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Christoph Lippert

Showing results (21-30 of 57) with videos related to

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Nature Methods|June 7, 2012
Improved linear mixed models for genome-wide association studiesJennifer Listgarten, Christoph Lippert, Carl M Kadie, et al.
Scientific Reports|May 10, 2013
The benefits of selecting phenotype-specific variants for applications of mixed models in genomicsChristoph Lippert, Gerald Quon, Eun Yong Kang, et al.
Nature Methods|September 6, 2011
FaST linear mixed models for genome-wide association studiesChristoph Lippert, Jennifer Listgarten, Ying Liu, et al.
Bioinformatics (Oxford, England)|July 31, 2014
Greater power and computational efficiency for kernel-based association testing of sets of genetic variantsChristoph Lippert, Jing Xiang, Danilo Horta, et al.
Bioinformatics (Oxford, England)|April 20, 2013
A powerful and efficient set test for genetic markers that handles confoundersJennifer Listgarten, Christoph Lippert, Eun Yong Kang, et al.
Bioinformatics (Oxford, England)|May 31, 2022
transferGWAS: GWAS of images using deep transfer learningMatthias Kirchler, Stefan Konigorski, Matthias Norden, et al.
NAR Genomics and Bioinformatics|October 13, 2022
AntiSplodge: a neural-network-based RNA-profile deconvolution pipeline designed for spatial transcriptomicsJesper B Lund, Eric L Lindberg, Henrike Maatz, et al.
NPJ Digital Medicine|January 22, 2026
Large language models improve transferability of electronic health record-based predictions across countries and coding systemsMatthias Kirchler, Matteo Ferro, Veronica Lorenzini, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 15, 2021
Predicting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phonesSten Rüdiger, Stefan Konigorski, Alexander Rakowski, et al.
Scientific Reports|November 13, 2014
Further improvements to linear mixed models for genome-wide association studiesChristian Widmer, Christoph Lippert, Omer Weissbrod, et al.
Pageof 6

Showing results (21-30 of 57) with videos related to

Sort By:
Pageof 6
Nature Methods|June 7, 2012
Improved linear mixed models for genome-wide association studiesJennifer Listgarten, Christoph Lippert, Carl M Kadie, et al.
Scientific Reports|May 10, 2013
The benefits of selecting phenotype-specific variants for applications of mixed models in genomicsChristoph Lippert, Gerald Quon, Eun Yong Kang, et al.
Nature Methods|September 6, 2011
FaST linear mixed models for genome-wide association studiesChristoph Lippert, Jennifer Listgarten, Ying Liu, et al.
Bioinformatics (Oxford, England)|July 31, 2014
Greater power and computational efficiency for kernel-based association testing of sets of genetic variantsChristoph Lippert, Jing Xiang, Danilo Horta, et al.
Bioinformatics (Oxford, England)|April 20, 2013
A powerful and efficient set test for genetic markers that handles confoundersJennifer Listgarten, Christoph Lippert, Eun Yong Kang, et al.
Bioinformatics (Oxford, England)|May 31, 2022
transferGWAS: GWAS of images using deep transfer learningMatthias Kirchler, Stefan Konigorski, Matthias Norden, et al.
NAR Genomics and Bioinformatics|October 13, 2022
AntiSplodge: a neural-network-based RNA-profile deconvolution pipeline designed for spatial transcriptomicsJesper B Lund, Eric L Lindberg, Henrike Maatz, et al.
NPJ Digital Medicine|January 22, 2026
Large language models improve transferability of electronic health record-based predictions across countries and coding systemsMatthias Kirchler, Matteo Ferro, Veronica Lorenzini, et al.
Proceedings of the National Academy of Sciences of the United States of America|July 15, 2021
Predicting the SARS-CoV-2 effective reproduction number using bulk contact data from mobile phonesSten Rüdiger, Stefan Konigorski, Alexander Rakowski, et al.
Scientific Reports|November 13, 2014
Further improvements to linear mixed models for genome-wide association studiesChristian Widmer, Christoph Lippert, Omer Weissbrod, et al.
Pageof 6