Below you can find a list of my publications (journal articles, conference papers, tech reports) categorised coarsely by content, as well as supporting code/data where applicable.


Scholary Book Chapters




Statistics/Machine Learning



  • “Association of DNA Methylation-Based Biological Age with Health Risk Factors, and Overall and Cause-Specific Mortality”, Dugué PA, Bassett JK, …, Schmidt D, …, Milne RL, American Journal of Epidemiology, 2017 doi: 10.1093/aje/kwx291. [Epub ahead of print]
  • “Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study”, FitzGerald LM, Naeem H, Makalic E, Schmidt DF, …, Southey MC, Prostate, Vol. 77, No. 5, pp. 471-478, 2016
  • “Genome-wide measures of DNA methylation in peripheral blood and the risk of urothelial cell carcinoma: a prospective nested case-control study”, P. A. Dugué, …, D. F. Schmidt, …,  G. G. Giles, British Journal of Cancer, Vol. 115, No. 6, pp. 664-673, 2016
  • “Genome-wide analysis identifies 12 loci influencing human reproductive behavior”, N. Barban, …, D. F. Schmidt, …, M. C. Mills, Nature Genetics, Vol 48, No. 12, pp. 1462-1472, 2016
  • “Use of a Novel Nonparametric Version of DEPTH to Identify Genomic Regions Associated with Prostate Cancer Risk”, R. J. MacInnis, D. F. Schmidt, …, G. G. Giles, Cancer Epidemiol Biomarkers Prev., Vol. 25, No. 12, pp. 1619-1624
  • “Cross-Cancer Genome-Wide Analysis of Lung, Ovary, Breast, Prostate, and Colorectal Cancer Reveals Novel Pleiotropic Associations”, G. Fehringer, …, D. F. Schmidt, …, R. J. Hung, Cancer Research, Vol. 76, No. 17, pp. 5103-5114, 2016
  • “Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer”, F. J. Couch, …, D. F. Schmidt, …, A. C. Antoniou, Nature Communications, Vol. 27, No. 7, 2016
  • “Childhood body mass index and adult mammographic density measures that predict breast cancer risk”, J. L. Hopper, … D. F. Schmidt, …, C. Apicella, Breast Cancer Research and Treatment, Vol. 156, No. 1, pp. 163-170, 2016
  • “Quantifying the utility of single nucleotide polymorphisms to guide colorectal cancer screening”, M. A. Jenkins, …, D. F. Schmidt, …, D. D. Buchanan, Future Oncology, Vol. 12, No. 4, pp. 503-513, 2016
  • “Quantifying the cumulative effect of low-penetrance genetic variants on breast cancer risk”, Smyth C, …, D. F. Schmidt, …, B. D. MacArthur, Molecular Genetics and Genome Medicine, Vol. 3., No. 3, pp. 182-188, 2016
  • “Global measures of peripheral blood-derived DNA methylation as a risk factor in the development of mature B-cell neoplasms”, N. Wong Doo, …, D. F. Schmidt, et al., Epigenomics, Vol. 8, No. 1, pp. 55–66, 2016
  • “High performance computing enabling exhaustive analysis of higher order single nucleotide polymorphism interaction in Genome Wide Association Studies”, B. Goudey, …, D. F. Schmidt, et al., Health Inf Sci Syst (Suppl 1 HISA Big Data in Biomedicine and Healthcare 2013 Con), Vol. 3, 2015
  • “Quantifying the cumulative effect of low-penetrance genetic variants on breast cancer risk”, C. Smyth, …, D. F. Schmidt, et al., Mol. Genet. Genomic Med., Vol. 3, No. 3, pp. 182–188, 2015
  • “Genome-wide association analysis of more than 120,000 individuals identifies 15 new susceptibility loci for breast cancer”, K. Michailidou, …, D. F. Schmidt, et al., Nature Genetics, Vol. 47, No. 4, pp. 373–380, 2015
  • “Identification and characterization of novel associations in the CASP8/ALS2CR12 region on chromosome 2 with breast cancer risk”, W. Y. Lin, …, D. F. Schmidt, et al., Hum. Mol. Genet., Vol. 24, No. 1, pp. 285–298, 2015
  • “Common non-synonymous SNPs associated with breast cancer susceptibility: fi ndings from the Breast Cancer Association Consortium”, R. L. Milne, …, D. F. Schmidt, et al., Hum. Mol. Genet., Vol. 23, No. 22, pp. 6096–6111, 2014
  • “MicroRNA related polymorphisms and breast cancer risk”, S. Khan, …, D. F. Schmidt, et al., PLoS One, Vol. 9, No. 11, 2014
  • “A Genome-wide Association Study of Early-onset Breast Cancer Identifi es PFKM as a Novel Breast Cancer Gene and Supports a Common Genetic Spectrum for Breast Cancer at Any Age”, H. Ahsan, …, D. F. Schmidt, et al., Cancer Epidemiol. Biomarkers Prev., Vol. 23, No. 4, pp. 658-59, 2014
  • “FGF receptor genes and breast cancer susceptibility: results from the Breast Cancer Association Consortium”, D. Agarwal, …, D. F. Schmidt, et al., British Journal of Cancer, Vol. 110, No. 4, pp. 1088–1100, 2014
  • “An identifi cation of new genetic susceptibility loci for breast cancer through consideration of gene-environment interactions”, A. Schoeps, …, D. F. Schmidt, et al., Genetic Epidemiology, Vol. 38, No. 1, pp. 84–93, 2014
  • “Evidence of gene-environment interactions between common breast cancer susceptibility loci and established environmental risk factors”, S. Nickels, …, D. F. Schmidt, et al., PLoS Genetics, Vol. 9, No. 3, 2013
  • “Genome-wide association studies identify four ER negative-specifi c breast cancer risk loci”, M. Garcia-Closas, …, D. F. Schmidt, et al., Nature Genetics, Vol 45, No. 4, 2013
  • “Large-scale genotyping identifies 41 new loci associated with breast cancer risk”, K. Michailidou, …, D. F. Schmidt, et al., Nature Genetics, Vol. 45, No. 4, 2013
  • “Explaining variance in the cumulus mammographic measures that predict breast cancer risk: a twins and sisters study”, T. L. Nguyen, D. F. Schmidt, et al., Cancer Epidemiol. Biomarkers Prev., Vol. 20, 2013
  • “Variants in the VEGFA Gene and Treatment Outcome after Anti-VEGF Treatment for Neovascular Age-related Macular Degeneration”, F. Abedi, …, D. F. Schmidt, et al., Ophthalmology, Vol. 120, No. 1, 2013
  • “Tumour morphology of early-onset breast cancers predicts breast cancer risk for fi rst-degree relatives: the Australian Breast Cancer Family Registry”, G. S. Dite, E. Makalic, D. F. Schmidt, et al., Breast Cancer Research, Vol. 14, No. 4, 2012
  • “A meta-analysis of genome-wide association studies of breast cancer identifi es two novel susceptibility loci at 6q14 and 20q11″, A. Siddiq, …, D. F. Schmidt, et al., Hum. Mol. Genet., Vol. 21, No. 24, 2012
  • “Supercomputing Enabling Exhaustive Statistical Analysis of Genome Wide Association Study Data: Preliminary Results”, M. Reumann, … D. F. Schmidt, et al., Conf Proc IEEE Eng Med Biol Soc., San Diego, USA, 2012
  • “Genome-wide Association Analysis Identifies Three New Breast Cancer Susceptibility Loci”, M. Ghoussaini, …, D. F.Schmidt, et al., Nature Genetics, to appear, 2012
  • “FAN1 variants identi ed in multiple-case early-onset breast cancer families via exome sequencing: no evidence for association with risk for breast cancer”, D. J. Park, …, D. F. Schmidt, et al., Breast Cancer Research and Treatment, Vol. 130, No. 3, pp. 1043–1049, 2011
  • “Melanoma risk for CDKN2A mutation carriers who are relatives of population-based case carriers in Australia and the UK”, A. E. Cust, …, D. F. Schmidt, et al., Journal of Medical Genetics, Vol. 48, No. 4, pp. 266–272, 2011


Other Research


Tech Reports/Invited Papers/Unrefereed



  • “Minimum Message Length Inference of Autoregressive Moving Average Models”, D. F. Schmidt, Ph.D thesis, Clayton School of Information Technology, Monash University, Melbourne, Australia, 2008
D. F. Schmidt and E. Makalic

One Response to Publications

  1. LB says:

    I had no idea you’d written so many papers man. Bloody impressive.

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