| Recovering gene interactions from single-cell data using data diffusion D Van Dijk, R Sharma, J Nainys, K Yim, P Kathail, AJ Carr, C Burdziak, ... Cell 174 (3), 716-729. e27, 2018 | 1333 | 2018 |
| Wishbone identifies bifurcating developmental trajectories from single-cell data M Setty, MD Tadmor, S Reich-Zeliger, O Angel, TM Salame, P Kathail, ... Nature biotechnology 34 (6), 637-645, 2016 | 628 | 2016 |
| MAGIC: A diffusion-based imputation method reveals gene-gene interactions in single-cell RNA-sequencing data D Dijk, J Nainys, R Sharma, P Kaithail, AJ Carr, KR Moon, L Mazutis, ... BioRxiv, 111591, 2017 | 170 | 2017 |
| Personal transcriptome variation is poorly explained by current genomic deep learning models C Huang, RW Shuai, P Baokar, R Chung, R Rastogi, P Kathail, ... Nature Genetics 55 (12), 2056-2059, 2023 | 8 | 2023 |
| Characterizing uncertainty in predictions of genomic sequence-to-activity models A Bajwa, R Rastogi, P Kathail, RW Shuai, N Ioannidis Machine Learning in Computational Biology, 279-297, 2024 | | 2024 |
| Population Diversity at the Single-Cell Level MG Gordon, P Kathail, B Choy, MC Kim, T Mazumder, M Gearing, CJ Ye Annual Review of Genomics and Human Genetics 25, 2024 | | 2024 |
| Reference-free multiplexed single-cell sequencing identifies genetic modifiers of the human immune response GC Hartoularos, Y Si, F Zhang, P Kathail, DS Lee, A Ogorodnikov, Y Sun, ... bioRxiv, 2023.05. 29.542756, 2023 | | 2023 |
| Assessing the utility of genomic deep learning models for disease-relevant variant effect prediction P Kathail, R Shuai, R Chung, CJ Ye, G Loeb, NM Ioannidis International Conference on Machine Learning (ICML) Workshop on …, 2022 | | 2022 |
