Theis, Fabian J.

SCANPY: large-scale single-cell gene expression data analysis

Wolf, F. A., Angerer, P., & Theis, F. J. (2018) · Genome Biology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 8,881

Generalizing RNA velocity to transient cell states through dynamical modeling

Bergen, V., Lange, M., Peidli, S., Wolf, F. A., & Theis, F. J. (2020) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 2,951

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues

Ziegler, C. G. K., Allon, S. J., Nyquist, S. K., Mbano, I. M., Miao, V. N., Tzouanas, C. N., Cao, Y., Yousif, A. S., Bals, J., Hauser, B. M., et al. (2020) · Cell

SARS-CoV-2 and COVID-19 ResearchCOVID-19 Clinical Research Studies

Cited by 2,284

The human cell atlas

Regev, A., Teichmann, S. A., Lander, E. S., Amit, I., Benoist, C., Birney, E., Bodenmiller, B., Campbell, P., Carninci, P., Clatworthy, M., et al. (2017) · eLife

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 2,232

Current best practices in single-cell RNA-seq analysis: a tutorial

Luecken, M. D., & Theis, F. J. (2019) · Molecular Systems Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 2,231

PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells

Wolf, F. A., Hamey, F. K., Plass, M., Solana, J., Dahlin, J. S., Göttgens, B., Rajewsky, N., Simon, L., & Theis, F. J. (2019) · Genome Biology

Single-cell and spatial transcriptomicsTopological and Geometric Data Analysis

Cited by 1,698

An atlas of genetic influences on human blood metabolites

The Multiple Tissue Human Expression Resource (MuTHER) Consortium, Shin, S.-Y., Fauman, E. B., Petersen, A.-K., Krumsiek, J., Santos, R., Huang, J., Arnold, M., Erte, I., Forgetta, V., et al. (2014) · Nature Genetics

Genetic Associations and EpidemiologyMetabolomics and Mass Spectrometry Studies

Cited by 1,515

Severe COVID-19 Is Marked by a Dysregulated Myeloid Cell Compartment

Schulte-Schrepping, J., Reusch, N., Paclik, D., Baßler, K., Schlickeiser, S., Zhang, B., Krämer, B., Krammer, T., Brumhard, S., Bonaguro, L., et al. (2020) · Cell

COVID-19 Clinical Research StudiesSARS-CoV-2 and COVID-19 Research

Cited by 1,461

Benchmarking atlas-level data integration in single-cell genomics

Luecken, M. D., Büttner, M., Chaichoompu, K., Danese, A., Interlandi, M., Mueller, M. F., Strobl, D. C., Zappia, L., Dugas, M., Colomé-Tatché, M., et al. (2022) · Nature Methods

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,438

Diffusion pseudotime robustly reconstructs lineage branching

Haghverdi, L., Büttner, M., Wolf, F. A., Buettner, F., & Theis, F. J. (2016) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 1,385

Eleven grand challenges in single-cell data science

Lähnemann, D., Köster, J., Szczurek, E., McCarthy, D. J., Hicks, S. C., Robinson, M. D., Vallejos, C. A., Campbell, K. R., Beerenwinkel, N., Mahfouz, A., et al. (2020) · Genome Biology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,327

Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells

Buettner, F., Natarajan, K. N., Casale, F. P., Proserpio, V., Scialdone, A., Theis, F. J., Teichmann, S. A., Marioni, J. C., & Stegle, O. (2015) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,136

Single-cell RNA-seq denoising using a deep count autoencoder

Eraslan, G., Simon, L. M., Mircea, M., Mueller, N. S., & Theis, F. J. (2019) · Nature Communications

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 1,084

Best practices for single-cell analysis across modalities

Heumos, L., Schaar, A. C., Lance, C., Litinetskaya, A., Drost, F., Zappia, L., Lücken, M. D., Strobl, D. C., Henao, J., Curion, F., et al. (2023) · Nature Reviews Genetics

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 1,051

A cellular census of human lungs identifies novel cell states in health and in asthma

Vieira Braga, F. A., Kar, G., Berg, M., Carpaij, O. A., Polanski, K., Simon, L. M., Brouwer, S., Gomes, T., Hesse, L., Jiang, J., et al. (2019) · Nature Medicine

Asthma and respiratory diseasesSingle-cell and spatial transcriptomics

Cited by 896

Swarm Learning for decentralized and confidential clinical machine learning

Warnat-Herresthal, S., Schultze, H., Shastry, K. L., Manamohan, S., Mukherjee, S., Garg, V., Sarveswara, R., Händler, K., Pickkers, P., Aziz, N. A., et al. (2021) · Nature

Privacy-Preserving Technologies in DataBlockchain Technology Applications and Security

Cited by 884

A Python library for probabilistic analysis of single-cell omics data

Gayoso, A., Lopez, R., Xing, G., Boyeau, P., Valiollah Pour Amiri, V., Hong, J., Wu, K., Jayasuriya, M., Mehlman, E., Langevin, M., et al. (2022) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 789

scGen predicts single-cell perturbation responses

Lotfollahi, M., Wolf, F. A., & Theis, F. J. (2019) · Nature Methods

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 661

Diffusion maps for high-dimensional single-cell analysis of differentiation data

Haghverdi, L., Buettner, F., & Theis, F. J. (2015) · Bioinformatics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 649

destiny : diffusion maps for large-scale single-cell data in R

Angerer, P., Haghverdi, L., Büttner, M., Theis, F. J., Marr, C., & Buettner, F. (2016) · Bioinformatics

Single-cell and spatial transcriptomicsGene expression and cancer classification

Cited by 640

An atlas of the aging lung mapped by single cell transcriptomics and deep tissue proteomics

Angelidis, I., Simon, L. M., Fernandez, I. E., Strunz, M., Mayr, C. H., Greiffo, F. R., Tsitsiridis, G., Ansari, M., Graf, E., Strom, T.-M., et al. (2019) · Nature Communications

Single-cell and spatial transcriptomicsGenetics, Aging, and Longevity in Model Organisms

Cited by 637

Mapping single-cell data to reference atlases by transfer learning

Lotfollahi, M., Naghipourfar, M., Luecken, M. D., Khajavi, M., Büttner, M., Wagenstetter, M., Avsec, Ž., Gayoso, A., Yosef, N., Interlandi, M., et al. (2022) · Nature Biotechnology

Single-cell and spatial transcriptomicsGene Regulatory Network Analysis

Cited by 602

Ultra‐high sensitivity mass spectrometry quantifies single‐cell proteome changes upon perturbation

Brunner, A., Thielert, M., Vasilopoulou, C., Ammar, C., Coscia, F., Mund, A., Hoerning, O. B., Bache, N., Apalategui, A., Lubeck, M., et al. (2022) · Molecular Systems Biology

Advanced Proteomics Techniques and ApplicationsMass Spectrometry Techniques and Applications

Cited by 544

SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis

Wendisch, D., Dietrich, O., Mari, T., von Stillfried, S., Ibarra, I. L., Mittermaier, M., Mache, C., Chua, R. L., Knoll, R., Timm, S., et al. (2021) · Cell

COVID-19 Clinical Research StudiesInterstitial Lung Diseases and Idiopathic Pulmonary Fibrosis

Cited by 528