Estimating High-Dimensional Directed Acyclic Graphs with the PC-Algorithm. - Markus Kalisch; Peter Bühlmann (J. Mach. Learn. Res., 2007)

Annotating novel genes by integrating synthetic lethals and genomic information. - Daniel Schöner; Markus Kalisch; Christian Leisner; Lukas Meier; Marc Sohrmann; Mahamadou Faty; Yves Barral; Matthias Peter; Wilhelm Gruissem; Peter Bühlmann (BMC Syst. Biol., 2008)

Robustified L2 boosting. - Roman Werner Lutz; Markus Kalisch; Peter Bühlmann (Comput. Stat. Data Anal., 2008)

Learning high-dimensional DAGs with latent and selection variables (Abstract). - Diego Colombo; Marloes H. Maathuis; Markus Kalisch; Thomas S. Richardson 001 (UAI, 2011)

Learning high-dimensional DAGs with latent and selection variables - Diego Colombo; Marloes H. Maathuis; Markus Kalisch; Thomas S. Richardson 001 (CoRR, 2011)

A Complete Generalized Adjustment Criterion. - Emilija Perkovic; Johannes Textor; Markus Kalisch; Marloes H. Maathuis (UAI, 2015)

Assessing statistical significance in multivariable genome wide association analysis. - Laura Buzdugan; Markus Kalisch; Arcadi Navarro; Daniel Schunk; Ernst Fehr; Peter Bühlmann (Bioinform., 2016)

Interpreting and Using CPDAGs With Background Knowledge. - Emilija Perkovic; Markus Kalisch; Marloes H. Maathuis (UAI, 2017)

Complete Graphical Characterization and Construction of Adjustment Sets in Markov Equivalence Classes of Ancestral Graphs. - Emilija Perkovic; Johannes Textor; Markus Kalisch; Marloes H. Maathuis (J. Mach. Learn. Res., 2017)

Hierarchical inference for genome-wide association studies: a view on methodology with software. - Claude Renaux; Laura Buzdugan; Markus Kalisch; Peter Bühlmann (Comput. Stat., 2020)

Rejoinder on: Hierarchical inference for genome-wide association studies: a view on methodology with software. - Claude Renaux; Laura Buzdugan; Markus Kalisch; Peter Bühlmann (Comput. Stat., 2020)