop a combination of fluorescent DNA tags and PCR-based methodologies that can be used to separate cells of species of interest from environmental cells, and use these to generate genotypes of the animals present in an area.
This project, led by FSP postdoctoral researcher Flavia Tarquinio, is testing whether seagrass restoration can be improved by manipulating the bacterial communities that naturally coexist in their seeds, leaves and roots.
Identifying animals, plants and microbes is important for many industries and activities, including agriculture, forestry and fisheries, human disease, biosecurity, water management, and biodiversity conservation.
Unfortunately, the ability of metabarcoding to provide quantitative information is currently limited due to a number of technical constraints leading to differential amplification between DNA fragments.
We are developing tools that will allow users to combine and analyse standard data types in biodiversity informatics, in this case large-scale information about the evolutionary history of species, traits for individuals or species, and ecological data.
This project is focused on developing new bioinformatic methods for obtaining quantitative information on animal abundance and biomass from eDNA datasets.
Our project will develop and apply ecological and genomic methods to help untangle complex plant-pollinator webs within a range of Australian habitats.
In this project we are using metagenomic sequencing combined with experiments in the laboratory and in the field to unlock the relationships between microbial identity (i.e., who is there) and the ecosystem functions they perform (i.e., what are they doing).
This project will verify whether subsurface microbes can be cultivated in the lab by providing electrons directly as the energy source opening up new possibilities to utilise subsurface microbial life.
In this project, we will quantify the response of plants to temperature stress by sequencing the transcriptome and combine this information with trait data to develop a platform that can predict if a species are near their thermal limits.