Our research focuses on the development of novel computational techniques to reveal principles of biological systems. Pathogenic bacteria live in complex ecosystems composed of thousands or millions of other microbial and viral species. New methods such as next-generation DNA sequencing enable the state of such systems to be digitised and analysed computationally.
Through metagenomic sequencing and related techniques, information on the state of an entire microbial ecosystem can be measured. Using statistical methods and data mining techniques, such data can be associated to other information about the system, such as patient health status or environmental metadata.
Metagenomics and microbial community profiling
The human body plays host to a complex microbiome composed of 10x more microbial cells than mammalian cells. The composition of this microbiome defines susceptibility to a wide variety of diseases; some microbial communities appear to confer protection from invasive pathogens while others are associated with disease states including diabetes. The Darling group develops novel statistical methods to analyse the species content and gene content of microbial communities. Through collaboration, we apply these statistical tools to characterise microbial communities sampled from the human and other environments.
Phylogenetics, recombination, and modeling gene flow in microbes
Bacteria reproduce clonally, yet occasionally genetic material is transferred from one lineage to another and incorporated into the recipient genome, a process called lateral gene transfer. This form of non-Darwinian evolution appears to happen most frequently among closely related bacteria but can occasionally transfer material among very divergent lineages, an example being the recent spread of antibiotic resistance genes among very diverse bacteria. Ongoing research in Darling's group focuses on developing and refining Bayesian statistical models of gene flow in bacterial populations. These models can be applied for genomic epidemiology, identifying natural selection on specific genes, and characterising basic aspects of microbial population biology.
Sequencing, assembly, and alignment of genomes and metagenomes
New sequencing technologies produce large volumes of data, but new algorithms and protocols are required to efficiently exploit the information present in that data. Work by the Darling group in this area focuses on developing efficient and scalable laboratory protocols and algorithms for de novo assembly of (meta)genomes from Illumina and other new sequencing instruments. We also work on methods to compare genome assemblies using multiple genome alignment.
Phone: +61 2 9514 2232