| Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells F Buettner, KN Natarajan, FP Casale, V Proserpio, A Scialdone, FJ Theis, ... Nature biotechnology 33 (2), 155-160, 2015 | 806 | 2015 |
| SARS-CoV-2 entry factors are highly expressed in nasal epithelial cells together with innate immune genes W Sungnak, N Huang, C Bécavin, M Berg, R Queen, M Litvinukova, ... Nature medicine 26 (5), 681-687, 2020 | 800 | 2020 |
| Science forum: the human cell atlas A Regev, SA Teichmann, ES Lander, I Amit, C Benoist, E Birney, ... Elife 6, e27041, 2017 | 778 | 2017 |
| SCANPY: large-scale single-cell gene expression data analysis FA Wolf, P Angerer, FJ Theis Genome biology 19 (1), 15, 2018 | 749 | 2018 |
| An atlas of genetic influences on human blood metabolites SY Shin, EB Fauman, AK Petersen, J Krumsiek, R Santos, J Huang, ... Nature genetics 46 (6), 543-550, 2014 | 681 | 2014 |
| SARS-CoV-2 receptor ACE2 is an interferon-stimulated gene in human airway epithelial cells and is detected in specific cell subsets across tissues CGK Ziegler, SJ Allon, SK Nyquist, IM Mbano, VN Miao, CN Tzouanas, ... Cell, 2020 | 675 | 2020 |
| Genome-wide association analyses identify 18 new loci associated with serum urate concentrations A Köttgen, E Albrecht, A Teumer, V Vitart, J Krumsiek, C Hundertmark, ... Nature genetics 45 (2), 145-154, 2013 | 580 | 2013 |
| Diffusion pseudotime robustly reconstructs lineage branching L Haghverdi, M Büttner, FA Wolf, F Buettner, FJ Theis Nature methods 13 (10), 845, 2016 | 531 | 2016 |
| Sparse component analysis and blind source separation of underdetermined mixtures P Georgiev, F Theis, A Cichocki IEEE Transactions on Neural Networks 16 (4), 993, 2005 | 404 | 2005 |
| Diffusion maps for high-dimensional single-cell analysis of differentiation data L Haghverdi, F Buettner, FJ Theis Bioinformatics 31 (18), 2989-2998, 2015 | 374 | 2015 |
| Hypergraphs and cellular networks S Klamt, UU Haus, F Theis PLoS Comput Biol 5 (5), e1000385, 2009 | 354 | 2009 |
| Combined single-cell functional and gene expression analysis resolves heterogeneity within stem cell populations NK Wilson, DG Kent, F Buettner, M Shehata, IC Macaulay, ... Cell stem cell 16 (6), 712-724, 2015 | 324 | 2015 |
| MicroRNA loss enhances learning and memory in mice W Konopka, A Kiryk, M Novak, M Herwerth, JR Parkitna, M Wawrzyniak, ... Journal of Neuroscience 30 (44), 14835-14842, 2010 | 302 | 2010 |
| Discovery of sexual dimorphisms in metabolic and genetic biomarkers K Mittelstrass, JS Ried, Z Yu, J Krumsiek, C Gieger, C Prehn, ... PLoS Genet 7 (8), e1002215, 2011 | 299 | 2011 |
| Decoding the regulatory network of early blood development from single-cell gene expression measurements V Moignard, S Woodhouse, L Haghverdi, AJ Lilly, Y Tanaka, ... Nature biotechnology 33 (3), 269-276, 2015 | 290 | 2015 |
| Live imaging of astrocyte responses to acute injury reveals selective juxtavascular proliferation S Bardehle, M Krüger, F Buggenthin, J Schwausch, J Ninkovic, H Clevers, ... Nature neuroscience 16 (5), 580-586, 2013 | 290 | 2013 |
| Current best practices in single‐cell RNA‐seq analysis: a tutorial MD Luecken, FJ Theis Molecular systems biology 15 (6), e8746, 2019 | 285 | 2019 |
| Characterization of transcriptional networks in blood stem and progenitor cells using high-throughput single-cell gene expression analysis V Moignard, IC Macaulay, G Swiers, F Buettner, J Schütte, ... Nature cell biology 15 (4), 363-372, 2013 | 285 | 2013 |
| Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data J Krumsiek, K Suhre, T Illig, J Adamski, FJ Theis BMC systems biology 5 (1), 21, 2011 | 268 | 2011 |
| The dynamic range of the human metabolome revealed by challenges S Krug, G Kastenmüller, F Stückler, MJ Rist, T Skurk, M Sailer, J Raffler, ... The FASEB Journal 26 (6), 2607-2619, 2012 | 260 | 2012 |
Jan KrumsiekWeill Cornell MedicineVerified email at med.cornell.edu
