Theis, Fabian J.

A test metric for assessing single-cell RNA-seq batch correction

Büttner, M., Miao, Z., Wolf, F. A., Teichmann, S. A., & Theis, F. J. (2019) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 511

Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics

Plass, M., Solana, J., Wolf, F. A., Ayoub, S., Misios, A., Glažar, P., Obermayer, B., Theis, F. J., Kocks, C., & Rajewsky, N. (2018) · Science

Single-cell and spatial transcriptomicsPlanarian Biology and Electrostimulation

Cited by 474

Combined Single-Cell Functional and Gene Expression Analysis Resolves Heterogeneity within Stem Cell Populations

Wilson, N. K., Kent, D. G., Buettner, F., Shehata, M., Macaulay, I. C., Calero-Nieto, F. J., Sánchez Castillo, M., Oedekoven, C. A., Diamanti, E., Schulte, R., et al. (2015) · Cell Stem Cell

Hematopoietic Stem Cell TransplantationSingle-cell and spatial transcriptomics

Cited by 466

scCODA is a Bayesian model for compositional single-cell data analysis

Büttner, M., Ostner, J., Müller, C. L., Theis, F. J., & Schubert, B. (2021) · Nature Communications

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 388

Decoding the regulatory network of early blood development from single-cell gene expression measurements

Moignard, V., Woodhouse, S., Haghverdi, L., Lilly, A. J., Tanaka, Y., Wilkinson, A. C., Buettner, F., Macaulay, I. C., Jawaid, W., Diamanti, E., et al. (2015) · Nature Biotechnology

Gene Regulatory Network AnalysisSingle-cell and spatial transcriptomics

Cited by 380

Epigenetic germline inheritance of diet-induced obesity and insulin resistance

Huypens, P., Sass, S., Wu, M., Dyckhoff, D., Tschöp, M., Theis, F., Marschall, S., de Angelis, M. H., & Beckers, J. (2016) · Nature Genetics

Birth, Development, and HealthEpigenetics and DNA Methylation

Cited by 366

The dynamic range of the human metabolome revealed by challenges

Krug, S., Kastenmüller, G., Stückler, F., Rist, M. J., Skurk, T., Sailer, M., Raffler, J., Römisch‐Margl, W., Adamski, J., Prehn, C., et al. (2012) · The FASEB Journal

Metabolomics and Mass Spectrometry StudiesHealth, Environment, Cognitive Aging

Cited by 327

Predicting cellular responses to complex perturbations in high‐throughput screens

Lotfollahi, M., Klimovskaia Susmelj, A., De Donno, C., Hetzel, L., Ji, Y., Ibarra, I. L., Srivatsan, S. R., Naghipourfar, M., Daza, R. M., Martin, B., et al. (2023) · Molecular Systems Biology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 307

MicroRNA Loss Enhances Learning and Memory in Mice

Konopka, W., Kiryk, A., Novak, M., Herwerth, M., Parkitna, J. R., Wawrzyniak, M., Kowarsch, A., Michaluk, P., Dzwonek, J., Arnsperger, T., et al. (2010) · The Journal of Neuroscience

MicroRNA in disease regulationMemory and Neural Mechanisms

Cited by 306

RNA velocity—current challenges and future perspectives

Bergen, V., Soldatov, R. A., Kharchenko, P. V., & Theis, F. J. (2021) · Molecular Systems Biology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 271

The Human Lung Cell Atlas: A High-Resolution Reference Map of the Human Lung in Health and Disease

Schiller, H. B., Montoro, D. T., Simon, L. M., Rawlins, E. L., Meyer, K. B., Strunz, M., Vieira Braga, F. A., Timens, W., Koppelman, G. H., Budinger, G. R. S., et al. (2019) · American Journal of Respiratory Cell and Molecular Biology

Single-cell and spatial transcriptomicsGenomics and Chromatin Dynamics

Cited by 245

Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Reichart, D., Lindberg, E. L., Maatz, H., Miranda, A. M. A., Viveiros, A., Shvetsov, N., Gärtner, A., Nadelmann, E. R., Lee, M., Kanemaru, K., et al. (2022) · Science

Cardiomyopathy and Myosin StudiesCardiac electrophysiology and arrhythmias

Cited by 240

scSLAM-seq reveals core features of transcription dynamics in single cells

Erhard, F., Baptista, M. A. P., Krammer, T., Hennig, T., Lange, M., Arampatzi, P., Jürges, C. S., Theis, F. J., Saliba, A.-E., & Dölken, L. (2019) · Nature

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 233

Mining the Unknown: A Systems Approach to Metabolite Identification Combining Genetic and Metabolic Information

Krumsiek, J., Suhre, K., Evans, A. M., Mitchell, M. W., Mohney, R. P., Milburn, M. V., Wägele, B., Römisch-Margl, W., Illig, T., Adamski, J., et al. (2012) · PLoS Genetics

Metabolomics and Mass Spectrometry StudiesBioinformatics and Genomic Networks

Cited by 197

Reconstructing gene regulatory dynamics from high-dimensional single-cell snapshot data

Ocone, A., Haghverdi, L., Mueller, N. S., & Theis, F. J. (2015) · Bioinformatics

Gene Regulatory Network AnalysisSingle-cell and spatial transcriptomics

Cited by 155

Targeted pharmacological therapy restores β-cell function for diabetes remission

Sachs, S., Bastidas-Ponce, A., Tritschler, S., Bakhti, M., Böttcher, A., Sánchez-Garrido, M. A., Tarquis-Medina, M., Kleinert, M., Fischer, K., Jall, S., et al. (2020) · Nature Metabolism

Pancreatic function and diabetesDiabetes Treatment and Management

Cited by 147

Efficient Parameter Estimation Enables the Prediction of Drug Response Using a Mechanistic Pan-Cancer Pathway Model

Fröhlich, F., Kessler, T., Weindl, D., Shadrin, A., Schmiester, L., Hache, H., Muradyan, A., Schütte, M., Lim, J.-H., Heinig, M., et al. (2018) · Cell Systems

Gene Regulatory Network AnalysisBioinformatics and Genomic Networks

Cited by 143

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Czamara, D., Eraslan, G., Page, C. M., Lahti, J., Lahti-Pulkkinen, M., Hämäläinen, E., Kajantie, E., Laivuori, H., Villa, P. M., Reynolds, R. M., et al. (2019) · Nature Communications

Epigenetics and DNA MethylationBirth, Development, and Health

Cited by 143

Machine learning for perturbational single-cell omics

Ji, Y., Lotfollahi, M., Wolf, F. A., & Theis, F. J. (2021) · Cell Systems

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 137

Conditional out-of-distribution generation for unpaired data using transfer VAE

Lotfollahi, M., Naghipourfar, M., Theis, F. J., & Wolf, F. A. (2020) · Bioinformatics

Single-cell and spatial transcriptomicsGenerative Adversarial Networks and Image Synthesis

Cited by 130

Spatial proteomics in three-dimensional intact specimens

Bhatia, H. S., Brunner, A.-D., Öztürk, F., Kapoor, S., Rong, Z., Mai, H., Thielert, M., Ali, M., Al-Maskari, R., Paetzold, J. C., et al. (2022) · Cell

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 129

A foundation model to predict and capture human cognition

Binz, M., Akata, E., Bethge, M., Brändle, F., Callaway, F., Coda-Forno, J., Dayan, P., Demircan, C., Eckstein, M. K., Éltető, N., et al. (2025) · Nature

Cognitive Science and Education ResearchDecision-Making and Behavioral Economics

Cited by 119

scPower accelerates and optimizes the design of multi-sample single cell transcriptomic studies

Schmid, K. T., Höllbacher, B., Cruceanu, C., Böttcher, A., Lickert, H., Binder, E. B., Theis, F. J., & Heinig, M. (2021) · Nature Communications

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 108

Biologically informed deep learning to query gene programs in single-cell atlases

Lotfollahi, M., Rybakov, S., Hrovatin, K., Hediyeh-zadeh, S., Talavera-López, C., Misharin, A. V., & Theis, F. J. (2023) · Nature Cell Biology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 100