Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international effo ....Statistical methods for detection of non-coding RNAs in eukaryote genomes. Understanding how eukaryotic cells work is a major goal of 21st century biology. A crucial step will be to catalogue the functional components of eukaryotic genomes. Australian researchers must be involved in this process at an early stage, in order to maximise commercial opportunities, attract quality researchers and position ourselves for further advances. This project will make major contributions to international efforts in this area, via the development of statistical methods for segmenting genomes, classification of those segments, and study of the resulting classes. In the long term, enhanced understanding of eukaryotic cells will lead to breakthroughs in biology, and to medical, pharmaceutical, agricultural and scientific advances.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE200100425
Funder
Australian Research Council
Funding Amount
$409,364.00
Summary
Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advance ....Genetic and Molecular Consequences of Non-Random Mating in Humans. This project aims to develop and apply novel statistical methods to quantify the effects on a large number of complex traits of two forms of non-random mating in humans, that is inbreeding and assortative mating. The innovation in this proposal lies in integrating multi-level phenotypes with next-generation sequencing data collected in more than half a million study participants. Expected outcomes of this research include advanced analytical methods to perform this integration and dissection of the biological consequences of non-random mating in humans at an unprecedented phenotypically detailed scale. The benefit of this project will be to identify new drivers of mate choice that can contribute to economic, health and social inequalities. Read moreRead less