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Maren Hackenberg

Showing results (1-10 of 15) with videos related to

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Bioinformatics (Oxford, England)|July 11, 2020
Exploring generative deep learning for omics data using log-linear modelsMoritz Hess, Maren Hackenberg, Harald Binder
Communications Biology|March 12, 2025
Infusing structural assumptions into dimensionality reduction for single-cell RNA sequencing data to identify small gene setsMaren Hackenberg, Niklas Brunn, Tanja Vogel, et al.
Briefings in Bioinformatics|June 27, 2025
Evaluating discrepancies in dimensionality reduction for time-series single-cell RNA-sequencing dataMaren Hackenberg, Laia Canal Guitart, Rolf Backofen, et al.
Frontiers in Molecular Biosciences|November 17, 2022
The performance of deep generative models for learning joint embeddings of single-cell multi-omics dataEva Brombacher, Maren Hackenberg, Clemens Kreutz, et al.
Bioinformatics (Oxford, England)|May 26, 2026
mmContext: an open framework for multimodal contrastive learning of omics and text dataJonatan Menger, Sonia Maria Krissmer, Clemens Kreutz, et al.
Bioinformatics (Oxford, England)|October 15, 2025
Sparse dimensionality reduction for analyzing single-cell-resolved interactionsNiklas Brunn, Maren Hackenberg, Camila L Fullio, et al.
Bioinformatics Advances|March 27, 2026
Sparse dimensionality reduction for analyzing single-cell-resolved interactionsNiklas Brunn, Maren Hackenberg, Camila L Fullio, et al.
Genome Biology|November 21, 2025
scSpecies: enhancement of network architecture alignment in comparative single-cell studiesClemens Schächter, Maren Hackenberg, Martin Treppner, et al.
Biometrical Journal. Biometrische Zeitschrift|December 19, 2024
Investigating a Domain Adaptation Approach for Integrating Different Measurement Instruments in a Longitudinal Clinical RegistryMaren Hackenberg, Michelle Pfaffenlehner, Max Behrens, et al.
BMC Medical Research Methodology|September 9, 2024
Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groupsKiana Farhadyar, Federico Bonofiglio, Maren Hackenberg, et al.
Pageof 2

Showing results (1-10 of 15) with videos related to

Sort By:
Pageof 2
Bioinformatics (Oxford, England)|July 11, 2020
Exploring generative deep learning for omics data using log-linear modelsMoritz Hess, Maren Hackenberg, Harald Binder
Communications Biology|March 12, 2025
Infusing structural assumptions into dimensionality reduction for single-cell RNA sequencing data to identify small gene setsMaren Hackenberg, Niklas Brunn, Tanja Vogel, et al.
Briefings in Bioinformatics|June 27, 2025
Evaluating discrepancies in dimensionality reduction for time-series single-cell RNA-sequencing dataMaren Hackenberg, Laia Canal Guitart, Rolf Backofen, et al.
Frontiers in Molecular Biosciences|November 17, 2022
The performance of deep generative models for learning joint embeddings of single-cell multi-omics dataEva Brombacher, Maren Hackenberg, Clemens Kreutz, et al.
Bioinformatics (Oxford, England)|May 26, 2026
mmContext: an open framework for multimodal contrastive learning of omics and text dataJonatan Menger, Sonia Maria Krissmer, Clemens Kreutz, et al.
Bioinformatics (Oxford, England)|October 15, 2025
Sparse dimensionality reduction for analyzing single-cell-resolved interactionsNiklas Brunn, Maren Hackenberg, Camila L Fullio, et al.
Bioinformatics Advances|March 27, 2026
Sparse dimensionality reduction for analyzing single-cell-resolved interactionsNiklas Brunn, Maren Hackenberg, Camila L Fullio, et al.
Genome Biology|November 21, 2025
scSpecies: enhancement of network architecture alignment in comparative single-cell studiesClemens Schächter, Maren Hackenberg, Martin Treppner, et al.
Biometrical Journal. Biometrische Zeitschrift|December 19, 2024
Investigating a Domain Adaptation Approach for Integrating Different Measurement Instruments in a Longitudinal Clinical RegistryMaren Hackenberg, Michelle Pfaffenlehner, Max Behrens, et al.
BMC Medical Research Methodology|September 9, 2024
Combining propensity score methods with variational autoencoders for generating synthetic data in presence of latent sub-groupsKiana Farhadyar, Federico Bonofiglio, Maren Hackenberg, et al.
Pageof 2