| 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 | 49 | 2019 |
| 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 | 23 | 2018 |
| A Bioconductor workflow for the Bayesian analysis of spatial proteomics OM Crook, LM Breckels, KS Lilley, PDW Kirk, L Gatto F1000Research 8 (446), 2019 | 12 | 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, 2018 | 8 | 2018 |
| 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 | 5 | 2019 |
| 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 | 3 | 2020 |
| Moving Profiling Spatial Proteomics Beyond Discrete Classification OM Crook, T Smith, M Elzek, KS Lilley PROTEOMICS, 1900392, 2020 | 3 | 2020 |
| 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 | 1 | 2019 |
| 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 | 1 | 2019 |
| 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, ... | | |
kathryn lilleyProfessor of Cellular DynamicsVerified email at cam.ac.uk
