| Eleven grand challenges in single-cell data science D Lähnemann, J Köster, E Szczurek, DJ McCarthy, SC Hicks, ... Genome Biology 21 (1), 1-35, 2020 | 1120 | 2020 |
| Normalizing single-cell RNA sequencing data: challenges and opportunities CA Vallejos, D Risso, A Scialdone, S Dudoit, JC Marioni Nature methods 14 (6), 565-571, 2017 | 477 | 2017 |
| High-sensitivity troponin in the evaluation of patients with suspected acute coronary syndrome: a stepped-wedge, cluster-randomised controlled trial ASV Shah, A Anand, FE Strachan, AV Ferry, KK Lee, AR Chapman, ... The Lancet 392 (10151), 919-928, 2018 | 392 | 2018 |
| Aging increases cell-to-cell transcriptional variability upon immune stimulation CP Martinez-Jimenez, N Eling, HC Chen, CA Vallejos, AA Kolodziejczyk, ... Science 355 (6332), 1433-1436, 2017 | 339 | 2017 |
| BASiCS: Bayesian analysis of single-cell sequencing data CA Vallejos, JC Marioni, S Richardson PLoS computational biology 11 (6), e1004333, 2015 | 335 | 2015 |
| High-sensitivity cardiac troponin and the universal definition of myocardial infarction AR Chapman, PD Adamson, ASV Shah, A Anand, FE Strachan, AV Ferry, ... Circulation 141 (3), 161-171, 2020 | 193 | 2020 |
| Beyond comparisons of means: understanding changes in gene expression at the single-cell level CA Vallejos, S Richardson, JC Marioni Genome Biology 17 (1), 1-14, 2016 | 107 | 2016 |
| Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data N Eling, AC Richard, S Richardson, JC Marioni, CA Vallejos Cell systems 9 (4), 401, 2019 | 89 | 2019 |
| Correcting the Mean-Variance Dependency for Differential Variability Testing Using Single-Cell RNA Sequencing Data N Eling, AC Richard, S Richardson, JC Marioni, CA Vallejos Cell systems 7 (3), 284-294. e12, 2018 | 80 | 2018 |
| Single-nucleus RNA-seq2 reveals functional crosstalk between liver zonation and ploidy ML Richter, IK Deligiannis, K Yin, A Danese, E Lleshi, P Coupland, ... Nature communications 12 (1), 1-16, 2021 | 58 | 2021 |
| Refining epigenetic prediction of chronological and biological age E Bernabeu, DL McCartney, DA Gadd, RF Hillary, AT Lu, L Murphy, ... Genome Medicine 15 (1), 12, 2023 | 55 | 2023 |
| Bayesian survival modelling of university outcomes CA Vallejos, MFJ Steel Journal of the Royal Statistical Society: Series A (Statistics in Society …, 2017 | 44 | 2017 |
| Multimodal decoding of human liver regeneration KP Matchett, JR Wilson-Kanamori, JR Portman, CA Kapourani, F Fercoq, ... Nature, 1-8, 2024 | 23 | 2024 |
| scMET: Bayesian modeling of DNA methylation heterogeneity at single-cell resolution CA Kapourani, R Argelaguet, G Sanguinetti, CA Vallejos Genome Biology 22 (1), 1-21, 2021 | 22 | 2021 |
| Objective Bayesian survival analysis using shape mixtures of log-normal distributions CA Vallejos, MFJ Steel Journal of the American Statistical Association 110 (510), 697-710, 2015 | 21 | 2015 |
| Brain matters: unveiling the distinct contributions of region, age, and sex to glia diversity and CNS function LA Seeker, N Bestard-Cuche, S Jäkel, NL Kazakou, SMK Bøstrand, ... Acta Neuropathologica Communications 11 (1), 1-23, 2023 | 19 | 2023 |
| Exploring a world of a thousand dimensions CA Vallejos Nature Biotechnology 37 (12), 1423-1424, 2019 | 19 | 2019 |
| Model updating after interventions paradoxically introduces bias J Liley, S Emerson, B Mateen, C Vallejos, L Aslett, S Vollmer International Conference on Artificial Intelligence and Statistics, 3916-3924, 2021 | 17 | 2021 |
| Improving risk stratification for patients with type 2 myocardial infarction C Taggart, K Monterrubio-Gómez, A Roos, J Boeddinghaus, DM Kimenai, ... Journal of the American College of Cardiology 81 (2), 156-168, 2023 | 16 | 2023 |
| Development and validation of DNA Methylation scores in two European cohorts augment 10-year risk prediction of type 2 diabetes Y Cheng, DA Gadd, C Gieger, K Monterrubio-Gómez, Y Zhang, I Berta, ... Nature Aging 3 (4), 450-458, 2023 | 13 | 2023 |
John MarioniGenentechVerified email at gene.com
