Oliver M. Crook
TitleCited byYear
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
62018
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
32019
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
32017
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
12018
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
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Articles 1–10