Department of Statistics
24–29 St Giles'
Oxford OX1 3LB
My research explores the potential of computational statistics and statistical machine learning to assist in the medical and health sciences. In this respect I oversee a small research group working on probabilistic models and Bayesian decision analysis in complex biomedical data environments. This includes theoretical foundations, novel methodology, and “handson” study driven data science.
I hold a joint Statutory Professorship (Oxford speak for Chair) in Biostatistics at the departments of Statistics and the Nuffield Department of Medicine. Within the Nuffield medical school I am an Affiliate Member of the Li Ka Shing Centre for Health Information and Discovery. My research is partly funded through a Programme Leaders award in Statistical Genomics from the UK's Medical Research Council. I am Scientific Director for the Health Programme at the Alan Turing Institute, London.
The University of Oxford Big Data institute has recently engaged in a longterm research collaboration with Novartis. The aim of the collaboration is to develop statistical machine learning methods to better understand complex diseases using Novartis' clinical trial data. The partnership will initially focus on flagship programs in multiple sclerosis (MS), rheumatology and dermatology. MS is a chronic and ultimately debilitating disease that affects approximately 2.5 million individuals worldwide. A disease of the central nervous system, MS is characterised by the inflammation and eventual destruction of the axons. Novartis has amassed a vast database from clinical trials targeting MS, including brain MRI images across multiple modalities, clinical and genomic data. Using this data, the project aims to better characterise MS over the span of the disease and find biomarkers for early diagnosis, monitoring and prognosis of individual MS patients. The rheumatology and dermatology program will focus on the following autoimmune disorders: ankylosing spondylitis, rheumatoid arthritis, psoriatic arthritis and psoriasis. The goal of the study is to analyse the relevant studies and identify new factors driving disease progression and therapeutic response and develop cuttingedge tools to support clinical decision making.
This project aims to develop and apply computational statistics and machine learning methods to enhance interpretation of data from the International Mouse Phenotyping Consortium and to facilitate their use in identification of models for human disease. The IMPC is a multicentre collaboration aimed at measuring the phenotypic consequences of knocking out each gene in the mouse genome in turn. Several hundred measurements are taken on each animal, in procedures ranging from clinical blood chemistry, through calorimetry and body composition to behavioural phenotypes. Our current focus is on the use of sparse hierarchical factor models to effectively identify and interpret multivariate phenotype perturbations and impute unmeasured phenotypes.
HCV infects around 200,000 people within the UK and 200 million people worldwide (2% of the world population). STOPHCV is a flexible and dynamic UK wide consortium that will use patient stratification to optimise treatment of infected patients. The consortium builds on existing cutting edge clinical and scientific expertise, in partnership with industry. Our overarching aim is to define and develop a deeper understanding of patient strata and to develop prognostic models so that rational treatment strategies can be deployed. In a new era of novel Directly Acting Antiviral (DAA) therapies, treating only a subset of patients with DAA will cost the NHS an estimated £96 million/year. Therefore, refined patient stratification will be of enormous clinical and economic benefit. A focus of our program will be study of HCV genotype3 infection, highly prevalent in the UK, with a characteristic clinical phenotype, and a higher relapse rate with DAA therapy. We will also focus on difficulttotreat patient groups such as those with cirrhosis and those coinfected with HIV, where optimal management pathways will be of particular benefit in patients. Our consortium is underpinned by HCV Research UK, a network of 18 UK centres biobanking samples from 10,000 HCV infected patients, linked to a stateoftheart clinical database. A unique aspect of the STOPHCV consortium is the availability of complementary datasets on a common set of samples. This allows for integrative analysis, using all of the data for improved scientific understanding of the mechanisms underlying heterogeneity of disease susceptibility and progression, as well as hostviral interaction and implications for therapeutic response. The joint data will also enable an integrative approach to biomarker panel construction using genetic, genomic, and serum marker data, informed by the in vitro immunity experiments. Integrative analysis will take place in phases beginning with pairwise analysis of datasets prior to integration of heterogeneous sources of data.
The aim of the combined effort of SCORT consortium is to better diagnose colorectal cancer (CRC) in such a way as to increase the likelihood that the treatment with the highest chance of success, is prescribed to patients. It also aims to minimise the potential negative side effects associated with various therapies. Part of this work is to develop novel statistical methods, employing computational statistics and machine learning approaches, in biostatistics and statistical genomics to integrate the multiomics data (DNA sequence, methylation, transcriptome and patient records) generated by the consortium in order to provide a greater biological understanding of CRC and how that underlies the prediction of outcome.
New technologies are providing opportunities to measure health and disease in many novel ways. This project focuses on two such technologies that measure genomewide gene expression (RNAseq transcriptomics) and concentrations of a broad range of small molecules involved in metabolism (metabolomics). One of the next big steps in precision medicine promises to be the integration of genetic data with such longitudinally varying molecular phenotypes to enhance prediction of disease and stratify treatments across patient groups to improve health outcomes. This project gathers RNASeq and metabolomic data longitudinally from ~700 members of the TwinsUK cohort, with these data accompanied by genotypes and extensive clinical and lifestyle information. We will explore how molecular traits track and vary over time, determine how such variation relates to underlying genetic variation, and explore the joint contribution of genetic and genomic data to disease risk, with a particular focus on type II diabetes. We will develop bespoke statistical and machine learning approaches to infer the longitudinal multivariate relationships amongst genotype, molecular traits, and environmental/lifestyle factors; and their application to identify robust, reproducible signatures associated with disease susceptibility and onset.
We are members of the Computational Statistics and Machine Learning group within the Department of Statistics.
Projects and group funded by:
Title  Year  Research Area 

treeSeg: testing for dependence on tree structures M Behr, M A Ansari, A Munk, C Holmes bioRxiv, 622811 
2019 

Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap E Fong, S Lyddon, C Holmes arXiv preprint arXiv:1902.03175 
2019 

Nonparametric learning from Bayesian models with randomized objective functions S Lyddon, S Walker, C Holmes NeurIPS (2018): arXiv preprint arXiv:1806.11544 
2018 

General Bayesian Updating and the LossLikelihood Bootstrap S Lyddon, C Holmes, S Walker Biometrika, Volume 106, Issue 2 
2018 

A Framework for Adaptive MCMC Targeting Multimodal Distributions E Pompe, C Holmes, K Łatuszyński arXiv preprint arXiv:1812.02609 
2018 

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration Z Wang, S Cao, JS Morris, J Ahn, R Liu, S Tyekucheva, F Gao, B Li, W Lu, ... iScience 9, 451460 
2018 

Semiunsupervised Learning of Human Activity using Deep Generative Models M Willetts, A Doherty, S Roberts, C Holmes arXiv preprint arXiv:1810.12176 
2018 

Probabilistic Boolean Tensor Decomposition T Rukat, C Holmes, C Yau International Conference on Machine Learning, 44104419 
2018 

Principles of bayesian inference using general divergence criteria J Jewson, J Smith, C Holmes Entropy 20 (6), 442 
2018 

M, S Hollowell, L Aslett, C Holmes, A Doherty Nature Scientific Reports, 8 
2018 

TensOrMachine: Probabilistic Boolean Tensor Decomposition T Rukat, CC Holmes, C Yau To appear, ICML (2018): arXiv preprint arXiv:1805.04582 
2018 

Highthroughput mouse phenomics for characterizing mammalian gene function SDM Brown, CC Holmes, AM Mallon, TF Meehan, D Smedley, S Wells Nature Reviews Genetics, 1 
2018 

NOX1 lossoffunction genetic variants in patients with inflammatory bowel disease T Schwerd, RV Bryant, S Pandey, M Capitani, L Meran, JB Cazier, J Jung, ... Mucosal immunology 11 (2), 562 
2018 

Interferon lambda 4 impacts broadly on hepatitis C virus diversity MA Ansari, E ArandayCortes, CLC Ip, A da Silva Filipe, LS Hin, ... bioRxiv, 305151 
2018 

Multiscale blind source separation M Behr, C Holmes, A Munk The Annals of Statistics 46 (2), 711744 
2018 

Principled Bayesian Minimum Divergence Inference J Jewson, JQ Smith, C Holmes Special Edition on the Foundations of Statistics, Entropy, 20(6), 442 
2018 

A general framework for predicting the transcriptomic consequences of noncoding variation M Abdalla, MI McCarthy, CC Holmes bioRxiv, 279323 
2018 

A Doherty, K SmithBryne, T Ferreira, MV Holmes, C Holmes, SL Pulit, ... bioRxiv, 261719 
2018 

QF Wills, E MelladoGomez, R Nolan, D Warner, E Sharma, J Broxholme, ... BMC genomics 18 (1), 53 
2017 

Generalized Bayesian Updating and the LossLikelihood Bootstrap S Lyddon, C Holmes, S Walker arXiv preprint arXiv:1709.07616 
2017 

Adaptive MCMC for multimodal distributions C Holmes, K Łatuszyński, E Pompe 
2017 

AC Daly, J Cooper, DJ Gavaghan, C Holmes Journal of The Royal Society Interface 14 (134), 20170340 
2017 

Better together? Statistical learning in models made of modules PE Jacob, LM Murray, CC Holmes, CP Robert arXiv preprint arXiv:1708.08719 
2017 

J Watson, L NietoBarajas, C Holmes Statistics 51 (3), 558571 
2017 

Principles of Experimental Design for Big Data Analysis CC Drovandi, C Holmes, JM McGree, K Mengersen, S Richardson, ... Statistical Science. 2017 Aug; 32(3): 385–404 
2017 

MA Ansari, V Pedergnana, CLC Ip, A Magri, A Von Delft, D Bonsall, ... Nature genetics 49 (5), 666 
2017 

Encrypted accelerated least squares regression PM Esperança, LJM Aslett, CC Holmes AISTATS 2017: The 20th International Conference on Artificial Intelligence and Statistics, 54, 334343. 
2017 

A note on statistical repeatability and study design for high‐throughput assays G Nicholson, C Holmes Statistics in medicine 36 (5), 790798 
2017 

Bayesian Boolean Matrix Factorisation T Rukat, CC Holmes, MK Titsias, C Yau arXiv preprint arXiv:1702.06166 
2017 
This is to appear in ICML 
Digital Analysis of Tumour Microarchitecture as an Independent Prognostic Tool in Breast Cancer I Roxanis, R Colling, EA Rakha, A Green, J Rittscher, RC Conceicao, ... LABORATORY INVESTIGATION 97, 68A68A 
2017 

Assigning a value to a power likelihood in a general Bayesian model C Holmes, S Walker Biometrika, Volume 104, Issue 2, 497503 
2017 

QF Wills, E MelladoGomez, R Nolan, D Warner, E Sharma, J Broxholme, ... BMC genomics 18 (1), 53 
2017 

On Markov chain Monte Carlo Methods for Tall Data A Doucet, CC Holmes, R Bardenet 
2017 

Rejoinder: Approximate Models and Robust Decisions J Watson, C Holmes 
2017 

Transcriptome Deconvolution of Heterogeneous Tumor Samples with Immune Infiltration Z Wang, JS Morris, S Cao, J Ahn, R Liu, S Tyekucheva, B Li, W Lu, X Tang, ... bioRxiv, 146795 
2017 

AR Taylor, JA Flegg, CC Holmes, PJ Guérin, CH Sibley, MD Conrad, ... Open Forum Infectious Diseases, ofw229 
2016 

Multiscale Blind Source Separation M Behr, C Holmes, A Munk arXiv preprint arXiv:1608.07173 
2016 

Z Wang, JS Morris, CC Holmes, J Ahn, B Li, W Lu, X Tang, II Wistuba, ... Cancer Research 76 (14 Supplement), 24132413 
2016 

A general framework for updating belief distributions PG Bissiri, CC Holmes, SG Walker Journal of the Royal Statistical Society: Series B (Statistical Methodology) 
2016 

Statistical inference in hidden Markov models using ksegment constraints MK Titsias, CC Holmes, C Yau Journal of the American Statistical Association 111 (513), 200215 
2016 

S Filippi, CC Holmes, LE NietoBarajas Electronic Journal of Statistics 10 (2), 33383354 
2016 

Scalable Bayesian nonparametric regression via a PlackettLuce model for conditional ranks T GrayDavies, CC Holmes, F Caron Electronic Journal of Statistics 10 (2), 18071828 
2016 

A Bayesian nonparametric approach to testing for dependence between random variables S Filippi, CC Holmes Bayesian Analysis 12 (4), 919938 
2016 

Approximate models and robust decisions J Watson, C Holmes Statistical Science 31 (4), 465489 
2016 

AC Daly, DJ Gavaghan, C Holmes, J Cooper Royal Society open science 2 (12), 150499 
2015 

RGPM van Stiphout, L Winchester, SA Haider, J Ragoussis, AL Harris, ... Cancer Research 75 (22 Supplement 2), B156B156 
2015 

MH de Angelis, G Nicholson, M Selloum, JK White, H Morgan, ... Nature genetics 47 (9), 969978 
2015 

Encrypted statistical machine learning: new privacy preserving methods LJM Aslett, PM Esperança, CC Holmes arXiv preprint arXiv:1508.06845 
2015 

A review of homomorphic encryption and software tools for encrypted statistical machine learning LJM Aslett, PM Esperança, CC Holmes arXiv preprint arXiv:1508.06574 
2015 

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders JC Taylor, HC Martin, S Lise, J Broxholme, JB Cazier, A Rimmer, ... Nature genetics 47 (7), 717726 
2015 

Robust Linear Models for CiseQTL Analysis M Rantalainen, CM Lindgren, CC Holmes PloS one 10 (5), e0127882 
2015 

On Markov chain Monte Carlo methods for tall data R Bardenet, A Doucet, C Holmes arXiv preprint arXiv:1505.02827 
2015 

Twosample Bayesian nonparametric hypothesis testing CC Holmes, F Caron, JE Griffin, DA Stephens Bayesian Analysis 10 (2), 297320 
2015 

SJL Knight, R Clifford, P Robbe, SDC Ramos, A Burns, AT Timbs, ... Blood 124 (21), 33153315 
2014 

RM Clifford, P Robbe, S Weller, AT Timbs, M Titsias, A Burns, M Cabes, ... Blood 124 (21), 19421942 
2014 

Erythrocytosis associated with a novel missense mutation in the BPGM gene N Petousi, RR Copley, TRJ Lappin, SE Haggan, CM Bento, H Cario, ... haematologica 99 (10), e201e204 
2014 

KE Pinnick, G Nicholson, KN Manolopoulos, SE McQuaid, P Valet, ... Diabetes, DB_140385 
2014 

AR Taylor, JA Flegg, SL Nsobya, A Yeka, MR Kamya, PJ Rosenthal, ... Malaria journal 13 (1), 102 
2014 

An adaptive subsampling approach for MCMC inference in large datasets R Bardenet, A Doucet, C Holmes Proceedings of The 31st International Conference on Machine Learning, 405413 
2014 

Towards scaling up Markov chain Monte Carlo: an adaptive subsampling approach R Bardenet, A Doucet, C Holmes Proceedings of the 31st International Conference on Machine Learning (ICML ... 
2014 

Nonlinear estimation and classification DD Denison, MH Hansen, CC Holmes, B Mallick, B Yu Springer Science & Business Media 
2013 

D Mouradov, E Domingo, P Gibbs, RN Jorissen, S Li, PY Soo, L Lipton, ... The American journal of gastroenterology 108 (11), 17851793 
2013 

Integrative networkbased Bayesian analysis of diverse genomics data W Wang, V Baladandayuthapani, CC Holmes, KA Do BMC bioinformatics 14 (13), S8 
2013 

Statistical estimation of malaria genotype frequencies: a Bayesian approach A Taylor, J Flegg, G Dorsey, P Guerin, C Holmes Tropical Medicine & International Health 18, 67 
2013 

Singlecell gene expression analysis reveals genetic associations masked in wholetissue experiments QF Wills, KJ Livak, AJ Tipping, T Enver, AJ Goldson, DW Sexton, ... Nature biotechnology 31 (8), 748752 
2013 

NucleoFinder: a statistical approach for the detection of nucleosome positions J Becker, C Yau, JM Hancock, CC Holmes Bioinformatics 29 (6), 711716 
2013 

C Palles, JB Cazier, KM Howarth, E Domingo, AM Jones, P Broderick, ... Nature genetics 45 (2), 136144 
2013 

Use of multivariate analysis to suggest a new molecular classification of colorectal cancer E Domingo, R Ramamoorthy, D Oukrif, D Rosmarin, M Presz, H Wang, ... The Journal of pathology 229 (3), 441448 
2013 

Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells KJ Livak, QF Wills, AJ Tipping, K Datta, R Mittal, AJ Goldson, DW Sexton, ... Methods 59 (1), 7179 
2013 

C Palles, J Cazier, K Howarth, E Domingo, A Jones, P Broderick, Z Kemp, ... Nature Genet 45, 136144 
2013 

A decisiontheoretic approach for segmental classification C Yau, CC Holmes The Annals of Applied Statistics 7 (3), 18141835 
2013 

A Novel Test for GeneAncestry Interactions in GenomeWide Association Data JL Davies, JB Cazier, MG Dunlop, RS Houlston, IP Tomlinson, ... PloS one 7 (12), e48687 
2012 

JB Cazier, CC Holmes, J Broxholme Bioinformatics 28 (22), 29812982 
2012 

A Bayesian model for estimating within host P. falciparum haplotype frequencies AR Taylor, JA Flegg, PJ Guerin, C Roper, C Holmes Malaria Journal 11 (S1), P36 
2012 

Reprioritizing Genetic Associations in Hit Regions Using LASSO‐Based Resample Model Averaging W Valdar, J Sabourin, A Nobel, CC Holmes Genetic epidemiology 36 (5), 451462 
2012 

F Caron, C Holmes, E Rio 
2012 

F Caron, C Holmes, E Rio INRIA 
2012 

nEASE: a method for gene ontology subclassification of highthroughput gene expression data TW Chittenden, EA Howe, JM Taylor, JC Mar, MJ Aryee, H Gómez, ... Bioinformatics 28 (5), 726728 
2012 

JL Min, G Nicholson, I Halgrimsdottir, K Almstrup, A Petri, A Barrett, ... PLoS Genet 8 (2), e1002505 
2012 

SJL Knight, C Yau, R Clifford, AT Timbs, ES Akha, HM Dreau, A Burns, ... Leukemia 26 (7) 
2012 

Bayesian sparsitypathanalysis of genetic association signal using generalized t priors A Lee, F Caron, A Doucet, C Holmes Statistical applications in genetics and molecular biology 11 (2), 129 
2012 

Variance decomposition of protein profiles from antibody arrays using a longitudinal twin model BS Kato, G Nicholson, M Neiman, M Rantalainen, CC Holmes, A Barrett, ... Proteome science 9 (1), 73 
2011 

M Rantalainen, BM Herrera, G Nicholson, R Bowden, QF Wills, JL Min, ... PloS one 6 (11), e27338 
2011 

J Ciampa, M Yeager, K Jacobs, MJ Thun, S Gapstur, D Albanes, J Virtamo, ... Human heredity 72 (3), 182193 
2011 

Accounting for control mislabeling in case–control biomarker studies M Rantalainen, CC Holmes Journal of proteome research 10 (12), 55625567 
2011 

G Nicholson, M Rantalainen, JV Li, AD Maher, D Malmodin, KR Ahmadi, ... PLoS genetics 7 (9), e1002270 
2011 

Bayesian hierarchical mixture modeling to assign copy number from a targeted CNV array N Cardin, C Holmes, P Donnelly, J Marchini Genetic epidemiology 35 (6), 536548 
2011 

Stochastic boosting algorithms A Jasra, CC Holmes Statistics and Computing 21 (3), 335347 
2011 

C Yau, C Holmes Bayesian analysis (Online) 6 (2), 329 
2011 

JG Ciampa, C Holmes, N Chatterjee Cancer Research 71 (8 Supplement), 27472747 
2011 

A Drong, G Nicholson, M Schuster, F Karpe, MI McCarthy, CC Holmes, ... 
2011 

C Holmes, L Held Bayesian Analysis 6 (2), 357358 
2011 

Bayesian non‐parametric hidden Markov models with applications in genomics C Yau, O Papaspiliopoulos, GO Roberts, C Holmes Journal of the Royal Statistical Society: Series B (Statistical Methodology ... 
2011 

Human metabolic profiles are stably controlled by genetic and environmental variation G Nicholson, M Rantalainen, AD Maher, JV Li, D Malmodin, KR Ahmadi, ... Molecular systems biology 7 (1), 525 
2011 

Therapeutic implications of GIPC1 silencing in cancer TW Chittenden, J Pak, R Rubio, H Cheng, K Holton, N Prendergast, ... PloS one 5 (12), e15581 
2010 

A Timbs, S Knight, E SadighiAkha, A Burns, H Dreau, AM Hewitt, C Hatton, ... Blood 116 (21), 35903590 
2010 

IM Heid, AU Jackson, JC Randall, TW Winkler, L Qi, V Steinthorsdottir, ... Nature genetics 42 (11), 949960 
2010 

Elusive copy number variation in the mouse genome A Agam, B Yalcin, A Bhomra, M Cubin, C Webber, C Holmes, J Flint, ... PLoS One 5 (9), e12839 
2010 

C Yau, D Mouradov, RN Jorissen, S Colella, G Mirza, G Steers, A Harris, ... Genome biology 11 (9), R92 
2010 

A hierarchical Bayesian framework for constructing sparsityinducing priors A Lee, F Caron, A Doucet, C Holmes arXiv preprint arXiv:1009.1914 
2010 

TG Clark, SG Campino, E Anastasi, S Auburn, YY Teo, K Small, ... Bioinformatics 
2010 

JL Davies, J Hein, CC Holmes Genetic epidemiology 34 (4), 299308 
2010 

Q Zhou, AKK Ching, WKC Leung, C Szeto, SM Ho, CC Holmes, Y Yuan, ... Cancer Research 70 (8 Supplement), 44234423 
2010 

Computational issues arising in Bayesian nonparametric hierarchical models J Grifﬁn, C Holmes Bayesian Nonparametrics 28, 208 
2010 

An invitation to Bayesian nonparametrics NL Hjort, C Holmes, P Müller, SG Walker Bayesian Nonparametrics 28, 1 
2010 

NL Hjort, C Holmes, P Müller, SG Walker Cambridge University Press 
2010 

N Craddock, ME Hurles, N Cardin, RD Pearson, V Plagnol, S Robson, ... Nature 464 (7289), 713720 
2010 

M Rantalainen, BM Herrera, G Nicholson, QF Wills, R Bowden, MJ Neville, ... 
2010 

Bayesian nonparametrics. Cambridge series in statistical and probabilistic mathematics NL Hjort, C Holmes, P Müller, SG Walker Cambridge: Cambridge Univ. Press. Mathematical Reviews (MathSciNet): MR2722987 
2010 

A Lee, C Yau, MB Giles, A Doucet, CC Holmes Journal of Computational and Graphical Statistics 19 (4), 769789 
2010 

MA Suchard, C Holmes, M West Bulletin of the International Society for Bayesian Analysis 17 (1), 1216 
2010 

A boosting approach to structure learning of graphs with and without prior knowledge S Anjum, A Doucet, CC Holmes Bioinformatics 25 (22), 29292936 
2009 

FE Mackenzie, A Parker, NJ Parkinson, PL Oliver, D Brooker, P Underhill, ... Genes, Brain and Behavior 8 (7), 699713 
2009 

Mapping in structured populations by resample model averaging W Valdar, CC Holmes, R Mott, J Flint Genetics 182 (4), 12631277 
2009 

Reply to Wirth et al.: In vivo profiles show continuous variation between 2 cellular populations JE Lemieux, A Feller, CC Holmes, CI Newbold Proceedings of the National Academy of Sciences 106 (27), E71E72 
2009 

A Antonyuk, C Holmes Genetic epidemiology 33 (5), 371378 
2009 

JW Klingelhoefer, L Moutsianas, C Holmes Bioinformatics 25 (13), 15941601 
2009 

JE Lemieux, N GomezEscobar, A Feller, C Carret, A AmambuaNgwa, ... Proceedings of the National Academy of Sciences 106 (18), 75597564 
2009 

Phylogenetic inference under recombination using Bayesian stochastic topology selection A Webb, JM Hancock, CC Holmes Bioinformatics 25 (2), 197203 
2009 

Antithetic methods for gibbs samplers C Holmes, A Jasra Journal of Computational and Graphical Statistics 18 (2), 401414 
2009 

Beyond toplines: Heterogeneous treatment effects in randomized experiments A Feller, CC Holmes Unpublished manuscript, Oxford University 
2009 

E Giannoulatou, C Yau, S Colella, J Ragoussis, CC Holmes Bioinformatics 24 (19), 22092214 
2008 

Key issues in conducting a metaanalysis of gene expression microarray datasets A Ramasamy, A Mondry, CC Holmes, DG Altman PLoS Med 5 (9), e184 
2008 

TW Chittenden, EA Howe, AC Culhane, R Sultana, JM Taylor, C Holmes, ... Genomics 91 (6), 508511 
2008 

Interacting sequential Monte Carlo samplers for transdimensional simulation A Jasra, A Doucet, DA Stephens, CC Holmes Computational Statistics & Data Analysis 52 (4), 17651791 
2008 

CNV discovery using SNP genotyping arrays C Yau, CC Holmes Cytogenetic and genome research 123 (14), 307312 
2008 

Populationbased reversible jump Markov chain Monte Carlo A Jasra, DA Stephens, CC Holmes Biometrika, 787807 
2007 

CC Holmes, A Pintore Bayesian statistics 8: proceedings of the eighth Valencia International ... 
2007 

On populationbased simulation for static inference A Jasra, DA Stephens, CC Holmes Statistics and Computing 17 (3), 263279 
2007 

Mcmc Methods for Bayesian Variable Selection in Largescale Genomic Applications M Zucknick, C Holmes, S Richardson Annals of Human Genetics 71 (4), 558559 
2007 

Flexible threshold models for modelling interest rate volatility P Dellaportas, DGT Denison, C Holmes Econometric reviews 26 (24), 419437 
2007 

S Colella, C Yau, JM Taylor, G Mirza, H Butler, P Clouston, AS Bassett, ... Nucleic Acids Research 35 (6), 20132025 
2007 

Bayesian nonparametric calibration with applications in spatial epidemiology JE Griffin, CC Holmes Technical Report, Institute of Mathematics, Statistics and Actuarial Science ... 
2007 

Integrating 3D information from thermochronological data over unknown spatial scales K Gallagher, J Stephenson, R Brown, C Holmes Geophysical Research Abstracts 9, 09015 
2007 

LJ Astle, CC Holmes, DJ Balding WILEYLISS 31 (6), 605605 
2007 

J Stephenson, K Gallagher, C Holmes Geochimica et Cosmochimica Acta 70 (20), 51835200 
2006 

Putting the data to work—strategies for modelling multiple samples in multiple dimensions K Gallagher, J Stephenson, C Holmes, R Brown Geochimica et Cosmochimica Acta 70 (18), A190 
2006 

A new approach to mixture modelling for geochronology K Gallagher, A Jasra, D Stephens, C Holmes Geochimica et Cosmochimica Acta 70 (18), A190 
2006 

Bayesian mixture modelling in geochronology via Markov chain Monte Carlo A Jasra, DA Stephens, K Gallagher, CC Holmes Mathematical geology 38 (3), 269300 
2006 

A quantitative study of gene regulation involved in the immune response of anopheline mosquitoes NA Heard, CC Holmes, DA Stephens Journal of the American Statistical Association 101 (473), 1829 
2006 

Spatially adaptive smoothing splines A Pintore, P Speckman, CC Holmes Biometrika, 113125 
2006 

J Stephenson, K Gallagher, CC Holmes Earth and Planetary Science Letters 241 (3), 557570 
2006 

V Baladandayuthapani, CC Holmes, BK Mallick, RJ Carroll 
2006 

Analysis of geochronological data with measurement error using Bayesian mixtures A Jasra, DA Stephens, K Gallagher, CC Holmes Mathematical Geology 38, 269300 
2006 

Modeling nonlinear gene interactions using Bayesian MARS V Baladandayuthapani, CC Holmes, BK Mallick, RJ Carroll Bayesian Inference for Gene Expression and Proteomics. Cambridge University ... 
2006 

Modulation of the BK channel by estrogens: examination at single channel level H De Wet, M Allen, C Holmes, M Stobbart, JD Lippiat, H De Wet, M Allen, ... Molecular membrane biology 23 (5), 420429 
2006 

Bayesian auxiliary variable models for binary and multinomial regression CC Holmes, L Held Bayesian analysis 1 (1), 145168 
2006 

Bayesian prediction via partitioning CC Holmes, DGT Denison, S Ray, BK Mallick Journal of Computational and Graphical Statistics 14 (4), 811830 
2005 

NA Heard, CC Holmes, DA Stephens, DJ Hand, G Dimopoulos Proceedings of the National Academy of Sciences of the United States of ... 
2005 

Low temperature thermochronology and modeling strategies for multiple samples 1: Vertical profiles K Gallagher, J Stephenson, R Brown, C Holmes, P Fitzgerald Earth and Planetary Science Letters 237 (1), 193208 
2005 

Analyzing nonstationary spatial data using piecewise Gaussian processes HM Kim, BK Mallick, CC Holmes Journal of the American Statistical Association 100 (470), 653668 
2005 

Markov chain Monte Carlo methods and the label switching problem in Bayesian mixture modeling A Jasra, CC Holmes, DA Stephens Statistical Science, 5067 
2005 

All systems GO for understanding mouse gene function C Holmes, SDM Brown The Scientist 19 (1), 20.120.1 
2005 

A statistical technique for modelling nonstationary spatial processes J Stephenson, C Holmes, K Gallagher, A Pintore Geostatistics Banff 2004, 125134 
2005 

A dimensionreduction approach for spectral tempering using empirical orthogonal functions A Pintore, CC Holmes Geostatistics Banff 2004, 10071015 
2005 

Exploiting 3D spatial sampling in inverse modeling of thermochronological data K Gallagher, J Stephenson, R Brown, C Holmes, P Ballester Reviews in mineralogy and geochemistry 58 (1), 375387 
2005 

All systems GO for understanding mouse gene function C Holmes, SDM Brown Journal of biology 3 (5), 20 
2004 

J Stephenson, K Gallagher, CC Holmes Geological Society, London, Special Publications 239 (1), 195209 
2004 

Spatially adaptive nonstationary covariance functions via spatially adaptive spectra A Pintore, C Holmes http:\\ www. stats. ox. ac. uk cholmes\ Reports\ spectral tempering. pdf 
2004 

Generalized nonlinear modeling with multivariate freeknot regression splines CC Holmes, BK Mallick Journal of the American Statistical Association 98 (462), 352368 
2003 

Likelihood inference in nearestneighbour classification models CC Holmes, NM Adams Biometrika, 99112 
2003 

Generalized monotonic regression using random change points CC Holmes, NA Heard Statistics in Medicine 22 (4), 623638 
2003 

CC Holmes, DGT Denison Machine Learning 50 (3), 279301 
2003 

Gauss mixture quantization: clustering Gauss mixtures RM Gray, DD Denison, MH Hansen, CC Holmes, B Mallick, B Yu Nonlinear Estimation and Classification 1003, 189212 
2003 

Bayesian free knot polynomial splines of random order R Graziani, C Holmes Università commerciale Luigi Bocconi 
2003 

Perfect simulation for Bayesian curve and surface fitting CC Holmes, BK Mallick Preprint from www. stat. tamu. edu/~ bmallick/papers/perf. ps 
2003 

Classification with bayesian MARS CC Holmes, DGT Denison Machine Learning 50 (1), 159173 
2003 

Efficient simulation of Bayesian logistic regression models C Holmes, L KnorrHeld Discussion papers/Sonderforschungsbereich 386 der LudwigMaximilians ... 
2003 

Accounting for model uncertainty in seemingly unrelated regressions CC Holmes, DGT Denison, BK Mallick Journal of Computational and Graphical Statistics 11 (3), 533551 
2002 

Perfect simulation involving functionals of a Dirichlet process A Guglielmi, CC Holmes, SG Walker Journal of Computational and Graphical Statistics 11 (2), 306310 
2002 

J Ferreira, DGT Denison, CC Holmes 
2002 

A probabilistic nearest neighbour method for statistical pattern recognition CC Holmes, NM Adams Journal of the Royal Statistical Society: Series B (Statistical Methodology ... 
2002 

DGT Denison, NM Adams, CC Holmes, DJ Hand Computational statistics & data analysis 38 (4), 475485 
2002 

Perfect sampling for the wavelet reconstruction of signals C Holmes, DGT Denison IEEE Transactions on Signal Processing 50 (2), 337344 
2002 

Minimumentropy data partitioning using reversible jump Markov chain Monte Carlo SJ Roberts, C Holmes, D Denison IEEE Transactions on Pattern Analysis and Machine Intelligence 23 (8), 909914 
2001 

Bayesian partitioning for estimating disease risk DGT Denison, CC Holmes Biometrics 57 (1), 143149 
2001 

Minimumentropy data clustering using reversible jump markov chain monte carlo S Roberts, C Holmes, D Denison Artificial Neural Networks—ICANN 2001, 103110 
2001 

Bayesian regression with multivariate linear splines CC Holmes, BK Mallick Journal of the Royal Statistical Society: Series B (Statistical Methodology ... 
2001 

Bayesian wavelet networks for nonparametric regression CC Holmes, BK Mallick IEEE transactions on neural networks 11 (1), 2735 
2000 

Generalised nonlinear modelling with multivariate smoothing splines CC Holmes, BK Mallick Unpublished manuscript, Statistics Section, Department of Mathematics ... 
1999 

Bayesian wavelet analysis with a model complexity prior CC Holmes, DGT Denison Bayesian statistics 6, 769776 
1999 

Bayesian radial basis functions of variable dimension CC Holmes, BK Mallick Neural Computation 10 (5), 12171233 
1998 

Modelbased geostatisticsDiscussion R Webster, A Lawson, C Glasbey, G Horgan, D Elston, G Host, ... 
1998 
