Publications

[7] PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds. Oliver M. Crook, Tim Hurst, Carola-Bibiane Schönlieb, Matthew Thorpe, Konstantinos C Zygalakis. arXiv (2019)

[6] A Bioconductor workflow for the Bayesian analysis of spatial proteomics. Oliver M. Crook, Lisa Breckels, Kathyrn S. lilley, Paul D. W. Kirk, Laurent Gatto F1000Research (2019)

[5] Semi-Supervised non-parametric Bayesian modelling of spatial proteomics. Oliver M. Crook, Kathyrn S. lilley, Laurent Gatto, Paul D. W. Kirk arXiv (2019)

[4] Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics. Oliver M. Crook, Laurent Gatto, Paul D. W. Kirk arXiv (To appear in SAGAMB, 2019)

[3] Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics.  Aikaterini Geladaki, Nina Kocevar Britovsek, Lisa M. Breckels, Tom S. Smith, Owen L. Vennard, Claire M. Mulvey, Oliver M. Crook, Laurent Gatto, Kathryn S. Lilley Nature Communications (2019)

[2] A Bayesian mixture modelling approach for spatial proteomics. Oliver M. CrookClaire. M. Mulvey, Paul D.W. Kirk, Kathryn S. Lilley, Laraunt Gatto.  PloS Computational Biology  BioRxiv (2018) 

[1] Targeted treatment of yaws with contact tracing: How much do we miss? Louise Dyson, Michael Marks, Oliver M. Crook, Oliver Sokana, Anthony W. Solomon, Alex Bishop, David C. W. Mabey, T. Deirdre Hollingsworth, American Journal of Epidemiology (2017)