Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Marco Banterle"'
Publikováno v:
Journal of Statistical Software, Vol 100, Pp 1-32 (2021)
In molecular biology, advances in high-throughput technologies have made it possible to study complex multivariate phenotypes and their simultaneous associations with high-dimensional genomic and other omics data, a problem that can be studied with h
Externí odkaz:
https://doaj.org/article/797d6b76f6b0479d842607d50bc0bf30
Publikováno v:
Banterle, M, Grazian, C, Lee, A & Robert, C 2019, ' Accelerating Metropolis-Hastings algorithms by Delayed Acceptance ', Foundations of Data Science, vol. 1, no. 2, pp. 103-128 . https://doi.org/10.3934/fods.2019005
MCMC algorithms such as Metropolis-Hastings algorithms are slowed down by the computation of complex target distributions as exemplified by huge datasets. We offer in this paper a useful generalisation of the Delayed Acceptance approach, devised to r
Autor:
Marjo-Riitta Järvelin, Mika Ala-Korpela, Leonardo Bottolo, Alex Lewin, Marco Banterle, Sylvia Richardson
Publikováno v:
Journal of the Royal Statistical Society. Series C, Applied statistics
Funder: Victorian Government’s Operational Infrastructure Support Program
Our work is motivated by the search for metabolite quantitative trait loci (QTL) in a cohort of more than 5000 people. There are 158 metabolites measured by NMR spectros
Our work is motivated by the search for metabolite quantitative trait loci (QTL) in a cohort of more than 5000 people. There are 158 metabolites measured by NMR spectros
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1e671eed79d95103ff0a8f87dc3fe587
https://doi.org/10.1101/467019
https://doi.org/10.1101/467019
Autor:
N. Maneka G. De Silva, Sylvain Sebert, Alexessander Couto Alves, Ulla Sovio, Shikta Das, Rob Taal, Nicole M. Warrington, Alexandra M. Lewin, Marika Kaakinen, Diana Cousminer, Elisabeth Thiering, Nicholas J. Timpson, Ville Karhunen, Tom Bond, Xavier Estivill, Virpi Lindi, Jonathan P. Bradfield, Frank Geller, Lachlan J.M. Coin, Marie Loh, Sheila J. Barton, Lawrence J. Beilin, Hans Bisgaard, Klaus Bønnelykke, Rohia Alili, Ida J. Hatoum, Katharina Schramm, Rufus Cartwright, Marie-Aline Charles, Vincenzo Salerno, Karine Clément, Cornelia M. van Duijn, Elena Moltchanova, Johan G. Eriksson, Cathy Elks, Bjarke Feenstra, Claudia Flexeder, Stephen Franks, Timothy M. Frayling, Rachel M. Freathy, Paul Elliott, Elisabeth Widén, Hakon Hakonarson, Andrew T. Hattersley, Alina Rodriguez, Marco Banterle, Joachim Heinrich, Barbara Heude, John W. Holloway, Albert Hofman, Elina Hyppönen, Hazel Inskip, Lee M. Kaplan, Asa K. Hedman, Esa Läärä, Holger Prokisch, Harald Grallert, Timo A. Lakka, Debbie A. Lawlor, Mads Melbye, Tarunveer S. Ahluwalia, Marcella Marinelli, Iona Y. Millwood, Lyle J. Palmer, Craig E. Pennell, John R. Perry, Susan M. Ring, Markku Savolainen, Kari Stefansson, Gudmar Thorleifsson, Fernando Rivadeneira, Marie Standl, Jordi Sunyer, Carla M.T. Tiesler, Andre G. Uitterlinden, Inga Prokopenko, Karl-Heinz Herzig, George Davey Smith, Paul O'Reilly, Janine F. Felix, Jessica L. Buxton, Alexandra I.F. Blakemore, Ken K. Ong, Struan F.A. Grant, Vincent W.V. Jaddoe, Mark I. McCarthy, Marjo-Riitta Järvelin
Publikováno v:
bioRxiv
bioRxiv The Preprint Server for Biology.
bioRxiv The Preprint Server for Biology.
Early childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b364b3d95ff7602ee9e18bad1640ac56