Prof Enes Makalic
Honorary (Professorial Fellow)
Melbourne School of Population and Global Health
333 Scholarly works
17 Projects
HIGHLIGHTS
2026
Journal article
AI-based BRAIx risk score for the intermediate-term prediction of breast cancer: a population cohort study.
DOI: 10.1016/j.landig.2026.1009872026
Other
Supplementary Table S9 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622402026
Other
Supplementary Table S5 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622522024
Research grants (ARC, NHMRC, MRFF)
Centre of Research Excellence and Expertise in Genetic Epidemiology for Precision Population Health
2023
Journal article
Australian genome-wide association study confirms higher female risk for adult glioma associated with variants in the region of CCDC26
DOI: 10.1093/neuonc/noac2792021
Research grants (ARC, NHMRC, MRFF)
Centre of Research Excellence in Precision Public Health Approaches to Breast Cancer Screening, Early Detection and Mortality Reduction
2018
Research Grant
Improved and Automated Measures of Breast Cancer Risk Based on Digital Mammography and Family History Data Collected by Breastscreen That Will Enable Tailored Screening for Breast Cancer
RECENT SCHOLARLY WORKS
2026
Other
Supplementary Table S2 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622672026
Other
Data from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.c.75353162026
Other
Supplementary Figure S2 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622762026
Other
Supplementary Table S4 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622552026
Other
Supplementary Figure S1 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622822026
Other
Supplementary Table S8 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.317622432026
Other
Supplementary Table S3 from Region-Based Analyses of Existing Genome-Wide Association Studies Identifies Novel Potential Genetic Susceptibility Regions for Glioma
DOI: 10.1158/2767-9764.31762261
RECENT PROJECTS
2024
Research contracts (non-grants)
Using Machine Learning to Improve Polygenic Risk Prediction of Cancer