| SCANPY: large-scale single-cell gene expression data analysis FA Wolf, P Angerer, FJ Theis Genome Biology 19, 15, 2018 | 8694 | 2018 |
| Generalizing RNA velocity to transient cell states through dynamical modeling V Bergen, M Lange, S Peidli, FA Wolf†, FJ Theis† Nature Biotechnology, 2020 | 2883 | 2020 |
| PAGA: graph abstraction reconciles clustering with trajectory inference through a topology preserving map of single cells FA Wolf, FK Hamey, M Plass, [...], N Rajewsky, L Simon, FJ Theis Genome Biology 20, 59, 2019 | 1747 | 2019 |
| Diffusion pseudotime robustly reconstructs lineage branching L Haghverdi, M Buettner, FA Wolf, F Buettner, FJ Theis Nature Methods 13, 845-848, 2016 | 1495 | 2016 |
| scGen predicts single-cell perturbation responses M Lotfollahi, FA Wolf†, FJ Theis† Nature methods 16 (8), 715-721, 2019 | 612 | 2019 |
| Cell type atlas and lineage tree of a whole complex animal by single-cell transcriptomics M Plass*, J Solana*, FA Wolf, [...], FJ Theis, C Kocks, N Rajewsky Science 360 (6391), eaaq1723, 2018 | 527 | 2018 |
| A test metric for assessing single-cell RNA-seq batch correction M Büttner*, Z Miao*, FA Wolf, SA Teichmann†, FJ Theis† Nature Methods 16, 43, 2019 | 518 | 2019 |
| anndata: Access and store annotated data matrices I Virshup, S Rybakov, FJ Theis, P Angerer†, FA Wolf† Journal of Open Source Software 9 (101), 4371, 2024 | 384* | 2024 |
| Generalized Gibbs ensemble prediction of prethermalization plateaus and their relation to nonthermal steady states in integrable systems M Kollar, FA Wolf, M Eckstein Physical Review B—Condensed Matter and Materials Physics 84 (5), 054304, 2011 | 369 | 2011 |
| Reconstructing cell cycle and disease progression using deep learning P Eulenberg*, N Koehler*, T Blasi, [...], P Rees, FJ Theis†, FA Wolf† Nature Communications 8, 463, 2017 | 336 | 2017 |
| Predicting cellular responses to complex perturbations in high‐throughput screens M Lotfollahi, A Klimovskaia Susmelj, C De Donno, L Hetzel, Y Ji, IL Ibarra, ... Molecular systems biology 19 (6), e11517, 2023 | 298* | 2023 |
| The scverse project provides a computational ecosystem for single-cell omics data analysis I Virshup, D Bredikhin, L Heumos, G Palla, G Sturm, A Gayoso, I Kats, ... Nature biotechnology, 1-3, 2023 | 286 | 2023 |
| Single cells make big data: new challenges and opportunities in transcriptomics P Angerer, L Simon, S Tritschler, FA Wolf, D Fischer, FJ Theis Current Opinion in Systems Biology 4, 85-91, 2017 | 265 | 2017 |
| Strictly Single-Site DMRG Algorithm with Subspace Expansion C Hubig, IP McCulloch, U Schollwöck, FA Wolf Physical Review B 91 (15), 155115, 2015 | 239 | 2015 |
| Conditional out-of-distribution generation for unpaired data using transfer VAE M Lotfollahi, M Naghipourfar, FJ Theis†, FA Wolf† Bioinformatics 36 (Supplement_2), i610-i617, 2020 | 156* | 2020 |
| Solving nonequilibrium dynamical mean-field theory using matrix product states FA Wolf, IP McCulloch, U Schollwöck Physical Review B 90 (23), 235131, 2014 | 152 | 2014 |
| Machine learning for perturbational single-cell omics Y Ji, M Lotfollahi, FA Wolf, FJ Theis Cell Systems 12 (6), 522-537, 2021 | 148 | 2021 |
| Chebyshev matrix product state impurity solver for dynamical mean-field theory FA Wolf, IP McCulloch, O Parcollet, U Schollwöck Physical Review B 90 (11), 115124, 2014 | 134 | 2014 |
| Imaginary-time matrix product state impurity solver for dynamical mean-field theory FA Wolf, A Go, IP McCulloch, AJ Millis, U Schollwöck Physical Review X 5 (4), 041032, 2015 | 120 | 2015 |
| How to discretize a quantum bath for real-time evolution I de Vega, U Schollwöck, FA Wolf Physical Review B 92 (15), 155126, 2015 | 108 | 2015 |
Fabian J TheisHelmholtz Munich, Technical University of MunichVerified email at helmholtz-muenchen.de
