| A combinatorial library of lipid-like materials for delivery of RNAi therapeutics A Akinc, A Zumbuehl, M Goldberg, ES Leshchiner, V Busini, N Hossain, ... Nature biotechnology 26 (5), 561-569, 2008 | 1408 | 2008 |
| Rapid equilibrium sampling initiated from nonequilibrium data X Huang, GR Bowman, S Bacallado, VS Pande Proceedings of the National Academy of Sciences 106 (47), 19765-19769, 2009 | 161 | 2009 |
| Deterministic matrices matching the compressed sensing phase transitions of Gaussian random matrices H Monajemi, S Jafarpour, M Gavish, Stat 330/CME 362 Collaboration, ... Proceedings of the National Academy of Sciences 110 (4), 1181-1186, 2013 | 118 | 2013 |
| Bayesian comparison of Markov models of molecular dynamics with detailed balance constraint S Bacallado, JD Chodera, V Pande The Journal of chemical physics 131 (4), 2009 | 78 | 2009 |
| DOCKSTRING: easy molecular docking yields better benchmarks for ligand design M García-Ortegón, GNC Simm, AJ Tripp, JM Hernández-Lobato, A Bender, ... Journal of chemical information and modeling 62 (15), 3486-3502, 2022 | 51 | 2022 |
| Bayesian nonparametric ordination for the analysis of microbial communities B Ren, S Bacallado, S Favaro, S Holmes, L Trippa Journal of the American Statistical Association 112 (520), 1430-1442, 2017 | 43 | 2017 |
| Persistent topology and metastable state in conformational dynamics HW Chang, S Bacallado, VS Pande, GE Carlsson PloS one 8 (4), e58699, 2013 | 42 | 2013 |
| Bayesian analysis of variable-order, reversible Markov chains S Bacallado Annals of Statistics 39 (2), 838-864, 2011 | 33 | 2011 |
| BETS: The dangers of selection bias in early analyses of the coronavirus disease (COVID-19) pandemic Q Zhao, N Ju, S Bacallado, RD Shah Annals of Applied Statistics 15 (1), 363-390, 2021 | 28 | 2021 |
| Sufficientness postulates for Gibbs-type priors and hierarchical generalizations S Bacallado, M Battiston, S Favaro, L Trippa Statistical Science, 487-500, 2017 | 25 | 2017 |
| Bayesian nonparametric analysis of reversible Markov chains S Bacallado, S Favaro, L Trippa The Annals of Statistics, 870-896, 2013 | 23 | 2013 |
| Bayesian uncertainty directed trial designs S Ventz, M Cellamare, S Bacallado, L Trippa Journal of the American Statistical Association, 2018 | 16 | 2018 |
| Generation interval for COVID-19 based on symptom onset data S Bacallado, Q Zhao, N Ju Eurosurveillance 25 (29), 2001381, 2020 | 14 | 2020 |
| de Finetti priors using Markov chain Monte Carlo computations S Bacallado, P Diaconis, S Holmes Statistics and computing 25, 797-808, 2015 | 14 | 2015 |
| Bayesian mixed effects models for zero-inflated compositions in microbiome data analysis B Ren, S Bacallado, S Favaro, T Vatanen, C Huttenhower, L Trippa Annals of Applied Statistics 14 (1), 494-517, 2020 | 13 | 2020 |
| Looking-backward probabilities for Gibbs-type exchangeable random partitions S Bacallado, S Favaro, L Trippa Bernoulli 21 (1), 1-37, 2015 | 13 | 2015 |
| Preclinical evaluation of (S)-[18F]GE387, a novel 18-kDa translocator protein (TSPO) PET radioligand with low binding sensitivity to human polymorphism rs6971 NK Ramakrishnan, M Hird, S Thompson, DJ Williamson, L Qiao, ... European Journal of Nuclear Medicine and Molecular Imaging 49, 125-136, 2021 | 11 | 2021 |
| The effects of releasing early results from ongoing clinical trials S Ventz, S Bacallado, R Rahman, S Tolaney, JD Schoenfeld, ... Nature communications 12 (1), 801, 2021 | 7 | 2021 |
| Bayesian regularization of the length of memory in reversible sequences S Bacallado, V Pande, S Favaro, L Trippa Journal of the Royal Statistical Society Series B: Statistical Methodology …, 2016 | 6 | 2016 |
| Perfect Sampling of the Posterior in the Hierarchical Pitman–Yor Process S Bacallado, S Favaro, S Power, L Trippa Bayesian analysis 17 (3), 685, 2022 | 5 | 2022 |
