E. Bernabeu et al., “Refining epigenetic prediction of chronological and biological age,” Genome Medicine, vol. 15. Springer Nature, 2023.

S. E. Ojavee et al., “Genetic insights into the age-specific biological mechanisms governing human ovarian aging,” American Journal of Human Genetics, vol. 110, no. 9. Elsevier, pp. 1549–1563, 2023.

D. L. McCartney et al., “Blood-based epigenome-wide analyses of cognitive abilities,” Genome Biology, vol. 23, no. 1. Springer Nature, 2022.

E. J. Orliac et al., “Improving GWAS discovery and genomic prediction accuracy in biobank data,” Proceedings of the National Academy of Sciences of the United States of America, vol. 119, no. 31. Proceedings of the National Academy of Sciences, 2022.

E. Orliac et al., “Improving genome-wide association discovery and genomic prediction accuracy in biobank data.” Dryad, 2022.

S. E. Ojavee, Z. Kutalik, and M. R. Robinson, “Liability-scale heritability estimation for biobank studies of low-prevalence disease,” The American Journal of Human Genetics, vol. 109, no. 11. Elsevier, pp. 2009–2017, 2022.

M. Patxot et al., “Haematological changes from conception to childbirth: An indicator of major pregnancy complications,” European Journal of Haematology, vol. 109, no. 5. Wiley, pp. 566–575, 2022.

D. L. McCartney et al., “Blood-based epigenome-wide analyses of cognitive abilities.” Zenodo, 2021.

S. E. Ojavee et al., “Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis,” Nature Communications, vol. 12, no. 1. Nature Research, 2021.

M. R. Robinson, M. Patxot, M. Stojanov, S. Blum, and D. Baud, “Postpartum hemorrhage risk is driven by changes in blood composition through pregnancy,” Scientific Reports, vol. 11. Springer Nature, 2021.

M. Patxot et al., “Probabilistic inference of the genetic architecture underlying functional enrichment of complex traits,” Nature Communications, vol. 12, no. 1. Springer Nature, 2021.

M. R. Robinson, “Probabilistic inference of the genetic architecture of functional enrichment of complex traits.” Dryad, 2021.

M. F. Nabais et al., “Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis,” npj Genomic Medicine, vol. 5. Springer Nature, 2020.

J. Sulc et al., “Quantification of the overall contribution of gene-environment interaction for obesity-related traits,” Nature Communications, vol. 11. Springer Nature, 2020.

D. Trejo Banos et al., “Bayesian reassessment of the epigenetic architecture of complex traits,” Nature Communications, vol. 11. Springer Nature, 2020.

R. F. Hillary et al., “Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults,” Genome Medicine, vol. 12, no. 1. Springer Nature, 2020.

R. F. Hillary et al., “Additional file 2 of multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults.” Springer Nature, 2020.

O. Delaneau, J.-F. Zagury, M. R. Robinson, J. L. Marchini, and E. T. Dermitzakis, “Accurate, scalable and integrative haplotype estimation,” Nature Communications, vol. 10. Springer Nature, 2019.

R. P. J. Bevers et al., “Mitochondrial haplotypes affect metabolic phenotypes in the Drosophila Genetic Reference Panel,” Nature Metabolism, vol. 1, no. 12. Springer Nature, pp. 1226–1242, 2019.

J. Sulc et al., “Maximum likelihood method quantifies the overall contribution of gene-environment interaction to continuous traits: An application to complex traits in the UK Biobank,” bioRxiv. Cold Spring Harbor Laboratory, 2019.

Q. Zhang et al., “Genotype effects contribute to variation in longitudinal methylome patterns in older people,” Genome Medicine, vol. 10, no. 1. Springer Nature, 2018.

S. Tucci et al., “Evolutionary history and adaptation of a human pygmy population of Flores Island, Indonesia,” Science, vol. 361, no. 6401. American Association for the Advancement of Science, pp. 511–516, 2018.

C. X. Yap et al., “Dissection of genetic variation and evidence for pleiotropy in male pattern baldness,” Nature Communications, vol. 9. Springer Nature, 2018.

R. M. Maier et al., “Improving genetic prediction by leveraging genetic correlations among human diseases and traits,” Nature Communications, vol. 9. Springer Nature, 2018.

L. Yengo et al., “Imprint of assortative mating on the human genome,” Nature Human Behaviour, vol. 2, no. 12. Springer Nature, pp. 948–954, 2018.

Z. Zhu et al., “Causal associations between risk factors and common diseases inferred from GWAS summary data,” Nature Communications, vol. 9. Springer Nature, 2018.

J. Guo et al., “Global genetic differentiation of complex traits shaped by natural selection in humans,” Nature Communications, vol. 9. Springer Nature, 2018.

R. M. Maier, P. M. Visscher, M. R. Robinson, and N. R. Wray, “Embracing polygenicity: A review of methods and tools for psychiatric genetics research,” Psychological Medicine, vol. 48, no. 7. Cambridge University Press, pp. 1055–1067, 2018.

L. R. Lloyd-Jones, M. R. Robinson, J. Yang, and P. M. Visscher, “Transformation of summary statistics from linear mixed model association on all-or-none traits to odds ratio,” Genetics, vol. 208, no. 4. Genetics Society of America, pp. 1397–1408, 2018.

J. Zeng et al., “Signatures of negative selection in the genetic architecture of human complex traits,” Nature Genetics, vol. 50, no. 5. Springer Nature, pp. 746–753, 2018.

J. S. Sanjak, J. Sidorenko, M. R. Robinson, K. R. Thornton, and P. M. Visscher, “Evidence of directional and stabilizing selection in contemporary humans,” Proceedings of the National Academy of Sciences, vol. 115, no. 1. Proceedings of the National Academy of Sciences, pp. 151–156, 2018.

R. P. J. Bevers et al., “Extensive mitochondrial population structure and haplotype-specific phenotypic variation in the Drosophila Genetic Reference Panel,” bioRxiv. Cold Spring Harbor Laboratory, 2018.

F. C. Tropf et al., “Hidden heritability due to heterogeneity across seven populations,” Nature Human Behaviour, vol. 1, no. 10. Springer Nature, pp. 757–765, 2017.

D. Burger et al., “Major histocompatibility complex-linked social signalling affects female fertility,” Proceedings of the Royal Society B: Biological Sciences, vol. 284, no. 1868. The Royal Society, 2017.

L. Yengo et al., “Detection and quantification of inbreeding depression for complex traits from SNP data,” Proceedings of the National Academy of Sciences, vol. 114, no. 32. Proceedings of the National Academy of Sciences, pp. 8602–8607, 2017.

J. Reger, M. I. Lind, M. R. Robinson, and A. P. Beckerman, “Predation drives local adaptation of phenotypic plasticity,” Nature Ecology &; Evolution, vol. 2. Springer Nature, pp. 100–107, 2017.

F. C. Garton et al., “Whole exome sequencing and DNA methylation analysis in a clinical amyotrophic lateral sclerosis cohort,” Molecular Genetics &; Genomic Medicine, vol. 5, no. 4. Wiley, pp. 418–428, 2017.

L. R. Lloyd-Jones et al., “Inference on the genetic basis of eye and skin color in an admixed population via Bayesian linear mixed models,” Genetics, vol. 206, no. 2. Genetics Society of America, pp. 1113–1126, 2017.

W. J. Peyrot, M. R. Robinson, B. W. J. H. Penninx, and N. R. Wray, “Exploring boundaries for the genetic consequences of assortative mating for psychiatric traits,” JAMA Psychiatry, vol. 73, no. 11. American Medical Association, pp. 1189–1195, 2016.

G.-B. Chen, S. H. Lee, Z.-X. Zhu, B. Benyamin, and M. R. Robinson, “EigenGWAS: Finding loci under selection through genome-wide association studies of eigenvectors in structured populations,” Heredity, vol. 117. Springer Nature, pp. 51–61, 2016.

Z. Zhu et al., “Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets,” Nature Genetics, vol. 48, no. 5. Springer Nature, pp. 481–487, 2016.

M. R. Robinson et al., “Population genetic differentiation of height and body mass index across Europe,” Nature Genetics, vol. 47, no. 11. Springer Nature, pp. 1357–1362, 2015.

M. J. Adams, M. R. Robinson, M.-E. Mannarelli, and B. J. Hatchwell, “Social genetic and social environment effects on parental and helper care in a cooperatively breeding bird,” Proceedings of the Royal Society B: Biological Sciences, vol. 282, no. 1810. The Royal Society, 2015.

A. W. Santure et al., “Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations,” Molecular Ecology, vol. 24. Wiley, pp. 6148–6162, 2015.

M. R. Robinson and A. Qvarnström, “Influence of the environment on the genetic architecture of traits involved in sexual selection within wild populations,” in Genotype-by-Environment Interactions and Sexual Selection, J. Hunt and D. Hosken, Eds. Chichester, UK: Wiley, 2014, pp. 137–168.

M. R. Robinson, N. R. Wray, and P. M. Visscher, “Explaining additional genetic variation in complex traits,” Trends in Genetics, vol. 30, no. 4. Elsevier, pp. 124–132, 2014.

M. R. Robinson, A. W. Santure, I. DeCauwer, B. C. Sheldon, and J. Slate, “Partitioning of genetic variation across the genome using multimarker methods in a wild bird population,” Molecular Ecology, vol. 22, no. 15. Wiley, pp. 3963–3980, 2013.

A. W. Santure, I. De Cauwer, M. R. Robinson, J. Poissant, B. C. Sheldon, and J. Slate, “Genomic dissection of variation in clutch size and egg mass in a wild great tit (Parus major) population,” Molecular Ecology, vol. 22, no. 15. Wiley, pp. 3949–3962, 2013.

M. R. Robinson and A. P. Beckerman, “Quantifying multivariate plasticity: Genetic variation in resource acquisition drives plasticity in resource allocation to components of life history,” Ecology Letters, vol. 16, no. 3. Wiley, pp. 281–290, 2013.

M. R. Robinson, K. U. Mar, and V. Lummaa, “Senescence and age-specific trade-offs between reproduction and survival in female Asian elephants,” Ecology Letters, vol. 15, no. 3. Wiley, pp. 260–266, 2012.

M. R. Robinson, G. Sander van Doorn, L. Gustafsson, and A. Qvarnström, “Environment-dependent selection on mate choice in a natural population of birds,” Ecology Letters, vol. 15, no. 6. Wiley, pp. 611–618, 2012.

M. R. Robinson, “Understanding intrasexual competition and sexual selection requires an evolutionary ecology framework,” Behavioral Ecology, vol. 22, no. 6. Oxford University Press, pp. 1143–1144, 2011.

M. R. Robinson, A. J. Wilson, J. G. Pilkington, T. H. Clutton-Brock, J. M. Pemberton, and L. E. B. Kruuk, “The impact of environmental heterogeneity on genetic architecture in a wild population of soay sheep,” Genetics, vol. 181, no. 4. Genetics Society of America, pp. 1639–1648, 2009.

M. R. Robinson, J. G. Pilkington, T. H. Clutton-Brock, J. M. Pemberton, and L. E. B. Kruuk, “Environmental heterogeneity generates fluctuating selection on a secondary sexual trait,” Current Biology, vol. 18, no. 10. Elsevier, pp. 751–757, 2008.

M. R. Robinson and L. E. . Kruuk, “Function of weaponry in females: The use of horns in intrasexual competition for resources in female Soay sheep,” Biology Letters, vol. 3, no. 6. The Royal Society, pp. 651–654, 2007.

M. R. Robinson, J. G. Pilkington, T. H. Clutton-Brock, J. M. Pemberton, and L. E. B. Kruuk, “Live fast, die young: Trade-offs between fitness components and sexually antagonistic selection on weaponry in soay sheep,” Evolution, vol. 60, no. 10. Wiley, pp. 2168–2181, 2007.