Oliver M. Crook
Oliver M. Crook
Posdoctoral Researcher, University of Oxford
Verified email at stats.ox.ac.uk - Homepage
Title
Cited by
Cited by
Year
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
492019
A Comprehensive Subcellular Atlas of the Toxoplasma Proteome via hyperLOPIT Provides Spatial Context for Protein Functions
K Barylyuk, L Koreny, H Ke, S Butterworth, OM Crook, I Lassadi, V Gupta, ...
Cell Host & Microbe 28 (5), 752-766. e9, 2020
26*2020
A Bayesian mixture modelling approach for spatial proteomics
OM Crook, CM Mulvey, PDW Kirk, KS Lilley, L Gatto
PLoS Computational Biology 14, e1006516, 2018
232018
A Bioconductor workflow for the Bayesian analysis of spatial proteomics
OM Crook, LM Breckels, KS Lilley, PDW Kirk, L Gatto
F1000Research 8 (446), 2019
122019
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, 2018
82018
Spatial proteomics defines the content of trafficking vesicles captured by golgin tethers
JJH Shin, OM Crook, AC Borgeaud, J Cattin-Ortolá, SY Peak-Chew, ...
Nature Communications 11 (1), 1-13, 2020
7*2020
Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics
OM Crook, KS Lilley, L Gatto, PDW Kirk
arXiv preprint arXiv:1903.02909, 2019
52019
A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection
O Crook, A Geladaki, DJH Nightingale, O Vennard, KS Lilley, L Gatto, ...
PLoS Computational Biology 16 (11), e1008288, 2020
32020
Moving Profiling Spatial Proteomics Beyond Discrete Classification
OM Crook, T Smith, M Elzek, KS Lilley
PROTEOMICS, 1900392, 2020
32020
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
12019
Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics
OM Crook, L Gatto, PDW Kirk
Statistical Applications in Genetics and Molecular Biology, 2019
12019
Supplementary Material: Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE
OM Crook, CTR Davies, L Gatto, PDW Kirk, KS Lilley
2021
Inferring differential subcellular localisation in comparative spatial proteomics using BANDLE
O Crook, CTR Davies, L Gatto, PDW Kirk, KS Lilley
bioRxiv, 2021.01. 04.425239, 2021
2021
Supplement: A semi-supervised Bayesian approach for simultaneous protein sub-cellular localisation assignment and novelty detection
OM Crook, A Geladaki, DJH Nightingale, O Vennard, KS Lilley, L Gatto, ...
2020
A Linear Transportation Distance for Pattern Recognition
OM Crook, M Cucuringu, T Hurst, CB Schönlieb, M Thorpe, KC Zygalakis
arXiv preprint arXiv:2009.11262, 2020
2020
A Bayesian semi-parametric model for thermal proteome profiling
Siqi Fang, Paul D.W. Kirk, Marcus Bantscheff, Kathryn S. Lilley, Oliver M. Crook
biorxiv, 2020
2020
Methods to interrogate the spatial relationship between the transcriptome and proteome on a cell wide scale
KS Lilley, M Elzek, R Queiroz, TS Smith, M Monti, OM Crook, E Villanueva
MOLECULAR & CELLULAR PROTEOMICS 18 (8), S25-S25, 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
Preprint highlights, selected by the biological community
K Barylyuk, L Koreny, H Ke, S Butterworth, OM Crook, I Lassadi, V Gupta, ...
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Articles 1–20