Development Of Statistical Methodologies And Application To Clinical Cancer Studies
Funder
National Health and Medical Research Council
Funding Amount
$428,065.00
Summary
Integrating different layers of information coming from the recent ‘-omics’ technologies can help improving the treatment and the prevention of complex diseases. In particular, the identification of molecular markers of different types can be used for better diagnostics and prognosis in cancer and immune diseases. This project will develop innovative statistical solutions to handle and make sense of the vast amount of biological data that are routinely generated in the laboratories.
The Stemformatics gene expression compendium: development of multivariate statistical approaches for cross platform analyses. Scientific data is gathered in many different forms, but there are significant gaps in our ability to analyse multiple datasets when generated on different pieces of equipment. This project will study three typical research questions in stem cell biology to develop new analytical approaches to help solve this major data gap.
I am a bioinformatician conducting methodological research in statistical functional genomics. I use designed experiments involving highthroughput gene expression technologies to make inferences about gene function and to make discoveries of medical signi
Vertically integrated statistical modelling in multi-layered omics studies. This project will develop an adaptive statistical modelling framework that uses information from many omics data to discover a collection of stable and clinically significant biomarkers. Results will enable researchers to better understand the underlying biological system of complex diseases such as cancer, Alzheimer and diabetes.