Oliver M. Crook
Oliver M. Crook
Posdoctoral Researcher, University of Oxford
Bestätigte E-Mail-Adresse bei stats.ox.ac.uk - Startseite
Titel
Zitiert von
Zitiert von
Jahr
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
362019
A Bayesian mixture modelling approach for spatial proteomics
OM Crook, CM Mulvey, PDW Kirk, KS Lilley, L Gatto
PLoS Computational Biology 14, e1006516, 2018
192018
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
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
10*2020
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
72018
Semi-Supervised Non-Parametric Bayesian Modelling of Spatial Proteomics
OM Crook, KS Lilley, L Gatto, PDW Kirk
arXiv preprint arXiv:1903.02909, 2019
42019
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
2*2020
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
22020
Moving Profiling Spatial Proteomics Beyond Discrete Classification
OM Crook, T Smith, M Elzek, KS Lilley
PROTEOMICS, 1900392, 2020
12020
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
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, ...
Supplementary material for: Fast approximate inference for Dirichlet process mixtures with variable selection: an application to pan-cancer proteomics
OM Crook, L Gatto, PDW Kirk
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