Huber, Wolfgang

Deep learning-based predictions of gene perturbation effects do not yet outperform simple linear baselines

Ahlmann-Eltze, C., Huber, W., & Anders, S. (2024) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 268

Deep-learning-based gene perturbation effect prediction does not yet outperform simple linear baselines

Ahlmann-Eltze, C., Huber, W., & Anders, S. (2025) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 238

Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation

Kelmer Sacramento, E., Kirkpatrick, J. M., Mazzetto, M., Baumgart, M., Bartolome, A., Di Sanzo, S., Caterino, C., Sanguanini, M., Papaevgeniou, N., Lefaki, M., et al. (2020) · Molecular Systems Biology

Genetics, Aging, and Longevity in Model OrganismsUbiquitin and proteasome pathways

Cited by 236

Reduced proteasome activity in the aging brain results in ribosome stoichiometry loss and aggregation

Sacramento, E. K., Kirkpatrick, J. M., Mazzetto, M., Baumgart, M., Bartolome, A., Di Sanzo, S., Caterino, C., Sanguanini, M., Papaevgeniou, N., Lefaki, M., et al. (2019) · Molecular Systems Biology

Genetics, Aging, and Longevity in Model OrganismsUbiquitin and proteasome pathways

Cited by 236

The Shh Topological Domain Facilitates the Action of Remote Enhancers by Reducing the Effects of Genomic Distances

Symmons, O., Pan, L., Remeseiro, S., Aktas, T., Klein, F., Huber, W., & Spitz, F. (2016) · Developmental Cell

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 222

Biological plasticity rescues target activity in CRISPR knock outs

Smits, A. H., Ziebell, F., Joberty, G., Zinn, N., Mueller, W. F., Clauder-Münster, S., Eberhard, D., Fälth Savitski, M., Grandi, P., Jakob, P., et al. (2019) · Nature Methods

CRISPR and Genetic EngineeringRNA regulation and disease

Cited by 219

Mapping of signaling networks through synthetic genetic interaction analysis by RNAi

Horn, T., Sandmann, T., Fischer, B., Axelsson, E., Huber, W., & Boutros, M. (2011) · Nature Methods

Bioinformatics and Genomic NetworksGene Regulatory Network Analysis

Cited by 193

Identifying drug targets in tissues and whole blood with thermal-shift profiling

Perrin, J., Werner, T., Kurzawa, N., Rutkowska, A., Childs, D. D., Kalxdorf, M., Poeckel, D., Stonehouse, E., Strohmer, K., Heller, B., et al. (2020) · Nature Biotechnology

Advanced Proteomics Techniques and ApplicationsProtein Degradation and Inhibitors

Cited by 178

Comparison of Transformations for Single-Cell RNA-Seq Data

Ahlmann-Eltze, C., & Huber, W. (2021) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 148

Quantification of Differential Transcription Factor Activity and Multiomics-Based Classification into Activators and Repressors: diffTF

Berest, I., Arnold, C., Reyes-Palomares, A., Palla, G., Rasmussen, K. D., Giles, H., Bruch, P.-M., Huber, W., Dietrich, S., Helin, K., et al. (2019) · Cell Reports

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 119

Alternative polyadenylation diversifies post‐transcriptional regulation by selective RNA–protein interactions

Gupta, I., Clauder‐Münster, S., Klaus, B., Järvelin, A. I., Aiyar, R. S., Benes, V., Wilkening, S., Huber, W., Pelechano, V., & Steinmetz, L. M. (2014) · Molecular Systems Biology

RNA Research and SplicingRNA and protein synthesis mechanisms

Cited by 95

Gain of CTCF-Anchored Chromatin Loops Marks the Exit from Naive Pluripotency

Pękowska, A., Klaus, B., Xiang, W., Severino, J., Daigle, N., Klein, F. A., Oleś, M., Casellas, R., Ellenberg, J., Steinmetz, L. M., et al. (2018) · Cell Systems

Genomics and Chromatin DynamicsPluripotent Stem Cells Research

Cited by 74

A computational method for detection of ligand-binding proteins from dose range thermal proteome profiles

Kurzawa, N., Becher, I., Sridharan, S., Franken, H., Mateus, A., Anders, S., Bantscheff, M., Huber, W., & Savitski, M. M. (2020) · Nature Communications

Advanced Proteomics Techniques and Applicationsthermodynamics and calorimetric analyses

Cited by 53

Analysis of multi-condition single-cell data with latent embedding multivariate regression

Ahlmann-Eltze, C., & Huber, W. (2025) · Nature Genetics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 15