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Group by: Date | Item Type | Source
Jump to: 2018 | 2017 | 2016 | 2015 | 2014 | 2013 | 2012 | 2011 | 2010 | 2009 | 2008

2018

Deep learning of genomic variation and regulatory network data.
Telenti, A. and Lippert, C. and Chang, P.C. and DePristo, M.
Human Molecular Genetics 10 April 2018 (In Press)

2017

Ensembles of lasso screening rules.
Lee, S. and Görnitz, N. and Xing, E.P. and Heckerman, D. and Lippert, C.
IEEE Transactions on Pattern Analysis and Machine Intelligence 24 November 2017 (In Press)

Profiling of short-tandem-repeat disease alleles in 12,632 human whole genomes.
Tang, H. and Kirkness, E.F. and Lippert, C. and Biggs, W.H. and Fabani, M. and Guzman, E. and Ramakrishnan, S. and Lavrenko, V. and Kakaradov, B. and Hou, C. and Hicks, B. and Heckerman, D. and Och, F.J. and Caskey, C.T. and Venter, J.C. and Telenti, A.
American Journal of Human Genetics 101 (5): 700-715. 2 November 2017

No major flaws in "Identification of individuals by trait prediction using whole-genome sequencing data".
Lippert, C. and Sabatini, R. and Maher, M.C. and Kang, E.Y. and Lee, S. and Arikan, O. and Harley, A. and Bernal, A. and Garst, P. and Lavrenko, V. and Yocum, K. and Wong, T.M. and Zhu, M. and Yang, W.Y.n and Chang, C. and Hicks, B. and Ramakrishnan, S. and Tang, H. and Xie, C. and Brewerton, S. and Turpaz, Y. and Telenti, A. and Roby, R.K. and Och, F. and Venter, J.C.
bioRxiv : 187542. 19 October 2017

Sparse probit linear mixed model.
Mandt, S. and Wenzel, F. and Nakajima, S. and Cunningham, J. and Lippert, C. and Kloft, M.
Machine Learning 106 (9-10): 1621-1642. October 2017

Identification of individuals by trait prediction using whole-genome sequencing data.
Lippert, C. and Sabatini, R. and Maher, M.C. and Kang, E.Y. and Lee, S. and Arikan, O. and Harley, A. and Bernal, A. and Garst, P. and Lavrenko, V. and Yocum, K. and Wong, T. and Zhu, M. and Yang, W.Y. and Chang, C. and Lu, T. and Lee, C.W.H. and Hicks, B. and Ramakrishnan, S. and Tang, H. and Xie, C. and Piper, J. and Brewerton, S. and Turpaz, Y. and Telenti, A. and Roby, R.K. and Och, F.J. and Venter, J.C.
Proceedings of the National Academy of Sciences of the United States of America 114 (38): 10166-10171. 19 September 2017

easyGWAS: a cloud-based platform for comparing the results of genome-wide association studies.
Grimm, D.G. and Roqueiro, D. and Salome, P.A. and Kleeberger, S. and Greshake, B. and Zhu, W. and Liu, C. and Lippert, C. and Stegle, O. and Schoelkopf, B. and Weigel, D. and Borgwardt, K.M.
Plant Cell 29 (1): 5-19. January 2017

2016

Separating sparse signals from correlated noise in binary classification.
Mandt, S. and Wenzel, F. and Nakajima, S. and Lippert, C. and Kloft, M.
CEUR Workshop Proceedings 1792 : 48-58. 2016

2015

Efficient set tests for the genetic analysis of correlated traits.
Casale, F.P. and Rakitsch, B. and Lippert, C. and Stegle, O.
Nature Methods 12 (8): 755-758. August 2015

Computational and statistical issues in personalized medicine.
Lippert, C. and Hackerman, D.
XRDS: Crossroads, The ACM Magazine for Students 21 (4): 24-27. 27 July 2015

Accurate liability estimation improves power in ascertained case-control studies.
Weissbrod, O. and Lippert, C. and Geiger, D. and Heckerman, D.
Nature Methods 12 (4): 332-334. April 2015

Finding sparse features in strongly confounded medical binary data.
Mandt, S. and Wenzel, F. and Nakajima, S. and Cunningham, J. and Lippert, C. and Kloft, M.
NIPS workshop on Machine Learning For Healthcare 2015

2014

Greater power and computational efficiency for kernel-based association testing of sets of genetic variants.
Lippert, C. and Xiang, J. and Horta, D. and Widmer, C. and Kadie, C. and Heckerman, D. and Listgarten, J.
Bioinformatics 30 (22): 3206-3214. 15 November 2014

Further improvements to linear mixed models for genome-wide association studies.
Widmer, C. and Lippert, C. and Weissbrod, O. and Fusi, N. and Kadie, C. and Davidson, R. and Listgarten, J. and Heckerman, D.
Scientific Reports 4 : 6874. 12 November 2014

Warped linear mixed models for the genetic analysis of transformed phenotypes.
Fusi, N. and Lippert, C. and Lawrence, N.D. and Stegle, O.
Nature Communications 5 : 4890. 19 September 2014

LIMIX: genetic analysis of multiple traits.
Lippert, C. and Casale, F.P. and Rakitsch, B. and Stegle, O.
bioRxiv : 003905. 22 May 2014

Quantifying the uncertainty in heritability.
Furlotte, N.A. and Heckerman, D. and Lippert, C.
Journal of Human Genetics 59 (5): 269-275. May 2014

Epigenome-wide association studies without the need for cell-type composition.
Zou, J. and Lippert, C. and Heckerman, D. and Aryee, M. and Listgarten, J.
Nature Methods 11 (3): 309-311. March 2014

2013

It is all in the noise: efficient multi-task Gaussian process inference with structured residuals.
Rakitsch, B. and Lippert, C. and Borgwardt, K. and Stegle, O.
In: 27th Annual Conference on Neural Information Processing Systems, 5-10 Dec 2013, Lake Tahoe, United States of America. December 2013

A genome-to-genome analysis of associations between human genetic variation, HIV-1 sequence diversity, and viral control.
Bartha, I. and Carlson, J.M. and Brumme, C.J. and McLaren, P.J. and Brumme, Z.L. and John, M. and Haas, D.W. and Martinez-Picado, J. and Dalmau, J. and Lopez-Galindez, C. and Casado, C. and Rauch, A. and Guenthard, H.F. and Bernasconi, E. and Vernazza, P. and Klimkait, T. and Yerly, S. and O'Brien, S.J. and Listgarten, J. and Pfeifer, N. and Lippert, C. and Fusi, N. and Kutalik, Z. and Allen, T.M. and Mueller, V. and Harrigan, P.R. and Heckerman, D. and Telenti, A. and Fellay, J.
eLife 2 : e01123. 29 October 2013

A powerful and efficient set test for genetic markers that handles confounders.
Listgarten, J. and Lippert, C. and Kang, E.Y. and Xiang, J. and Kadie, C.M. and Heckerman, D.
Bioinformatics 29 (12): 1526-1533. 15 June 2013

Detecting regulatory gene-environment interactions with unmeasured environmental factors.
Fusi, N. and Lippert, C. and Borgwardt, K. and Lawrence, N.D. and Stegle, O.
Bioinformatics 29 (11): 1382-1389. 1 June 2013

The benefits of selecting phenotype-specific variants for applications of mixed models in genomics.
Lippert, C. and Quon, G. and Kang, E.Y. and Kadie, C.M. and Listgarten, J. and Heckerman, D.
Scientific Reports 3 : 1815. 9 May 2013

FaST-LMM-Select for addressing confounding from spatial structure and rare variants.
Listgarten, J. and Lippert, C. and Heckerman, D.
Nature Genetics 45 (5): 470-471. May 2013

Patterns of methylation heritability in a genome-wide analysis of four brain regions.
Quon, G. and Lippert, C. and Heckerman, D. and Listgarten, J.
Nucleic Acids Research 41 (4): 2095-2104. 1 February 2013

An exhaustive epistatic SNP association analysis on expanded Wellcome Trust data.
Lippert, C. and Listgarten, J. and Davidson, R.I. and Baxter, J. and Poon, H. and Kadie, C.M. and Heckerman, D.
Scientific Reports 3 : 1099. 22 January 2013

A Lasso multi-marker mixed model for association mapping with population structure correction.
Rakitsch, B. and Lippert, C. and Stegle, O. and Borgwardt, K.
Bioinformatics 29 (2): 206-214. 15 January 2013

2012

Extraneous markers used for genetic similarity leads to loss of power in GWAS and heritability determination.
Lippert, C. and Quon, G. and Listgarten, J. and Heckerman, D.
3 December 2012

Improved linear mixed models for genome-wide association studies.
Listgarten, J. and Lippert, C. and Kadie, C.M. and Davidson, R.I. and Eskin, E. and Heckerman, D.
Nature Methods 9 (6): 525-526. 30 May 2012

2011

FaST linear mixed models for genome-wide association studies.
Lippert, C. and Listgarten, J. and Liu, Y. and Kadie, C.M. and Davidson, R.I. and Heckerman, .
Nature Methods 8 (10): 833-835. 4 September 2011

Whole-genome sequencing of multiple Arabidopsis thaliana populations.
Cao, J. and Schneeberger, K. and Ossowski, S. and Guenther, T. and Bender, S. and Fitz, J. and Koenig, D. and Lanz, C. and Stegle, O. and Lippert, C. and Wang, X. and Ott, F. and Mueller, J. and Alonso-Blanco, C. and Borgwardt, K. and Schmid, K.J. and Weigel, D.
Nature Genetics 43 (10): 956-963. 28 August 2011

Efficient inference in matrix-variate Gaussian models with iid observation noise.
Stegle, O. and Lippert, C. and Mooij, J. and Lawrence, N. and Borgwardt, K.
Advances in Neural Information Processing Systems 24 : 1-9. 2011

2010

Gene function prediction from synthetic lethality networks via ranking on demand.
Lippert, C. and Ghahramani, Z. and Borgwardt, K.M.
Bioinformatics 26 (7): 912-918. 1 April 2010

2009

A kernel method for unsupervised structured network inference.
Lippert, C. and Stegle, O. and Ghahramani, Z. and Borgwardt, K.M.
Journal of Machine Learning Research 5 : 368-375. 2009

Relational models for generating labeled real-world graphs.
Lippert, C. and Shervashidze, N. and Stegle, O.
In: 7th International Workshop on Mining and Learning with Graphs, 2-4 July 2009, Leuven, Belgium. 2009

2008

Relation prediction in multi-relational domains using matrix factorization.
Lippert, C. and Weber, S.H. and Huang, Y. and Tresp, V. and Schubert, M. and Kriegel, H.P.
Proceedings of the NIPS 2008 Workshop 2008

This list was generated on Sun Apr 22 02:23:35 2018 CEST.
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