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2020 – today
- 2023
[j11]Mohammed Zidane, Ahmad Makky
, Matthias Bruhns, Alexander Rochwarger, Sepideh Babaei, Manfred Claassen, Christian M. Schürch:
A review on deep learning applications in highly multiplexed tissue imaging data analysis. Frontiers Bioinform. 3 (2023)- [j10]Mohammed Zidane, Ahmad Makky, Matthias Bruhns, Alexander Rochwarger, Sepideh Babaei, Manfred Claassen, Christian M. Schürch:
Corrigendum: A review on deep learning applications in highly multiplexed tissue imaging data analysis. Frontiers Bioinform. 3 (2023) - [j9]Sepideh Babaei, Jonathan Christ, Vivek Sehra, Ahmad Makky, Mohammed Zidane, Kilian Wistuba-Hamprecht, Christian M. Schürch, Manfred Claassen:
S3-CIMA: Supervised spatial single-cell image analysis for identifying disease-associated cell-type compositions in tissue. Patterns 4(9): 100829 (2023) - 2022
- [j8]Sinem Sav, Jean-Philippe Bossuat, Juan Ramón Troncoso-Pastoriza, Manfred Claassen, Jean-Pierre Hubaux:
Privacy-preserving federated neural network learning for disease-associated cell classification. Patterns 3(5): 100487 (2022) - 2021
- [j7]Andreas Kopf, Manfred Claassen:
Latent representation learning in biology and translational medicine. Patterns 2(3): 100198 (2021) - [j6]Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen:
Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations on single cell data. PLoS Comput. Biol. 17(6) (2021) - [i3]Quentin Garrido, Sebastian Damrich, Alexander Jäger, Dario Cerletti, Manfred Claassen, Laurent Najman, Fred A. Hamprecht:
Visualizing hierarchies in scRNA-seq data using a density tree-biased autoencoder. CoRR abs/2102.05892 (2021) - 2020
- [j5]Jake P. Taylor-King, Asbjørn Nilsen Riseth, Will Macnair, Manfred Claassen:
Dynamic distribution decomposition for single-cell snapshot time series identifies subpopulations and trajectories during iPSC reprogramming. PLoS Comput. Biol. 16(1) (2020)
2010 – 2019
- 2019
- [i2]Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen:
Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations. CoRR abs/1910.07763 (2019) - 2018
- [i1]Eirini Arvaniti, Manfred Claassen:
Coupling weak and strong supervision for classification of prostate cancer histopathology images. CoRR abs/1811.07013 (2018) - 2017
- [j4]Andreas Kühne, Urs Mayr, Daniel C. Sévin, Manfred Claassen, Nicola Zamboni:
Metabolic network segmentation: A probabilistic graphical modeling approach to identify the sites and sequential order of metabolic regulation from non-targeted metabolomics data. PLoS Comput. Biol. 13(6) (2017) - 2016
- [j3]Anna Klimovskaia, Stefan Ganscha, Manfred Claassen:
Sparse Regression Based Structure Learning of Stochastic Reaction Networks from Single Cell Snapshot Time Series. PLoS Comput. Biol. 12(12) (2016) - 2014
- [c2]Eirini Arvaniti, Manfred Claassen:
Markov Network Structure Learning via Ensemble-of-Forests Models. UAI 2014: 42-51 - 2011
- [j2]Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann:
Proteome Coverage Prediction for Integrated Proteomics Datasets. J. Comput. Biol. 18(3): 283-293 (2011) - 2010
- [c1]Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann:
Proteome Coverage Prediction for Integrated Proteomics Datasets. RECOMB 2010: 96-109 - [p1]Manfred Claassen:
Design and Validation of Proteome Measurements. Ausgezeichnete Informatikdissertationen 2010: 71-80
2000 – 2009
- 2009
- [j1]Manfred Claassen, Ruedi Aebersold, Joachim M. Buhmann:
Proteome coverage prediction with infinite Markov models. Bioinform. 25(12) (2009)
Coauthor Index
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