Machine learning for organelle selection and feature detection in live cells (2018–2020)

Abstract:
This project addresses a roadblock in cell imaging and analysis by creating new mathematical and machine learning techniques for large datasets. Using advanced imaging and these analytic tools we will define newly-discovered macropinosomes - cell structures with seminal roles in immunobiology. A highly interdisciplinary approach will create methods and information to generate a deep understanding of dynamic cell function. Outcomes will include a suite of computational tools that can be applied across bioscience to fully reveal and quantify information contained within microscopic imaging and high impact knowledge for immunity. Innovative approaches will benefit the nation by capacity building in cutting-edge interdisciplinary technology.
Grant type:
ARC Discovery Projects
Researchers:
  • Senior Research Fellow
    Institute for Molecular Bioscience
  • Deputy Director (Research)
    Institute for Molecular Bioscience
    Affiliated Professor
    School of Biomedical Sciences
    Faculty of Medicine
Funded by:
Australian Research Council