Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Matthieu de Rochemonteix"'
Autor:
Emily K. Mallory, Matthieu de Rochemonteix, Alex Ratner, Ambika Acharya, Chris Re, Roselie A. Bright, Russ B. Altman
Publikováno v:
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
Abstract Background Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these databases struggle to keep up with the exponential growth of the biomedical literatu
Externí odkaz:
https://doaj.org/article/9cb4eacf8100417aadbb541d13cecffd
Autor:
Nilotpal Sanyal, Nilanjan Chatterjee, Valerio Napolioni, Michael E. Belloy, Michael D. Greicius, Neil E. Caporaso, Maria Teresa Landi, Summer S. Han, Matthieu de Rochemonteix
Publikováno v:
Am J Epidemiol
Evaluating gene by environment (G × E) interaction under an additive risk model (i.e., additive interaction) has gained wider attention. Recently, statistical tests have been proposed for detecting additive interaction, utilizing an assumption on ge
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::38d1f1f66ea34d3bfc3f3eca0e07a61a
https://doi.org/10.1093/aje/kwab124
https://doi.org/10.1093/aje/kwab124
Autor:
Alexander Ratner, Matthieu de Rochemonteix, Christopher Ré, Emily K. Mallory, Ambika Acharya, Russ B. Altman, Roselie A. Bright
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
BMC Bioinformatics, Vol 21, Iss 1, Pp 1-15 (2020)
Background Enzymatic and chemical reactions are key for understanding biological processes in cells. Curated databases of chemical reactions exist but these databases struggle to keep up with the exponential growth of the biomedical literature. Conve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e78deb34b932f5689710575999ea17ae
https://doi.org/10.1186/s12859-020-03542-1
https://doi.org/10.1186/s12859-020-03542-1
Autor:
Nilotpal Sanyal, Maria Teresa Landi, Matthieu de Rochemonteix, Valerio Napolioni, Neil E. Caporaso, Michael D. Greicius, Michael E. Belloy, Summer S. Han, Nilanjan Chatterjee
Publikováno v:
Am J Epidemiol
Several statistical methods have been proposed for testing gene-environment (G-E) interactions under additive risk models using data from genome-wide association studies. However, these approaches have strong assumptions from underlying genetic model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b992658028f705b47801c2b9fcc8adde
http://hdl.handle.net/11581/447104
http://hdl.handle.net/11581/447104
