Privacy-preserving construction of generalized linear mixed model for biomedical computation

MOTIVATION: The generalized linear mixed model (GLMM) is an extension of the generalized linear model (GLM) in which the linear predictor takes random effects into account. Given its power of precisely modeling the mixed effects from multiple sources of random variations, the method has been widely...

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Detalles Bibliográficos
Autores principales: Zhu, Rui, Jiang, Chao, Wang, Xiaofeng, Wang, Shuang, Zheng, Hao, Tang, Haixu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Genome Privacy and Security
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355231/
https://www.ncbi.nlm.nih.gov/pubmed/32657380
http://dx.doi.org/10.1093/bioinformatics/btaa478

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7355231/
https://www.ncbi.nlm.nih.gov/pubmed/32657380
http://dx.doi.org/10.1093/bioinformatics/btaa478

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