Modelling Large-scale Medical Record Data
Common complex diseases such as type-2 diabetes, obesity, stroke, and cardiovascular disease are among the leading causes of mortality worldwide. Our limited understanding of how genetic variation and the environment affect health and disease makes it impossible to respond optimally, treat and ultimately prevent symptoms.
The Robinson Group develops statistical models and the computational tools required to implement these models for very large-scale human medical record data. The overall goal is to improve our understanding of how genetics and our lifestyles shape our risk of disease.
We still have very little understanding of why people develop first symptoms at different age, or why the severity of symptoms varies. The Robinson Group works to better characterize the underlying pathways and relationships among diseases. The hope is to improve our ability to predict not only an individual’s overall risk of disease, but also when people are likely to become sick and how they might respond to different treatments.
Answers to long-standing questions at the heart of understanding the changes that occur at important stages of our lives are also investigated: How does the maternal and child genome interact to shape pregnancy and early life? What constitutes a healthy pregnancy? How does our genome shape our growth? How do genetics influence our ability to lead long and healthy lives?
On this site:
Statistical models for the genetic basis of common complex disease | The genetic basis of age of onset | The genetics of ageing | Maternal health | Genomic prediction for personalized health
Sulc J, Mounier N, Günther F, Winkler T, Wood AR, Frayling TM, Heid IM, Robinson MR, Kutalik Z. 2020. Quantification of the overall contribution of gene-environment interaction for obesity-related traits. Nature Communications. 11, 1385. View
Nabais MF, Lin T, Benyamin B, Williams KL, Garton FC, Vinkhuyzen AAE, Zhang F, Vallerga CL, Restuadi R, Freydenzon A, Zwamborn RAJ, Hop PJ, Robinson MR, Gratten J, Visscher PM, Hannon E, Mill J, Brown MA, Laing NG, Mather KA, Sachdev PS, Ngo ST, Steyn FJ, Wallace L, Henders AK, Needham M, Veldink JH, Mathers S, Nicholson G, Rowe DB, Henderson RD, McCombe PA, Pamphlett R, Yang J, Blair IP, McRae AF, Wray NR. 2020. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. npj Genomic Medicine. 5, 10. View
Bevers RPJ, Litovchenko M, Kapopoulou A, Braman VS, Robinson MR, Auwerx J, Hollis B, Deplancke B. 2019. Mitochondrial haplotypes affect metabolic phenotypes in the Drosophila Genetic Reference Panel. Nature Metabolism. 1(12), 1226–1242. View
Delaneau O, Zagury J-F, Robinson MR, Marchini JL, Dermitzakis ET. 2019. Accurate, scalable and integrative haplotype estimation. Nature Communications. 10, 5436. View
Yap CX, Sidorenko J, Wu Y, Kemper KE, Yang J, Wray NR, Robinson MR, Visscher PM. 2018. Dissection of genetic variation and evidence for pleiotropy in male pattern baldness. Nature Communications. 9, 5407. View
since 2020 Assistant Professor, IST Austria
2017 – 2020 Assistant Professor, University of Lausanne, Switzerland
2013 – 2017 Postdoc, University of Queensland, Australia
2009 – 2013 NERC Junior Research Fellow, University of Sheffield, UK
2008 PhD, University of Edinburgh, UK
2019 SNSF Eccellenza Grant awardee
2010 NERC Research Fellowship