| Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics A Geladaki, NK Britovšek, LM Breckels, TS Smith, OL Vennard, ... Nature Communications 10 (1), 331, 2019 | 9* | 2019 |
| A Bayesian mixture modelling approach for spatial proteomics OM Crook, CM Mulvey, PDW Kirk, KS Lilley, L Gatto PLoS Computational Biology 14, e1006516, 2018 | 6 | 2018 |
| A Bioconductor workflow for the Bayesian analysis of spatial proteomics [version 1; peer review: awaiting peer review] OM Crook, LM Breckels, KS Lilley, PDW Kirk, L Gatto F1000Research 8 (446), 2019 | 3 | 2019 |
| Targeted Treatment of Yaws With Household Contact Tracing: How Much Do We Miss? L Dyson, M Marks, OM Crook, O Sokana, AW Solomon, A Bishop, ... American journal of epidemiology 187 (4), 837-844, 2017 | 3 | 2017 |
| Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics OM Crook, L Gatto, PDW Kirk arXiv preprint arXiv:1810.05450, 2018 | 1 | 2018 |
| PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds OM Crook, T Hurst, CB Schönlieb, M Thorpe, KC Zygalakis arXiv preprint arXiv:1909.10221, 2019 | | 2019 |
| Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics OM Crook, KS Lilley, L Gatto, PDW Kirk arXiv preprint arXiv:1903.02909, 2019 | | 2019 |
| Determining the content of vesicles captured by golgin tethers using LOPIT-DC JJH Shin, OM Crook, A Borgeaud, J Cattin-Ortolá, SY Peak-Chew, ... biorxiv, 2019 | | 2019 |
| Package ‘pRolocdata’ L Gatto, LM Breckels, ML Gatto | | 2014 |
| Package ‘pRoloc’ L Gatto, T Burger, S Wieczorek, ML Gatto, I Biobase, LT Rcpp, ... | | 2013 |
Laurent Gattode Duve Institute, UCLouvainVerified email at uclouvain.be
