Sequential Monte Carlo EM for multivariate probit models. - Giusi Moffa; Jack Kuipers (Comput. Stat. Data Anal., 2014)

Uniform random generation of large acyclic digraphs. - Jack Kuipers; Giusi Moffa (Stat. Comput., 2015)

pathTiMEx: Joint Inference of Mutually Exclusive Cancer Pathways and Their Dependencies in Tumor Progression. - Simona Cristea; Jack Kuipers; Niko Beerenwinkel (RECOMB, 2016)

Tree Inference for Single-Cell Data. - Katharina Jahn 001; Jack Kuipers; Niko Beerenwinkel (RECOMB, 2016)

Large-scale inference of conjunctive Bayesian networks. - Hesam Montazeri; Jack Kuipers; Roger D. Kouyos; Jürg Böni; Sabine Yerly; Thomas Klimkait; Vincent Aubert; Huldrych F. Günthard; Niko Beerenwinkel; The Swiss Hiv Cohort Study (Bioinform., 2016)

Detailed simulation of cancer exome sequencing data reveals differences and common limitations of variant callers. - Ariane L. Hofmann; Jonas Behr; Jochen Singer; Jack Kuipers; Christian Beisel; Peter Schraml; Holger Moch; Niko Beerenwinkel (BMC Bioinform., 2017)

pathTiMEx: Joint Inference of Mutually Exclusive Cancer Pathways and Their Progression Dynamics. - Simona Cristea; Jack Kuipers; Niko Beerenwinkel (J. Comput. Biol., 2017)

Multistate nested canalizing functions and their networks. - Claus Kadelka; Yuan Li; Jack Kuipers; John O. Adeyeye; Reinhard C. Laubenbacher (Theor. Comput. Sci., 2017)

Integrative Inference of Subclonal Tumour Evolution from Single-Cell and Bulk Sequencing Data. - Salem Malikic; Katharina Jahn 001; Jack Kuipers; Süleyman Cenk Sahinalp; Niko Beerenwinkel (RECOMB, 2018)

SCIΦ: Single-Cell Mutation Identification via Phylogenetic Inference. - Jochen Singer; Jack Kuipers; Katharina Jahn 001; Niko Beerenwinkel (RECOMB, 2018)

Improved pathway reconstruction from RNA interference screens by exploiting off-target effects. - Sumana Srivatsa; Jack Kuipers; Fabian Schmich; Simone Eicher; Mario Emmenlauer; Christoph Dehio; Niko Beerenwinkel (Bioinform., 2018)

Efficient Structure Learning and Sampling of Bayesian Networks. - Jack Kuipers; Polina Suter; Giusi Moffa (CoRR, 2018)

Predicting colorectal cancer risk from adenoma detection via a two-type branching process model. - Brian Lang; Jack Kuipers; Benjamin Misselwitz; Niko Beerenwinkel (PLoS Comput. Biol., 2020)

Benchpress: a scalable and platform-independent workflow for benchmarking structure learning algorithms for graphical models. - Felix L. Rios; Giusi Moffa; Jack Kuipers (CoRR, 2021)

Marginalization in Bayesian Networks: Integrating Exact and Approximate Inference. - Fritz M. Bayer; Giusi Moffa; Niko Beerenwinkel; Jack Kuipers (CoRR, 2021)

Learning Bayesian Networks from Ordinal Data. - Xiang Ge Luo; Giusi Moffa; Jack Kuipers (J. Mach. Learn. Res., 2021)

Statistical tests for intra-tumour clonal co-occurrence and exclusivity. - Jack Kuipers; Ariane L. Moore; Katharina Jahn 001; Peter Schraml; Feng Wang; Kiyomi Morita; P. Andrew Futreal; Koichi Takahashi; Christian Beisel; Holger Moch; Niko Beerenwinkel (PLoS Comput. Biol., 2021)

Comparing mutational pathways to lopinavir resistance in HIV-1 subtypes B versus C. - Susana Posada-Céspedes; Gert van Zyl; Hesam Montazeri; Jack Kuipers; Soo-Yon Rhee; Roger D. Kouyos; Huldrych F. Günthard; Niko Beerenwinkel (PLoS Comput. Biol., 2021)

The Dual PC Algorithm for Structure Learning. - Enrico Giudice; Jack Kuipers; Giusi Moffa (PGM, 2022)

Mapping Single-Cell Transcriptomes to Copy Number Evolutionary Trees. - Pedro F. Ferreira; Jack Kuipers; Niko Beerenwinkel (RECOMB, 2022)

Joint Inference of Repeated Evolutionary Trajectories and Patterns of Clonal Exclusivity or Co-occurrence from Tumor Mutation Trees. - Xiang Ge Luo; Jack Kuipers; Niko Beerenwinkel (RECOMB, 2022)

Discovering gene regulatory networks of multiple phenotypic groups using dynamic Bayesian networks. - Polina Suter; Jack Kuipers; Niko Beerenwinkel (Briefings Bioinform., 2022)

scAmpi - A versatile pipeline for single-cell RNA-seq analysis from basics to clinics. - Anne Bertolini; Michael Prummer; Mustafa Anil Tuncel; Ulrike Menzel; María Lourdes Rosano-González; Jack Kuipers; Daniel J. Stekhoven; Tumor Profiler Consortium; Niko Beerenwinkel; Franziska Singer (PLoS Comput. Biol., 2022)

Efficient Sampling and Structure Learning of Bayesian Networks. - Jack Kuipers; Polina Suter; Giusi Moffa (J. Comput. Graph. Stat., 2022)

Multi-omics subtyping of hepatocellular carcinoma patients using a Bayesian network mixture model. - Polina Suter; Eva Dazert; Jack Kuipers; Charlotte K. Y. Ng; Tuyana Boldanova; Michael N. Hall; Markus H. Heim; Niko Beerenwinkel (PLoS Comput. Biol., 2022)

Single-cell mutation calling and phylogenetic tree reconstruction with loss and recurrence. - Jack Kuipers; Jochen Singer; Niko Beerenwinkel (Bioinform., 2022)

A Bayesian Take on Gaussian Process Networks. - Enrico Giudice; Jack Kuipers; Giusi Moffa (NeurIPS, 2023)

Bayesian Structure Learning and Sampling of Bayesian Networks with the R Package BiDAG. - Polina Suter; Jack Kuipers; Giusi Moffa; Niko Beerenwinkel (J. Stat. Softw., 2023)

The dual PC algorithm and the role of Gaussianity for structure learning of Bayesian networks. - Enrico Giudice; Jack Kuipers; Giusi Moffa (Int. J. Approx. Reason., 2023)

Bayesian Causal Inference with Gaussian Process Networks. - Enrico Giudice; Jack Kuipers; Giusi Moffa (CoRR, 2024)

Fair Clustering: A Causal Perspective. - Fritz M. Bayer; Drago Plecko; Niko Beerenwinkel; Jack Kuipers (CLeaR, 2025)

The interventional Bayesian Gaussian equivalent score for Bayesian causal inference with unknown soft interventions. - Jack Kuipers; Giusi Moffa (CLeaR, 2025)

Exact discovery is polynomial for certain sparse causal Bayesian networks. - Felix Leopoldo Rios; Giusi Moffa; Jack Kuipers (CLeaR, 2025)

Determining distances and consensus between mutation trees. - Luís Cunha 001; Jack Kuipers; Thiago Lopes (CoRR, 2025)