Dr Mark Dunning
Department of Neuroscience
Bioinformatics Core Director
Full contact details
Department of Neuroscience
Sheffield Institute for Translational Neuroscience (SITraN)
385a Glossop Road
I obtained my PhD in the Statistics and Computational Biology group of Simon Tavare at The University of Cambridge. As part of my thesis I developed open-source software for the analysis of Illumina microarray data, which is available through the Bioconductor project.
I joined the Bioinformatics Core at Cancer Research Uk Cambridge Institute and played a key role in the analysis of gene expression profiles as part of the METABRIC project, which identified and described new subtypes of breast cancer. I also participated in the pilot phases of the International Cancer Genome Consortium (ICGC) project by developing computational pipelines to process the whole-genome sequencing data from Oesophageal cancer patients.
During my time in the Bioinformatics Core I also developed a passion for teaching and commenced a role dedicated to organising and delivering Bioinformatics training courses, with the aim of empowering wet-lab scientists to begin to explore data for themselves and foster more-productive collaborations with Bioinformaticians.
I have a strong commitment to reproducible research and making my research outputs available to other researchers, and indeed members of the public who may have funded the research in the first place. For instance, I recently developed and deployed a Shiny application that allows interested parties to query various prostate cancer datasets.
In keeping with my open access principles, the code underlying the application is available via github and utilises data sets that can be downloaded from Bioconductor. I have also recently investigated technologies such as Galaxy and Docker to ease the deployment of software and facilitate reproducible research.
- 2015 – 2017: Bioinformatics Training Co-ordinator, Cancer Research Uk, Cambridge Institute
- 2009 – 2015: Bioinformatics Analyst / Senior Bioinformatics Analyst, Cancer Research Uk Cambridge Institute
- 2005 – 2009: PhD (Oncology) University of Cambridge
- 2004 – 2005: Msc (Data Analysis, Networks and Nonlinear Dynamics) University of York
- 1999 – 2004: Bsc (Mathematics and Computer Science) University of York
- Research interests
High-throughput technologies such as next generation sequencing (NGS) can routinely produce massive amounts of data that can be used for tasks such as identifying biological samples with aberrant expression patterns or allow us to describe all variants in a genome.
However, such datasets pose new challenges in the way the data have to be analysed, annotated and interpreted which are not trivial and are daunting to the wet-lab biologist.
My interests lie in making the analysis of high-throughput datasets accessible to the non-bioinformatician; via specialised training courses and by developing computational pipelines and workflow.
I am currently exploring technologies that facilitate reproducible research and promote an open attitude to scientific research, and endeavour to make my talks, code, and analyses available whenever.
From October 2017 I will be establishing a Bioinformatics Core service at The University of Sheffield to support researchers in the planning, analysis, interpretation and management of their data.
I will also be developing and organising training courses covering the analysis skills essential to the being a modern, data-literate scientist.
- Biological heterogeneity in idiopathic pulmonary arterial hypertension identified through unsupervised transcriptomic profiling of whole blood. Nature Communications, 12(1).
- Fostering accessible online education using Galaxy as an e-learning platform. PLoS Computational Biology, 17(5). View this article in WRRO
- Distinct concentration-dependent molecular pathways regulate bone cell responses to cobalt and chromium exposure from joint replacement prostheses. International Journal of Molecular Sciences, 22(10).
- Whole blood RNA profiles associated with pulmonary arterial hypertension and clinical outcome. American Journal of Respiratory and Critical Care Medicine. View this article in WRRO
- Consensus genomic subtypes of muscle-invasive bladder cancer : a step in the right direction but still a long way to go. European Urology, 77(4), 434-435. View this article in WRRO
- The failure of microglia to digest developmental apoptotic cells contributes to the pathology of RNASET2-deficient leukoencephalopathy. Glia. View this article in WRRO
- Identification and validation of DOCK4 as a potential biomarker for risk of bone metastasis development in patients with early breast cancer. The Journal of Pathology, 247(3), 381-391. View this article in WRRO
- Neuroendocrine differentiation of prostate cancer leads to PSMA suppression. Endocrine-Related Cancer, 131-146.
- Identification of potential therapeutic targets in prostate cancer through a cross-species approach.. EMBO Molecular Medicine, 10(3).
- Translating a Prognostic DNA Genomic Classifier into the Clinic: Retrospective Validation in 563 Localized Prostate Tumors. European Urology, 72(1), 22-31.
- Mining Human Prostate Cancer Datasets: The “camcAPP” Shiny App. EBioMedicine, 17, 5-6.
- Corrigendum to “Integration of Copy Number and Transcriptomics Provides Risk Stratification in Prostate Cancer: A Discovery and Validation Cohort Study” [EBioMedicine 2 (9) (2015) 1133–1144]. EBioMedicine, 17, 238-238.
- The Early Effects of Rapid Androgen Deprivation on Human Prostate Cancer. European Urology, 70(2), 214-218.
- Gene regulatory mechanisms underpinning prostate cancer susceptibility. Nature Genetics, 48(4), 387-397.
- Integration of copy number and transcriptomics provides risk stratification in prostate cancer: A discovery and validation cohort study. EBioMedicine, 2(9), 1133-1144.
- 5-hydroxymethylcytosine marks promoters in colon that resist DNA hypermethylation in cancer. Genome Biology, 16(1).
- HES5 silencing is an early and recurrent change in prostate tumourigenesis. Endocrine-Related Cancer, 22(2), 131-144.
- A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Molecular Oncology, 9(1), 115-127.
- Tumour genomic and microenvironmental heterogeneity for integrated prediction of 5-year biochemical recurrence of prostate cancer: a retrospective cohort study. The Lancet Oncology, 15(13), 1521-1532.
- Genome-driven integrated classification of breast cancer validated in over 7,500 samples. Genome Biology, 15(8).
- Ordering of mutations in preinvasive disease stages of esophageal carcinogenesis. Nature Genetics, 46(8), 837-843.
- Loss of centrioles causes chromosomal instability in vertebrate somatic cells. The Journal of Cell Biology, 203(5), 747-756.
- Analysis of Circulating Tumor DNA to Monitor Metastatic Breast Cancer. New England Journal of Medicine, 368(13), 1199-1209.
- A Correction to the Research Article Titled: "Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling" by Y. Yuan, H. Failmezger, O. M. Rueda, H. R. Ali, S. Graf, S.-F. Chin, R. F. Schwarz, C. Curtis, M. J. Dunning, H. Bardwell, N. Johnson, S. Doyle, G. Turashvili, E. Provenzano, S. Aparicio, C. Caldas, F. Markowetz. Science Translational Medicine, 4(161), 161er6-161er6.
- Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling. Science Translational Medicine, 4(157), 157ra143-157ra143.
- Effects of BRCA2 cis-regulation in normal breast and cancer risk amongst BRCA2 mutation carriers. Breast Cancer Research, 14(2).
- The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature, 486(7403), 346-352.
- Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature, 481(7381), 389-393.
- ZNF703 is a common Luminal B breast cancer oncogene that differentially regulates luminal and basal progenitors in human mammary epithelium. EMBO Molecular Medicine, 3(3), 167-180.
- The cost of reducing starting RNA quantity for Illumina BeadArrays: A bead-level dilution experiment. BMC Genomics, 11(1).
- The importance of platform annotation in interpreting microarray data. The Lancet Oncology, 11(8), 717-717.
- Identification and correction of previously unreported spatial phenomena using raw Illumina BeadArray data. BMC Bioinformatics, 11(1).
- A re-annotation pipeline for Illumina BeadArrays: improving the interpretation of gene expression data. Nucleic Acids Research, 38(3), e17-e17.
- The pitfalls of platform comparison: DNA copy number array technologies assessed. BMC Genomics, 10(1), 588-588.
- Considerations for the processing and analysis of GoldenGate-based two-colour Illumina platforms. Statistical Methods in Medical Research, 18(5), 437-452.
- BASH: a tool for managing BeadArray spatial artefacts. Bioinformatics, 24(24), 2921-2922.
- PMC42, a breast progenitor cancer cell line, has normal-like mRNA and microRNA transcriptomes. Breast Cancer Research, 10(3).
- Spike-in validation of an Illumina-specific variance-stabilizing transformation. BMC Research Notes, 1(1), 18-18.
- Statistical issues in the analysis of Illumina data. BMC Bioinformatics, 9(1).
- Population genomics of human gene expression. Nature Genetics, 39(10), 1217-1224.
- beadarray: R classes and methods for Illumina bead-based data. Bioinformatics, 23(16), 2183-2184.
- Relative Impact of Nucleotide and Copy Number Variation on Gene Expression Phenotypes. Science, 315(5813), 848-853.
- MicroRNA expression profiling of human breast cancer identifies new markers of tumor subtype. Genome Biology, 8(10), R214-R214.
- Failure to clear developmental apoptosis contributes to the pathology of RNASET2-deficient leukoencephalopathy. View this article in WRRO
- Clinical long-read sequencing of the human mitochondrial genome for mitochondrial disease diagnostics. View this article in WRRO
- Mining human prostate cancer datasets: The “camcAPP” shiny app.
- Calling Sample Mix-Ups in Cancer Population Studies. PLoS ONE, 7(8), e41815-e41815.
- BeadArray Expression Analysis Using Bioconductor. PLoS Computational Biology, 7(12), e1002276-e1002276.