| Genomic epidemiology reveals multiple introductions of SARS-CoV-2 from mainland Europe into Scotland A da Silva Filipe, JG Shepherd, T Williams, J Hughes, E Aranday-Cortes, ... Nature Microbiology 6 (1), 112-122, 2021 | 104 | 2021 |
| Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile-health data K Li, I Urteaga, CH Wiggins, A Druet, A Shea, VJ Vitzthum, N Elhadad NPJ digital medicine 3 (1), 79, 2020 | 63 | 2020 |
| A simple developmental model recapitulates complex insect wing venation patterns J Hoffmann, S Donoughe, K Li, MK Salcedo, CH Rycroft Proceedings of the National Academy of Sciences 115 (40), 9905-9910, 2018 | 48 | 2018 |
| A predictive model for next cycle start date that accounts for adherence in menstrual self-tracking K Li, I Urteaga, A Shea, VJ Vitzthum, CH Wiggins, N Elhadad Journal of the American Medical Informatics Association 29 (1), 3-11, 2022 | 23 | 2022 |
| Dose–response modeling in high-throughput cancer drug screenings: an end-to-end approach W Tansey, K Li, H Zhang, SW Linderman, R Rabadan, DM Blei, ... Biostatistics 23 (2), 643-665, 2022 | 15 | 2022 |
| A generative modeling approach to calibrated predictions: a use case on menstrual cycle length prediction I Urteaga, K Li, A Shea, VJ Vitzthum, CH Wiggins, N Elhadad Machine Learning for Healthcare Conference, 535-566, 2021 | 10 | 2021 |
| Ribotoxic collisions on CAG expansions disrupt proteostasis and stress responses in Huntington’s Disease R Aviner, TT Lee, VB Masto, D Gestaut, KH Li, R Andino, J Frydman BiorXiv, 2022.05. 04.490528, 2022 | 9 | 2022 |
| A generative, predictive model for menstrual cycle lengths that accounts for potential self-tracking artifacts in mobile health data K Li, I Urteaga, A Shea, VJ Vitzthum, CH Wiggins, N Elhadad arXiv preprint arXiv:2102.12439, 2021 | 7 | 2021 |
| Characterizing physiological and symptomatic variation in menstrual cycles using self-tracked mobile health data. npj Digital Medicine 3, 79 K Li, I Urteaga, CH Wiggins, A Druet, A Shea, VJ Vitzthum, N Elhadad | 5 | 2020 |
| Dose-response modeling in high-throughput cancer drug screenings: A case study with recommendations for practitioners W Tansey, K Li, H Zhang, SW Linderman, R Rabadan, DM Blei, ... arXiv preprint arXiv:1812.05691, 2018 | 2 | 2018 |
| Application of stable isotope labeling-based quantitative PTM proteomics and interactomics in study of Arabidopsis cell signaling EOY Wong, MH Leung, N Yang, J Ren, S Xu, S Nair, K Li, Z Al Wang, ... Molecular & Cellular Proteomics 21 (8), S46-S46, 2022 | | 2022 |
| Learning predictive models from menstrual cycle data K Li Columbia University, 2022 | | 2022 |
| Author Correction: Cotranslational prolyl hydroxylation is essential for flavivirus biogenesis R Aviner, KH Li, J Frydman, R Andino Nature 599 (7885), E3-E3, 2021 | | 2021 |
| Author Correction: Genomic epidemiology reveals multiple introductions of SARS-CoV-2 from mainland Europe into Scotland JG Shepherd, T Williams, J Hughes, AC Elihu, A Patawee, A Shirin, ... Nature Microbiology 6 (3), 414-414, 2021 | | 2021 |
| Publisher Correction: Genomic epidemiology reveals multiple introductions of SARS-CoV-2 from mainland Europe into Scotland JG Shepherd, T Williams, J Hughes, AC Elihu, A Patawee, A Shirin, ... Nature Microbiology 6 (2), 271-271, 2021 | | 2021 |
| Global proteomic and transcriptomic analysis of the LRRK2 G2019S mutation in iPSC-derived midbrain dopaminergic neurons J Martin, H Booth, B Gao, K Li, C Roberts, N Allaire, J Vowles, S Cowley, ... MOLECULAR & CELLULAR PROTEOMICS 16 (8), S52-S52, 2017 | | 2017 |
| High throughput proteomics approach reveals mechanistic basis of acute viral pathogenesis mediated by an RNAi suppressor protein in insect cells A Nayak, MJ Trnka, K Li, C Kerr, E Jan, AL Burlingame, R Andino MOLECULAR & CELLULAR PROTEOMICS 16 (8), S49-S49, 2017 | | 2017 |
| Unraveling White Lupin's Signal Transduction in Response to Phosphorus Deficiency Using iTRAQ Labeling, Phosphopeptide Enrichment, and Tandem Mass Spectrometry M Amadi, J Cole, K Li, RJ Chalkley, A Burlingame, C Uhde‐Stone The FASEB Journal 31, 617.1-617.1, 2017 | | 2017 |
| A Multiple Sclerosis Disease-Risk Variant in EVI5 Links Susceptibility to the S1P Pathway A Didonna, N Isobe, SJ Caillier, KH Li, AL Burlingame, SL Hauser, ... ANNALS OF NEUROLOGY 78, S62-S63, 2015 | | 2015 |
| Rethinking dose-response modeling in high throughput cancer drug screenings: a case study and recommendations for practitioners W Tansey, K Li, H Zhang, SW Linderman, DM Blei, R Rabadan, ... | | |
