| The Type I IFN response to infection with Mycobacterium tuberculosis requires ESX-1-mediated secretion and contributes to pathogenesis SA Stanley, JE Johndrow, P Manzanillo, JS Cox The Journal of Immunology 178 (5), 3143-3152, 2007 | 502 | 2007 |
| Anti-inflammatory actions of lipoxin A4 and aspirin-triggered lipoxin are SOCS-2 dependent FS Machado, JE Johndrow, L Esper, A Dias, A Bafica, CN Serhan, ... Nature medicine 12 (3), 330-334, 2006 | 390 | 2006 |
| An algorithm for removing sensitive information JE Johndrow, K Lum The Annals of Applied Statistics 13 (1), 189-220, 2019 | 286* | 2019 |
| Coordination of microtubule and microfilament dynamics by Drosophila Rho1, Spire and Cappuccino AE Rosales-Nieves, JE Johndrow, LC Keller, CR Magie, DM Pinto-Santini, ... Nature cell biology 8 (4), 367-376, 2006 | 185 | 2006 |
| Scalable approximate MCMC algorithms for the horseshoe prior J Johndrow, P Orenstein, A Bhattacharya Journal of Machine Learning Research 21 (73), 1-61, 2020 | 89* | 2020 |
| Sisyphus, the Drosophila myosin XV homolog, traffics within filopodia transporting key sensory and adhesion cargos R Liu, S Woolner, JE Johndrow, D Metzger, A Flores, SM Parkhurst Oxford University Press for The Company of Biologists Limited 135 (1), 53-63, 2008 | 84 | 2008 |
| MCMC for imbalanced categorical data JE Johndrow, A Smith, N Pillai, DB Dunson Journal of the American Statistical Association, 2018 | 83* | 2018 |
| The Hastings algorithm at fifty DB Dunson, JE Johndrow Biometrika 107 (1), 1-23, 2020 | 49 | 2020 |
| Rho GTPase function in flies: insights from a developmental and organismal perspective JE Johndrow, CR Magie, SM Parkhurst Biochemistry and cell biology 82 (6), 643-657, 2004 | 39 | 2004 |
| Tensor decompositions and sparse log-linear models JE Johndrow, A Bhattacharya, DB Dunson Annals of statistics 45 (1), 1, 2017 | 38 | 2017 |
| Error bounds for approximations of Markov chains used in Bayesian sampling JE Johndrow, JC Mattingly arXiv preprint arXiv:1711.05382, 2017 | 37 | 2017 |
| Approximations of Markov chains and high-dimensional Bayesian inference JE Johndrow, JC Mattingly, S Mukherjee, D Dunson arXiv preprint arXiv:1508.03387, 2015 | 35 | 2015 |
| Scaling up data augmentation MCMC via calibration LL Duan, JE Johndrow, DB Dunson Journal of Machine Learning Research 19 (64), 1-34, 2018 | 32 | 2018 |
| Diagonal orthant multinomial probit models J Johndrow, D Dunson, K Lum Artificial intelligence and statistics, 29-38, 2013 | 30 | 2013 |
| No free lunch for approximate MCMC JE Johndrow, NS Pillai, A Smith arXiv preprint arXiv:2010.12514, 2020 | 22 | 2020 |
| Scalable MCMC for Bayes shrinkage priors JE Johndrow, P Orenstein, A Bhattacharya arXiv preprint arXiv:1705.00841, 0162-8828, 2017 | 22 | 2017 |
| Removing the influence of group variables in high-dimensional predictive modelling E Aliverti, K Lum, JE Johndrow, DB Dunson Journal of the Royal Statistical Society Series A: Statistics in Society 184 …, 2021 | 19 | 2021 |
| Estimating the number of SARS-CoV-2 infections and the impact of mitigation policies in the United States J Johndrow, P Ball, M Gargiulo, K Lum Harvard Data Sci. Rev 10, 2020 | 19* | 2020 |
| Drosophila Rho-kinase (DRok) is required for tissue morphogenesis in diverse compartments of the egg chamber during oogenesis V Verdier, JE Johndrow, M Betson, GC Chen, DA Hughes, SM Parkhurst, ... Developmental biology 297 (2), 417-432, 2006 | 19 | 2006 |
| Optimal approximating Markov chains for Bayesian inference JE Johndrow, JC Mattingly, S Mukherjee, D Dunson arXiv preprint arXiv:1508.03387, 2015 | 18 | 2015 |
David DunsonArts & Sciences Professor of Statistical Science & MathematicsVerified email at duke.edu
