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Grant Award View - GA64642
Next generation causal inference methods for biological data
GA ID:
GA64642
Agency:
Australian Research Council
Approval Date:
4-Dec-2019
Publish Date:
5-Dec-2019
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2020 to 31-Dec-2023
Original: 1-Jan-2020 to 31-Dec-2022
Value (AUD):
$418,398.00
(GST inclusive where applicable)
Variations:
- GA64642-V3 - Variation to Grant (19-Apr-2023 )
- GA64642-V2 - Variation to Grant (14-Oct-2021 )
- GA64642-V1 - Variation to Grant (2-Aug-2021 )
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
Discovery Early Career Researcher Award
Grant Activity:
Next generation causal inference methods for biological data
Purpose:
This project aims to develop next generation causal inference methods for analysing biological data especially the single cell sequencing data and their applications in cell biology. Although Artificial Intelligence and Statistical Machine Learning have been applied successfully in many fields, including biological research, there is still a serious lack of methods for interpreting and reasoning about the mechanism of biological systems, the ultimate goal of research in many areas. Efficient data-driven causality discovery approaches developed by the project will be a timely and significant contribution to the knowledge of biology and statistics as well as the battle against health threats.
GO ID:
GO Title:
Discovery Early Career Researcher Award for funding commencing in 2020
Internal Reference ID:
DE20 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
University of South Australia
Recipient ABN:
37 191 313 308
Grant Recipient Location
Suburb:
ADELAIDE
Town/City:
ADELAIDE
Postcode:
5000
State/Territory:
SA
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
SA
Postcode:
5000
Country:
AUSTRALIA