Artificial intelligence-assisted prediction, feature selection, and multi-omics integration in exploring the interaction between IgG N-glycome and transcriptome and constructing the ageing clock
Date of Award
2023
Document Type
Thesis
Publisher
Edith Cowan University
Degree Name
Doctor of Philosophy
School
School of Science
First Supervisor
Syed Mohammed Shamsul Islam
Second Supervisor
Wei Wang
Third Supervisor
Xinggang Li
Fourth Supervisor
David Suter
Fifth Supervisor
Abdul Baten
Access Note
Access to this thesis is not available
Recommended Citation
Xia, Y. (2023). Artificial intelligence-assisted prediction, feature selection, and multi-omics integration in exploring the interaction between IgG N-glycome and transcriptome and constructing the ageing clock. Edith Cowan University. Retrieved from https://ro.ecu.edu.au/theses/2646