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Statistical Methods in Medical Research|November 26, 2011
Controlling false positive selections in high-dimensional regression and causal inferencePeter Bühlmann, Philipp Rütimann, Markus KalischBiometrical Journal. Biometrische Zeitschrift|March 10, 2010
Decomposition and model selection for large contingency tablesCorinne Dahinden, Markus Kalisch, Peter BühlmannBioinformatics (Oxford, England)|May 7, 2016
Assessing statistical significance in multivariable genome wide association analysisLaura Buzdugan, Markus Kalisch, Arcadi Navarro, et al.BMC Medical Research Methodology|February 13, 2010
Understanding human functioning using graphical modelsMarkus Kalisch, Bernd A G Fellinghauer, Eva Grill, et al.Methods in Molecular Biology (Clifton, N.J.)|April 30, 2014
A flexible protocol for targeted gene co-expression network analysisDiana Coman, Philipp Rütimann, Wilhelm GruissemBMC Systems Biology|January 16, 2008
Annotating novel genes by integrating synthetic lethals and genomic informationDaniel Schöner, Markus Kalisch, Christian Leisner, et al.The New Phytologist|July 31, 2015
Arabidopsis GERANYLGERANYL DIPHOSPHATE SYNTHASE 11 is a hub isozyme required for the production of most photosynthesis-related isoprenoidsM Águila Ruiz-Sola, Diana Coman, Gilles Beck, et al.Statistical Applications in Genetics and Molecular Biology|May 2, 2006
Low-order conditional independence graphs for inferring genetic networksAnja Wille, Peter BühlmannNeural Computation|January 21, 2015
Structural intervention distance for evaluating causal graphsJonas Peters, Peter BühlmannBioinformatics (Oxford, England)|August 31, 2006
Model-based boosting in high dimensionsTorsten Hothorn, Peter BühlmannPageof 6