The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molec ....The systems biology of stem cells. Using new bioinformatic methods, this project aims to identify new classifiers of different stem cell populations, develop statistical models that address population heterogeneity and provide molecular predictors of the differentiation potential of stem cells. Understanding, predicting and directing the processes of differentiation are major goals in the disciplines of stem cell biology, developmental biology, tissue engineering and regenerative medicine. Molecular atlas projects have successfully revealed rules of genome output and regulation, by mining patterns that are evident across multiple cell types and datasets. By applying this philosophy to relevant, well-curated stem cell experiments, this project aims to create new methods for the integration and interrogation of smaller individual datasets. These methods should have broad utility and enable new avenues in tissue engineering.Read moreRead less
A biological model to understand caveolin-1 and lipid raft function in health and disease. This project will generate a biological model for pathological caveolin-1 action on cell membrane domains called lipid rafts to determine how they trigger chronic diseases such as cancer and diabetes. The tools developed in this project will help Australia find new drug targets for the treatment and prevention of these prevalent diseases.
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE120100071
Funder
Australian Research Council
Funding Amount
$290,000.00
Summary
Chemi–biology computational platform for lead discovery in infectious disease. A challenge in fighting infectious disease is in finding new bioactive compounds. This facility will provide a high performance computational environment designed to accelerate the discovery of quality compounds for use in anti-infective medicine.
Discovery Early Career Researcher Award - Grant ID: DE170100759
Funder
Australian Research Council
Funding Amount
$372,000.00
Summary
Trans-omic networks: A machine learning and omics integration approach. This project aims to map and model ‘trans-omic’ networks that cut through omic layers using machine learning and multi-omic data integration. Global networks regulated by molecular programs, including signalling, epigenetic, transcriptional and translational regulation, orchestrate cellular functions. Technological advances can profile these molecular programmes, giving rise to various ‘omics’. However, data generated from e ....Trans-omic networks: A machine learning and omics integration approach. This project aims to map and model ‘trans-omic’ networks that cut through omic layers using machine learning and multi-omic data integration. Global networks regulated by molecular programs, including signalling, epigenetic, transcriptional and translational regulation, orchestrate cellular functions. Technological advances can profile these molecular programmes, giving rise to various ‘omics’. However, data generated from each omic layer are predominantly analysed separately owing to their heterogeneity. To understand cellular functions in its entirety, it is essential to interpret omic data across multiple omic layers. Applying this project’s methods is expected to improve use of omics data and fundamental molecular programs.Read moreRead less
Transcription factor – enhancer – promoter based regulatory networks. This project aims to develop new understanding on how multicellular organisms (including humans) develop, and how mutations in distant regions of the genome can affect human traits. The way the human genome is interpreted by the cellular machinery is still a mystery. We have a reference sequence and know where the majority of coding genes are, but we are far from understanding how the genome is regulated to generate the divers ....Transcription factor – enhancer – promoter based regulatory networks. This project aims to develop new understanding on how multicellular organisms (including humans) develop, and how mutations in distant regions of the genome can affect human traits. The way the human genome is interpreted by the cellular machinery is still a mystery. We have a reference sequence and know where the majority of coding genes are, but we are far from understanding how the genome is regulated to generate the diversity of cell types in our bodies. Enhancer regions interact with proximal promoters to regulate gene expression level and tissue-specificity. This project aims to develop transcriptional regulatory network models using high throughput chromatin interaction data and expression perturbation to link promoter and enhancers genome-wide.Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE130100007
Funder
Australian Research Council
Funding Amount
$650,000.00
Summary
A research platform for exploring the genotype: phenotype nexus. This project will allow us to connect the genetic code of an organism with its characteristic traits that are essential for its survival. The equipment will accelerate research that performs this translation, and will allow leading Australian scientists to continue to make breakthroughs in this field globally.
Commensal benefits: genomic basis for suppressing plant pathogens with Pseudomonas biocontrol species. Food security is an issue of mounting significance due to unpredictable climate trends and increasing global population growth. A feature of paramount importance to reliable crop production is the capacity to control plant diseases. This project investigates natural plant colonising bacteria as a tool for protecting plants from disease.
Computational systems biology: understanding mammalian cell fates using genome-scale network models. Mutations can disrupt the cellular networks that control normal development, causing cells to develop abnormally including in ways that lead to cancer. The project will analyse genome sequences from more than 700 pancreatic cancers and matched controls to precisely map the causative trail from mutations to disrupted networks to altered cell development.