TICO: a tool for improving predictions of prokaryotic translation initiation sites. - Maike Tech; Nico Pfeifer; Burkhard Morgenstern; Peter Meinicke (Bioinform., 2005)

TOPP - the OpenMS proteomics pipeline. - Oliver Kohlbacher; Knut Reinert; Clemens Gröpl; Eva Lange; Nico Pfeifer; Ole Schulz-Trieglaff; Marc Sturm (Bioinform., 2007)

Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics. - Nico Pfeifer; Andreas Leinenbach; Christian G. Huber; Oliver Kohlbacher (BMC Bioinform., 2007)

Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. - Christian Igel; Tobias Glasmachers; Britta Mersch; Nico Pfeifer; Peter Meinicke (IEEE ACM Trans. Comput. Biol. Bioinform., 2007)

Multiple Instance Learning Allows MHC Class II Epitope Predictions Across Alleles. - Nico Pfeifer; Oliver Kohlbacher (WABI, 2008)

LC-MSsim - a simulation software for liquid chromatography mass spectrometry data. - Ole Schulz-Trieglaff; Nico Pfeifer; Clemens Gröpl; Oliver Kohlbacher; Knut Reinert (BMC Bioinform., 2008)

OpenMS - An open-source software framework for mass spectrometry. - Marc Sturm; Andreas Bertsch; Clemens Gröpl; Andreas Hildebrandt 001; Rene Hussong; Eva Lange; Nico Pfeifer; Ole Schulz-Trieglaff; Alexandra Zerck; Knut Reinert; Oliver Kohlbacher (BMC Bioinform., 2008)

Kernel-based machine learning on sequence data from proteomics and immunomics. - Nico Pfeifer (2009)

Improving HIV coreceptor usage prediction in the clinic using hints from next-generation sequencing data. - Nico Pfeifer; Thomas Lengauer (Bioinform., 2012)

Interpretable Per Case Weighted Ensemble Method for Cancer Associations. - Adrin Jalali; Nico Pfeifer (WABI, 2014)

Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery. - Nora K. Speicher; Nico Pfeifer (Bioinform., 2015)

Identification and analysis of methylation call differences between bisulfite microarray and bisulfite sequencing data with statistical learning techniques. - Matthias Döring; Gilles Gasparoni; Jasmin Gries; Karl Nordström; Pavlo Lutsik; Jörn Walter; Nico Pfeifer (BMC Bioinform., 2015)

All Fingers Are Not the Same: Handling Variable-Length Sequences in a Discriminative Setting Using Conformal Multi-Instance Kernels. - Sarvesh Nikumbh; Peter Ebert; Nico Pfeifer (WABI, 2017)

Genetic sequence-based prediction of long-range chromatin interactions suggests a potential role of short tandem repeat sequences in genome organization. - Sarvesh Nikumbh; Nico Pfeifer (BMC Bioinform., 2017)

Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples. - Nora K. Speicher; Nico Pfeifer (J. Integr. Bioinform., 2017)

Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time. - Anna Hake; Nico Pfeifer (PLoS Comput. Biol., 2017)

XplOit: An Ontology-Based Data Integration Platform Supporting the Development of Predictive Models for Personalized Medicine. - Gabriele Weiler; Ulf Schwarz; Jochen Rauch; Kerstin Rohm; Thorsten Lehr; Stefan Theobald; Stephan Kiefer; Katharina Götz; Katharina Och; Nico Pfeifer; Lisa Handl; Sigrun Smola; et al. (MIE, 2018)

An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes. - Nora K. Speicher; Nico Pfeifer (CoRR, 2018)

geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data. - Matthias Döring; Joachim Büch; Georg Friedrich; Alejandro Pironti; Prabhav Kalaghatgi; Elena Knops; Eva Heger; Martin Obermeier; Martin Däumer; Alexander Thielen; Rolf Kaiser; Thomas Lengauer; et al. (Nucleic Acids Res., 2018)

A Framework with Randomized Encoding for a Fast Privacy Preserving Calculation of Non-linear Kernels for Machine Learning Applications in Precision Medicine. - Ali Burak Ünal; Mete Akgün; Nico Pfeifer (CANS, 2019)

Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data. - Lisa Handl; Adrin Jalali; Michael Scherer; Ralf Eggeling; Nico Pfeifer (Bioinform., 2019)

web-rMKL: a web server for dimensionality reduction and sample clustering of multi-view data based on unsupervised multiple kernel learning. - Benedict Röder; Nicolas Kersten; Marius Herr; Nora K. Speicher; Nico Pfeifer (Nucleic Acids Res., 2019)

Privacy-preserving SVM on Outsourced Genomic Data via Secure Multi-party Computation. - Huajie Chen; Ali Burak Ünal; Mete Akgün; Nico Pfeifer (IWSPA@CODASPY, 2020)

Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework. - Efe Bozkir; Ali Burak Ünal; Mete Akgün; Enkelejda Kasneci; Nico Pfeifer (ETRA Short Papers, 2020)

ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. - Ali Burak Ünal; Mete Akgün; Nico Pfeifer (AAAI, 2021)

Identifying disease-causing mutations with privacy protection. - Mete Akgün; Ali Burak Ünal; Bekir Ergüner; Nico Pfeifer; Oliver Kohlbacher (Bioinform., 2021)

ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation. - Ali Burak Ünal; Nico Pfeifer; Mete Akgün (CoRR, 2021)

Convolutional Motif Kernel Networks. - Jonas C. Ditz; Bernhard Reuter; Nico Pfeifer (CoRR, 2021)

Efficient privacy-preserving whole-genome variant queries. - Mete Akgün; Nico Pfeifer; Oliver Kohlbacher (Bioinform., 2022)

CECILIA: Comprehensive Secure Machine Learning Framework. - Ali Burak Ünal; Mete Akgün; Nico Pfeifer (CoRR, 2022)

Bringing the Algorithms to the Data - Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC). - Marius de Arruda Botelho Herr; Michael Graf; Peter Placzek; Florian König; Felix Bötte; Tyra Stickel; David Hieber; Lukas Zimmermann; Michael Slupina; Christopher Mohr; Stephanie Biergans; Mete Akgün; et al. (CoRR, 2022)

ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves. - Ali Burak Ünal; Nico Pfeifer; Mete Akgün (NSS, 2023)

COmic: convolutional kernel networks for interpretable end-to-end learning on (multi-)omics data. - Jonas C. Ditz; Bernhard Reuter; Nico Pfeifer (Bioinform., 2023)

PlasmoFAB: a benchmark to foster machine learning for Plasmodium falciparum protein antigen candidate prediction. - Jonas C. Ditz; Jacqueline Wistuba-Hamprecht; Timo Maier; Rolf Fendel; Nico Pfeifer; Bernhard Reuter (Bioinform., 2023)

PlasmoFAB: A Benchmark to Foster Machine Learning for Plasmodium falciparum Protein Antigen Candidate Prediction. - Jonas Christian Ditz; Jacqueline Wistuba-Hamprecht; Timo Maier; Rolf Fendel; Nico Pfeifer; Bernhard Reuter (CoRR, 2023)

Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach. - Sofiane Ouaari; Ali Burak Ünal; Mete Akgün; Nico Pfeifer (CoRR, 2023)

Attentive Variational Information Bottleneck for TCR-peptide interaction prediction. - Filippo Grazioli; Pierre Machart; Anja Mösch; Kai Li 012; Leonardo V. Castorina; Nico Pfeifer; Martin Renqiang Min (Bioinform., 2023)

Predicting functional effects of ion channel variants using new phenotypic machine learning methods. - Christian Malte Boßelmann; Ulrike B. S. Hedrich; Holger Lerche; Nico Pfeifer (PLoS Comput. Biol., 2023)

Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models. - Anna Hake; Anja Germann; Corena de Beer; Alexander Thielen; Martin Däumer; Wolfgang Preiser; Hagen von Briesen; Nico Pfeifer (PLoS Comput. Biol., 2023)

PP-GWAS: Privacy Preserving Multi-Site Genome-wide Association Studies. - Arjhun Swaminathan; Anika Hannemann; Ali Burak Ünal; Nico Pfeifer; Mete Akgün (CoRR, 2024)

Privacy Preserving Federated Unsupervised Domain Adaptation with Application to Age Prediction from DNA Methylation Data. - Cem Ata Baykara; Ali Burak Ünal; Nico Pfeifer; Mete Akgün (CoRR, 2024)

A privacy-preserving approach for cloud-based protein fold recognition. - Ali Burak Ünal; Nico Pfeifer; Mete Akgün (Patterns, 2024)

Machine learning prediction of malaria vaccine efficacy based on antibody profiles. - Jacqueline Wistuba-Hamprecht; Bernhard Reuter; Rolf Fendel; Stephen L. Hoffman; Joseph J. Campo; Philip L. Felgner; Peter G. Kremsner; Benjamin Mordmüller; Nico Pfeifer (PLoS Comput. Biol., 2024)

An informed deep learning model of the Omicron wave and the impact of vaccination. - Elham Shamsara; Florian König; Nico Pfeifer (Comput. Biol. Medicine, 2025)