Christoph Lippert

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David HeckermanMicrosoft ResearchVerified email at microsoft.com
Oliver StegleGerman Cancer Research Center (DKFZ) & EMBL HeidelbergVerified email at dkfz.de
Jennifer ListgartenProfessor, UC Berkeley EECS and Center for Computational BiologyVerified email at berkeley.edu
Karsten BorgwardtDirector, Max Planck Institute of BiochemistryVerified email at biochem.mpg.de
Carl KadieMicrosoft Research (retired)Verified email at benkadie.com
Benjamin BergnerPhD candidate, Hasso Plattner InstituteVerified email at hpi.de
Stefan KonigorskiSenior Researcher, Hasso Plattner InstituteVerified email at hpi.de
Barbara RakitschBosch Center for AIVerified email at de.bosch.com
Aiham TalebAmazon Web ServicesVerified email at amazon.de
Detlef WeigelMax Planck Institute for Biology TübingenVerified email at weigelworld.org
Matthias KirchlerHasso Plattner Institute, TU KaiserslauternVerified email at hpi.de
Remo MontiHasso Plattner Institute, Berlin Institute for Medical Systems BiologyVerified email at mdc-berlin.de
Neil D. LawrenceUniversity of CambridgeVerified email at cl.cam.ac.uk
Marius KloftProfessor, RPTU Kaiserslautern-LandauVerified email at cs.uni-kl.de
Nicolò FusiPartner Researcher, Microsoft ResearchVerified email at microsoft.com
Eun Yong KangMachine Learning, MicrosoftVerified email at microsoft.com
Jana FehrBerlin Institute of Health at CharitéVerified email at bih-charite.de
Jun CaoCorteva AgriscienceVerified email at corteva.com
Karl SchmidProfessor of Crop Biodiversity and Breeding Informatics, University of Hohenheim, Stuttgart, GermanyVerified email at uni-hohenheim.de
Korbinian SchneebergerLudwig-Maximilians-University Munich (LMU); Max Planck Institute for Plant Breeding ResearchVerified email at lmu.de

Christoph Lippert

Professor, Hasso Plattner Institute, Universität Potsdam

Verified email at hpi.de - Homepage

Statistical Genetics Computational Biology Machine Learning Bioinformatics Digital Health


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FaST linear mixed models for genome-wide association studies C Lippert, J Listgarten, Y Liu, CM Kadie, RI Davidson, D Heckerman Nature Methods 8 (10), 833-835, 2011	1314	2011
Whole-genome sequencing of multiple Arabidopsis thaliana populations J Cao, K Schneeberger, S Ossowski, T Günther, S Bender, J Fitz, ... Nature genetics 43 (10), 956-963, 2011	1097	2011
Improved linear mixed models for genome-wide association studies J Listgarten, C Lippert, CM Kadie, RI Davidson, E Eskin, D Heckerman Nature methods 9 (6), 525-526, 2012	390	2012
Epigenome-wide association studies without the need for cell-type composition J Zou, C Lippert, D Heckerman, M Aryee, J Listgarten Nature methods 11 (3), 309-311, 2014	259	2014
3d self-supervised methods for medical imaging A Taleb, W Loetzsch, N Danz, J Severin, T Gaertner, B Bergner, C Lippert Advances in neural information processing systems 33, 18158-18172, 2020	233	2020
Time to reality check the promises of machine learning-powered precision medicine J Wilkinson, KF Arnold, EJ Murray, M van Smeden, K Carr, R Sippy, ... The Lancet Digital Health 2 (12), e677-e680, 2020	211	2020
Identification of individuals by trait prediction using whole-genome sequencing data C Lippert, R Sabatini, MC Maher, EY Kang, S Lee, O Arikan, A Harley, ... Proceedings of the National Academy of Sciences 114 (38), 10166-10171, 2017	203	2017
Profiling of short-tandem-repeat disease alleles in 12,632 human whole genomes H Tang, EF Kirkness, C Lippert, WH Biggs, M Fabani, E Guzman, ... The American Journal of Human Genetics 101 (5), 700-715, 2017	164	2017
A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control I Bartha, JM Carlson, CJ Brumme, PJ McLaren, ZL Brumme, M John, ... elife 2, e01123, 2013	147	2013
A Lasso multi-marker mixed model for association mapping with population structure correction B Rakitsch, C Lippert, O Stegle, K Borgwardt Bioinformatics 29 (2), 206-214, 2013	135	2013
Multimodal self-supervised learning for medical image analysis A Taleb, C Lippert, T Klein, M Nabi International conference on information processing in medical imaging, 661-673, 2021	133	2021
LIMIX: genetic analysis of multiple traits C Lippert, FP Casale, B Rakitsch, O Stegle BioRxiv, 003905, 2014	122	2014
Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies D Reichart, EL Lindberg, H Maatz, AMA Miranda, A Viveiros, N Shvetsov, ... Science 377 (6606), eabo1984, 2022	118	2022
easyGWAS: a cloud-based platform for comparing the results of genome-wide association studies DG Grimm, D Roqueiro, PA Salomé, S Kleeberger, B Greshake, W Zhu, ... The Plant Cell 29 (1), 5-19, 2017	118	2017
Efficient set tests for the genetic analysis of correlated traits FP Casale, B Rakitsch, C Lippert, O Stegle Nature methods 12 (8), 755-758, 2015	117	2015
Efﬁcient inference in matrix-variate Gaussian models with iid observation noise O Stegle, C Lippert, J Mooij, N Lawrence, K Borgwardt NIPS 2011: Neural Information Processing Systems, 2011	107	2011
A powerful and efficient set test for genetic markers that handles confounders J Listgarten, C Lippert, EY Kang, J Xiang, CM Kadie, D Heckerman Bioinformatics 29 (12), 1526-1533, 2013	97	2013
An Exhaustive Epistatic SNP Association Analysis on Expanded Wellcome Trust Data C Lippert, J Listgarten, RI Davidson, S Baxter, H Poong, C Kadie, ... Scientific Reports 3, 2013	91	2013
Further improvements to linear mixed models for genome-wide association studies C Widmer, C Lippert, O Weissbrod, N Fusi, C Kadie, R Davidson, ... Scientific reports 4 (1), 6874, 2014	89	2014
It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals B Rakitsch, C Lippert, K Borgwardt, O Stegle Advances in neural information processing systems 26, 2013	89	2013

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