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ORCIDNico Pfeifer
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- affiliation: University of Tübingen, Wilhelm-Schickard-Institute for Computer Science, Germany
- affiliation: Max Planck Institute for Informatics, Saarbrücken, Computer
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2020 – today
- 2023
[j22]Filippo Grazioli
, Pierre Machart, Anja Mösch, Kai Li, Leonardo V. Castorina, Nico Pfeifer, Martin Renqiang Min:
Attentive Variational Information Bottleneck for TCR-peptide interaction prediction. Bioinform. 39(1) (2023)- [j21]Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer:
COmic: convolutional kernel networks for interpretable end-to-end learning on (multi-)omics data. Bioinform. 39(Supplement-1): 76-85 (2023) - [j20]Jonas C. Ditz, Jacqueline Wistuba-Hamprecht, Timo Maier, Rolf Fendel, Nico Pfeifer, Bernhard Reuter:
PlasmoFAB: a benchmark to foster machine learning for Plasmodium falciparum protein antigen candidate prediction. Bioinform. 39(Supplement-1): 86-93 (2023) - [j19]Christian Malte Boßelmann, Ulrike B. S. Hedrich, Holger Lerche, Nico Pfeifer:
Predicting functional effects of ion channel variants using new phenotypic machine learning methods. PLoS Comput. Biol. 19(3) (2023) - [j18]Anna Hake, Anja Germann, Corena de Beer, Alexander Thielen, Martin Däumer, Wolfgang Preiser, Hagen von Briesen, Nico Pfeifer:
Insights to HIV-1 coreceptor usage by estimating HLA adaptation with Bayesian generalized linear mixed models. PLoS Comput. Biol. 19(12) (2023) - [c9]Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
ppAURORA: Privacy Preserving Area Under Receiver Operating Characteristic and Precision-Recall Curves. NSS 2023: 265-280 - [i10]Jonas Christian Ditz, Jacqueline Wistuba-Hamprecht, Timo Maier, Rolf Fendel, Nico Pfeifer, Bernhard Reuter:
PlasmoFAB: A Benchmark to Foster Machine Learning for Plasmodium falciparum Protein Antigen Candidate Prediction. CoRR abs/2301.06454 (2023) - [i9]Sofiane Ouaari, Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach. CoRR abs/2309.04427 (2023) - 2022
- [j17]Mete Akgün, Nico Pfeifer, Oliver Kohlbacher:
Efficient privacy-preserving whole-genome variant queries. Bioinform. 38(8): 2202-2210 (2022) - [i8]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
CECILIA: Comprehensive Secure Machine Learning Framework. CoRR abs/2202.03023 (2022) - [i7]Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer:
COmic: Convolutional Kernel Networks for Interpretable End-to-End Learning on (Multi-)Omics Data. CoRR abs/2212.02504 (2022) - [i6]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, Nico Pfeifer, Oliver Kohlbacher:
Bringing the Algorithms to the Data - Secure Distributed Medical Analytics using the Personal Health Train (PHT-meDIC). CoRR abs/2212.03481 (2022) - 2021
- [j16]Mete Akgün, Ali Burak Ünal, Bekir Ergüner, Nico Pfeifer, Oliver Kohlbacher:
Identifying disease-causing mutations with privacy protection. Bioinform. 36(21): 5205-5213 (2021) - [c8]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. AAAI 2021: 9988-9996 - [i5]Ali Burak Ünal, Nico Pfeifer, Mete Akgün:
ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation. CoRR abs/2102.08788 (2021) - [i4]Jonas C. Ditz, Bernhard Reuter, Nico Pfeifer:
Convolutional Motif Kernel Networks. CoRR abs/2111.02272 (2021) - 2020
- [c7]Huajie Chen, Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
Privacy-preserving SVM on Outsourced Genomic Data via Secure Multi-party Computation. IWSPA@CODASPY 2020: 61-69 - [c6]Efe Bozkir, Ali Burak Ünal, Mete Akgün, Enkelejda Kasneci, Nico Pfeifer:
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework. ETRA Short Papers 2020: 21:1-21:5 - [i3]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare. CoRR abs/2012.02688 (2020)
2010 – 2019
- 2019
- [j15]Lisa Handl, Adrin Jalali, Michael Scherer, Ralf Eggeling, Nico Pfeifer:
Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data. Bioinform. 35(14): i154-i163 (2019) - [j14]Benedict Röder, Nicolas Kersten, Marius Herr, Nora K. Speicher, Nico Pfeifer:
web-rMKL: a web server for dimensionality reduction and sample clustering of multi-view data based on unsupervised multiple kernel learning. Nucleic Acids Res. 47(Webserver-Issue): W605-W609 (2019) - [c5]Ali Burak Ünal, Mete Akgün, Nico Pfeifer:
A Framework with Randomized Encoding for a Fast Privacy Preserving Calculation of Non-linear Kernels for Machine Learning Applications in Precision Medicine. CANS 2019: 493-511 - [i2]Efe Bozkir, Ali Burak Ünal, Mete Akgün, Enkelejda Kasneci, Nico Pfeifer:
Privacy Preserving Gaze Estimation using Synthetic Images via a Randomized Encoding Based Framework. CoRR abs/1911.07936 (2019) - 2018
- [j13]Matthias Döring, Joachim Büch, Georg Friedrich, Alejandro Pironti, Prabhav Kalaghatgi, Elena Knops, Eva Heger, Martin Obermeier, Martin Däumer, Alexander Thielen, Rolf Kaiser, Thomas Lengauer, Nico Pfeifer:
geno2pheno[ngs-freq]: a genotypic interpretation system for identifying viral drug resistance using next-generation sequencing data. Nucleic Acids Res. 46(Webserver-Issue): W271-W277 (2018) - [c4]Gabriele Weiler, Ulf Schwarz, Jochen Rauch, Kerstin Rohm, Thorsten Lehr, Stefan Theobald, Stephan Kiefer, Katharina Götz, Katharina Och, Nico Pfeifer, Lisa Handl, Sigrun Smola, Matthias Ihle, Amin T. Turki, Dietrich W. Beelen, Jürgen Rissland, Jörg Bittenbring, Norbert M. Graf:
XplOit: An Ontology-Based Data Integration Platform Supporting the Development of Predictive Models for Personalized Medicine. MIE 2018: 21-25 - [i1]Nora K. Speicher, Nico Pfeifer:
An interpretable multiple kernel learning approach for the discovery of integrative cancer subtypes. CoRR abs/1811.08102 (2018) - 2017
- [j12]Sarvesh Nikumbh, Nico Pfeifer:
Genetic sequence-based prediction of long-range chromatin interactions suggests a potential role of short tandem repeat sequences in genome organization. BMC Bioinform. 18(1): 218:1-218:16 (2017) - [j11]Nora K. Speicher, Nico Pfeifer:
Towards Multiple Kernel Principal Component Analysis for Integrative Analysis of Tumor Samples. J. Integr. Bioinform. 14(2) (2017) - [j10]Anna Hake, Nico Pfeifer:
Prediction of HIV-1 sensitivity to broadly neutralizing antibodies shows a trend towards resistance over time. PLoS Comput. Biol. 13(10) (2017) - [c3]Sarvesh Nikumbh, Peter Ebert, Nico Pfeifer:
All Fingers Are Not the Same: Handling Variable-Length Sequences in a Discriminative Setting Using Conformal Multi-Instance Kernels. WABI 2017: 16:1-16:14 - 2015
- [j9]Nora K. Speicher, Nico Pfeifer:
Integrating different data types by regularized unsupervised multiple kernel learning with application to cancer subtype discovery. Bioinform. 31(12): 268-275 (2015) - [j8]Matthias Döring, Gilles Gasparoni, Jasmin Gries, Karl Nordström, Pavlo Lutsik, Jörn Walter, Nico Pfeifer:
Identification and analysis of methylation call differences between bisulfite microarray and bisulfite sequencing data with statistical learning techniques. BMC Bioinform. 16(S-3): A7 (2015) - 2014
- [c2]Adrin Jalali, Nico Pfeifer:
Interpretable Per Case Weighted Ensemble Method for Cancer Associations. WABI 2014: 352-353 - 2012
- [j7]Nico Pfeifer, Thomas Lengauer:
Improving HIV coreceptor usage prediction in the clinic using hints from next-generation sequencing data. Bioinform. 28(18): 589-595 (2012)
2000 – 2009
- 2009
- [b1]Nico Pfeifer:
Kernel-based machine learning on sequence data from proteomics and immunomics. Eberhard Karls University of Tübingen, 2009, pp. 1-130 - 2008
- [j6]Ole Schulz-Trieglaff, Nico Pfeifer, Clemens Gröpl, Oliver Kohlbacher, Knut Reinert:
LC-MSsim - a simulation software for liquid chromatography mass spectrometry data. BMC Bioinform. 9 (2008) - [j5]Marc Sturm, Andreas Bertsch, Clemens Gröpl, Andreas Hildebrandt, Rene Hussong, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Alexandra Zerck, Knut Reinert, Oliver Kohlbacher:
OpenMS - An open-source software framework for mass spectrometry. BMC Bioinform. 9 (2008) - [c1]Nico Pfeifer, Oliver Kohlbacher:
Multiple Instance Learning Allows MHC Class II Epitope Predictions Across Alleles. WABI 2008: 210-221 - 2007
- [j4]Oliver Kohlbacher, Knut Reinert, Clemens Gröpl, Eva Lange, Nico Pfeifer, Ole Schulz-Trieglaff, Marc Sturm:
TOPP - the OpenMS proteomics pipeline. Bioinform. 23(2): 191-197 (2007) - [j3]Nico Pfeifer, Andreas Leinenbach, Christian G. Huber, Oliver Kohlbacher:
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics. BMC Bioinform. 8 (2007) - [j2]Christian Igel, Tobias Glasmachers, Britta Mersch, Nico Pfeifer, Peter Meinicke:
Gradient-Based Optimization of Kernel-Target Alignment for Sequence Kernels Applied to Bacterial Gene Start Detection. IEEE ACM Trans. Comput. Biol. Bioinform. 4(2): 216-226 (2007) - 2005
- [j1]Maike Tech, Nico Pfeifer, Burkhard Morgenstern, Peter Meinicke:
TICO: a tool for improving predictions of prokaryotic translation initiation sites. Bioinform. 21(17): 3568-3569 (2005)
Coauthor Index
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