ARC Centre in Bioinformatics. The Australian Centre for Genome-Phenome Bioinformatics will examine how the genome comes to life in the mammalian cell during differentiation and development. We will model, visualise and experimentally validate the complex cellular systems and regulatory networks that control the transformation of genomic information into biological structure and function. We will develop novel approaches and tools to improve health, optimise agricultural production and exploit ne ....ARC Centre in Bioinformatics. The Australian Centre for Genome-Phenome Bioinformatics will examine how the genome comes to life in the mammalian cell during differentiation and development. We will model, visualise and experimentally validate the complex cellular systems and regulatory networks that control the transformation of genomic information into biological structure and function. We will develop novel approaches and tools to improve health, optimise agricultural production and exploit new cell technologies. The Centre will build critical mass and national focus in bioinformatics to generate the human capital and intellectual property that Australia needs to compete in advanced bioscience and biotechnology.Read moreRead less
Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of ....Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of the methodology to be developed is to expedite the discovery of new subclasses of diseases. Another is to provide prediction rules for the diagnosis and treatment of diseases.Read moreRead less
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.Read moreRead less