Kingdom switching microbial pathogens: the bioinformatics of mutation in the genomes of viruses and bacteria affecting crops, livestock and people. Some organisms that cause infectious diseases have moved between plants and vertebrates, either recently or repeatedly over evolutionary time. Switching between plants and vertebrates strongly influences the way these microbes mutate and evolve. We will search the genomic sequence databases for information about how the choice of host influences muta ....Kingdom switching microbial pathogens: the bioinformatics of mutation in the genomes of viruses and bacteria affecting crops, livestock and people. Some organisms that cause infectious diseases have moved between plants and vertebrates, either recently or repeatedly over evolutionary time. Switching between plants and vertebrates strongly influences the way these microbes mutate and evolve. We will search the genomic sequence databases for information about how the choice of host influences mutations in viral and bacterial genomes and model the evolutionary processes involved. This project will advance our understanding of the fine structure of microbial genomes and the importance of selection pressures on genes. It will lead to better disease management strategies for humans, and for domestic crops and livestock.Read moreRead less
Statistical Advances in the Post-Genome Era. Biologically relevant statistical foundations for post-genome biology and biotechnology will be developed. Specific goals of the topics include the development of accurate and more efficient algorithms for sequence alignments, improved models to maximise the accuracy of analyses for gene expression data and superior statistical methods for identification of complex gene networks that predispose an organism to disease. The Project will make significant ....Statistical Advances in the Post-Genome Era. Biologically relevant statistical foundations for post-genome biology and biotechnology will be developed. Specific goals of the topics include the development of accurate and more efficient algorithms for sequence alignments, improved models to maximise the accuracy of analyses for gene expression data and superior statistical methods for identification of complex gene networks that predispose an organism to disease. The Project will make significant contributions to the new and evolving priority research area of Bioinformation Science (including bioinformatics). Outcomes will include novel techniques for analysis and mining of post-genome data, with applications to developments in Bio-medicine and Bio-agricultureRead moreRead less