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| viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia ED Amir, KL Davis, MD Tadmor, EF Simonds, JH Levine, SC Bendall, ... Nature biotechnology 31 (6), 545-552, 2013 | 1719 | 2013 |
| Visualizing structure and transitions in high-dimensional biological data KR Moon, D Van Dijk, Z Wang, S Gigante, DB Burkhardt, WS Chen, K Yim, ... Nature biotechnology 37 (12), 1482-1492, 2019 | 1353 | 2019 |
| Normalization of mass cytometry data with bead standards R Finck, EF Simonds, A Jager, S Krishnaswamy, K Sachs, W Fantl, ... Cytometry Part A 83 (5), 483-494, 2013 | 835 | 2013 |
| Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm ER Zunder, R Finck, GK Behbehani, ED Amir, S Krishnaswamy, ... Nature protocols 10 (2), 316-333, 2015 | 638 | 2015 |
| Accurate reliability evaluation and enhancement via probabilistic transfer matrices S Krishnaswamy, GF Viamontes, IL Markov, JP Hayes Design, Automation and Test in Europe, 282-287, 2005 | 379 | 2005 |
| A reservoir of stem-like CD8+ T cells in the tumor-draining lymph node preserves the ongoing antitumor immune response KA Connolly, M Kuchroo, A Venkat, A Khatun, J Wang, I William, ... Science immunology 6 (64), eabg7836, 2021 | 364 | 2021 |
| Exploring single-cell data with deep multitasking neural networks M Amodio, D Van Dijk, K Srinivasan, WS Chen, H Mohsen, KR Moon, ... Nature methods 16 (11), 1139-1145, 2019 | 354 | 2019 |
| PD-1 marks dysfunctional regulatory T cells in malignant gliomas DE Lowther, BA Goods, LE Lucca, BA Lerner, K Raddassi, D van Dijk, ... JCI insight 1 (5), e85935, 2016 | 299 | 2016 |
| Conditional density-based analysis of T cell signaling in single-cell data S Krishnaswamy, MH Spitzer, M Mingueneau, SC Bendall, O Litvin, ... Science 346 (6213), 1250689, 2014 | 279 | 2014 |
| Trajectorynet: A dynamic optimal transport network for modeling cellular dynamics A Tong, J Huang, G Wolf, D Van Dijk, S Krishnaswamy International conference on machine learning, 9526-9536, 2020 | 265 | 2020 |
| Quantifying the effect of experimental perturbations at single-cell resolution DB Burkhardt, JS Stanley III, A Tong, AL Perdigoto, SA Gigante, ... Nature biotechnology 39 (5), 619-629, 2021 | 251* | 2021 |
| Manifold learning-based methods for analyzing single-cell RNA-sequencing data KR Moon, JS Stanley III, D Burkhardt, D van Dijk, G Wolf, S Krishnaswamy Current Opinion in Systems Biology 7, 36-46, 2018 | 199 | 2018 |
| Probabilistic transfer matrices in symbolic reliability analysis of logic circuits S Krishnaswamy, GF Viamontes, IL Markov, JP Hayes ACM Transactions on Design Automation of Electronic Systems (TODAES) 13 (1 …, 2008 | 184 | 2008 |
| A sandbox for prediction and integration of DNA, RNA, and proteins in single cells MD Luecken, DB Burkhardt, R Cannoodt, C Lance, A Agrawal, H Aliee, ... 35th conference on neural information processing systems (NeurIPS 2021 …, 2021 | 179 | 2021 |
| Travelgan: Image-to-image translation by transformation vector learning M Amodio, S Krishnaswamy Proceedings of the ieee/cvf conference on computer vision and pattern …, 2019 | 148 | 2019 |
| Endocrine-exocrine signaling drives obesity-associated pancreatic ductal adenocarcinoma KM Chung, J Singh, L Lawres, KJ Dorans, C Garcia, DB Burkhardt, ... Cell 181 (4), 832-847. e18, 2020 | 144 | 2020 |
| Transcriptomic and clonal characterization of T cells in the human central nervous system JL Pappalardo, L Zhang, MK Pecsok, K Perlman, C Zografou, K Raddassi, ... Science immunology 5 (51), eabb8786, 2020 | 126 | 2020 |
| MAGAN: Aligning biological manifolds M Amodio, S Krishnaswamy International conference on machine learning, 215-223, 2018 | 106 | 2018 |
| Multimodal single cell data integration challenge: results and lessons learned C Lance, MD Luecken, DB Burkhardt, R Cannoodt, P Rautenstrauch, ... BioRxiv, 2022.04. 11.487796, 2022 | 105 | 2022 |
Guy WolfUniversité de Montréal; MilaVerified email at umontreal.ca
