WhopGenome: high-speed access to whole-genome variation and sequence data in R. - Ulrich Wittelsbürger; Bastian Pfeifer; Martin J. Lercher (Bioinform., 2015)

Whole-genome population genomic analyses. - Bastian Pfeifer (2015)

EHR Text Categorization for Enhanced Patient-Based Document Navigation. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (eHealth, 2018)

Problem List Clustering for Improved Patient-Based Disease Perception. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (ICHI Workshops, 2018)

BlockFeST: Bayesian calculation of region-specific FST to detect local adaptation. - Bastian Pfeifer; Martin J. Lercher (Bioinform., 2018)

Estimates of introgression as a function of pairwise distances. - Bastian Pfeifer; Durrell D. Kapan (BMC Bioinform., 2019)

EHR problem list clustering for improved topic-space navigation. - Markus Kreuzthaler; Bastian Pfeifer; José Antonio Vera Ramos; Diether Kramer; Victor Grogger; Sylvia Bredenfeldt; Markus Pedevilla; Peter Krisper; Stefan Schulz 001 (BMC Medical Informatics Decis. Mak., 2019)

Integrative hierarchical ensemble clustering for improved disease subtype discovery. - Bastian Pfeifer; Andrei Voicu-Spineanu; Michael G. Schimek; Nikolaos Alachiotis 001 (BIBM, 2021)

Network Module Detection from Multi-Modal Node Features with a Greedy Decision Forest for Actionable Explainable AI. - Bastian Pfeifer; Anna Saranti; Andreas Holzinger (CoRR, 2021)

Towards multi-modal causability with Graph Neural Networks enabling information fusion for explainable AI. - Andreas Holzinger; Bernd Malle; Anna Saranti; Bastian Pfeifer (Inf. Fusion, 2021)

A hierarchical clustering and data fusion approach for disease subtype discovery. - Bastian Pfeifer; Michael G. Schimek (J. Biomed. Informatics, 2021)

Terminology Expansion via Co-occurrence Analysis of Large Clinical Real-World Datasets. - Markus Kreuzthaler; Bastian Pfeifer; Stefan Schulz 001 (ICHI, 2022)

Robust Random Forest-Based All-Relevant Feature Ranks for Trustworthy AI. - Bastian Pfeifer; Andreas Holzinger; Michael G. Schimek (MIE, 2022)

GNN-SubNet: disease subnetwork detection with explainable graph neural networks. - Bastian Pfeifer; Anna Saranti; Andreas Holzinger (Bioinform., 2022)

Parea: multi-view ensemble clustering for cancer subtype discovery. - Bastian Pfeifer; Marcus D. Bloice; Michael G. Schimek (CoRR, 2022)

Generating Explanations for Conceptual Validation of Graph Neural Networks: An Investigation of Symbolic Predicates Learned on Relevance-Ranked Sub-Graphs. - Bettina Finzel; Anna Saranti; Alessa Angerschmid; David E. Tafler; Bastian Pfeifer; Andreas Holzinger (Künstliche Intell., 2022)

Actionable Explainable AI (AxAI): A Practical Example with Aggregation Functions for Adaptive Classification and Textual Explanations for Interpretable Machine Learning. - Anna Saranti; Miroslav Hudec; Erika Mináriková; Zdenko Takác; Udo Großschedl; Christoph Koch 006; Bastian Pfeifer; Alessa Angerschmid; Andreas Holzinger (Mach. Learn. Knowl. Extr., 2022)

Human-in-the-Loop Integration with Domain-Knowledge Graphs for Explainable Federated Deep Learning. - Andreas Holzinger; Anna Saranti; Anne-Christin Hauschild; Jacqueline Michelle Beinecke; Dominik Heider; Richard Röttger; Heimo Müller; Jan Baumbach; Bastian Pfeifer (CD-MAKE, 2023)

Improving the Reliability of Tree-Based Feature Importance via Consensus Signals. - Bastian Pfeifer; Michael G. Schimek (CIBB, 2023)

Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment. - Markus Kreuzthaler; Bastian Pfeifer; Diether Kramer; Stefan Schulz 001 (MIE, 2023)

Data-Driven Identification of Clinical Real-World Expressions Linked to ICD. - Amila Kugic; Bastian Pfeifer; Stefan Schulz 001; Markus Kreuzthaler (MIE, 2023)

Bayesian post-hoc regularization of random forests. - Bastian Pfeifer (CoRR, 2023)

Explainable AI with counterfactual paths. - Bastian Pfeifer; Mateusz Krzyzinski; Hubert Baniecki; Anna Saranti; Andreas Holzinger; Przemyslaw Biecek (CoRR, 2023)

Be Careful When Evaluating Explanations Regarding Ground Truth. - Hubert Baniecki; Maciej Chrabaszcz; Andreas Holzinger; Bastian Pfeifer; Anna Saranti; Przemyslaw Biecek (CoRR, 2023)

Parea: Multi-view ensemble clustering for cancer subtype discovery. - Bastian Pfeifer; Marcus D. Bloice; Michael G. Schimek (J. Biomed. Informatics, 2023)

Ensemble-GNN: Source Code and Data. - Bastian Pfeifer; Hryhorii Chereda; Roman Martin; Anna Saranti; Sandra Clemens; Anne-Christin Hauschild; Tim Beißbarth; Andreas Holzinger; Dominik Heider (Zenodo, 2023)

Ensemble-GNN: federated ensemble learning with graph neural networks for disease module discovery and classification. - Bastian Pfeifer; Hryhorii Chereda; Roman Martin; Anna Saranti; Sandra Clemens; Anne-Christin Hauschild; Tim Beißbarth; Andreas Holzinger; Dominik Heider (Bioinform., 2023)

Embedding-based terminology expansion via secondary use of large clinical real-world datasets. - Amila Kugic; Bastian Pfeifer; Stefan Schulz 001; Markus Kreuzthaler (J. Biomed. Informatics, 2023)

Hierarchical Clustering with an Ensemble of Principle Component Trees for Interpretable Patient Stratification. - Bastian Pfeifer; Marcus D. Bloice; Christel Sirocchi; Markus Loecher (CIBB, 2024)

Federated unsupervised random forest for privacy-preserving patient stratification. - Bastian Pfeifer; Christel Sirocchi; Marcus D. Bloice; Markus Kreuzthaler; Martin Urschler (Bioinform., 2024)

CLARUS: An interactive explainable AI platform for manual counterfactuals in graph neural networks. - Jacqueline Michelle Metsch; Anna Saranti; Alessa Angerschmid; Bastian Pfeifer; Vanessa Klemt; Andreas Holzinger; Anne-Christin Hauschild (J. Biomed. Informatics, 2024)

From 3D point-cloud data to explainable geometric deep learning: State-of-the-art and future challenges. - Anna Saranti; Bastian Pfeifer; Christoph Gollob; Karl Stampfer; Andreas Holzinger (WIREs Data. Mining. Knowl. Discov., 2024)

Effective signal reconstruction from multiple ranked lists via convex optimization. - Michael G. Schimek; Luca Vitale; Bastian Pfeifer; Michele La Rocca 001 (Data Min. Knowl. Discov., 2024)

Correction to: Effective signal reconstruction from multiple ranked lists via convex optimization. - Michael G. Schimek; Luca Vitale; Bastian Pfeifer; Michele La Rocca 001 (Data Min. Knowl. Discov., 2024)

Feature graphs for interpretable unsupervised tree ensembles: centrality, interaction, and application in disease subtyping. - Christel Sirocchi; Martin Urschler; Bastian Pfeifer (BioData Min., 2025)

Tree smoothing: Post-hoc regularization of tree ensembles for interpretable machine learning. - Bastian Pfeifer; Arne Gevaert; Markus Loecher; Andreas Holzinger (Inf. Sci., 2025)