Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

Dimitrios V. Vavoulis

BSc, MRes, MSc, PhD

Statistical Machine Learning, Computational Genomics

Short Biography

I am a computational biologist in the Department of Oncology and at the Wellcome Centre for Human Genetics, University of Oxford, where I focus on the applications of probabilistic machine learning for the analysis of big genomic data. I hold a BSc in Biology and an MRes in Environmental Biology with Distinction from the University of Patras (Greece), as well as an MSc in Evolutionary and Adaptive Systems with Distinction and a PhD in Computational Neurobiology (completed under the supervision of Prof. Paul Benjamin) from the University of Sussex. Before moving to Oxford, I held research positions at the Universities of Warwick and Bristol. The unifying thread underlying my work has always been a keen interest in applying computational methodologies for modelling and data analysis in the Life Sciences.

You can find me online on Twitter and/or Github.

Book chapter

  1. Vavoulis DV. "Exploring Bayesian approaches to eQTL mapping through probabilistic programming", in Methods in Molecular Biology (vol. 2082), Springer, 2019

SELECTED PUBLICATIONS

For a full list of publications, check pubmed 

*equal contribution, co-first or co-senior authors

  1. Vavoulis DV, Cutts A, Taylor JC, Schuh A. "A statistical approach for tracking clonal dynamics in cancer using longitudinal next-generation sequencing data", Bioinformatics, 2020
  2. Klintman J, Appleby N, ..., Taylor JC*, Vavoulis DV*, Schuh A*. "Differential genomic and transcriptomic events associated with high-grade transformation of Chronic Lymphocytic Leukemia", Blood, 2020 

  3. Cutts A*, Vavoulis DV*, Petrou M, Smith F, Clark B, Henderson S, Schuh A. "A method for non-invasive prenatal diagnosis of monogenic autosomal recessive disorders", Blood, 2019

  4. Vavoulis DV, Pagnamenta AT, Knight SJL, Pentony MM, ..., Taylor JC. "Whole genome sequencing identifies putative associations between genomic polymorphisms and clinical response to the anti-epileptic drug levetiracetam", medRxiv, 2019

  5. Vavoulis DV, Taylor J & Schuh A. "Hierarchical probabilistic models for multiple gene-variant associations based on next-generation sequencing data”, Bioinformatics, 2017

  6. Vavoulis DV, Frascescatto M, Heutink P & Gough J. “DGEclust: Differential expression analysis of clustered count data”, Genome Biology, 2015

  7. Oates M, Stahlhacke J, Vavoulis DV, …, Gough J. “The SUPERFAMILY 1.75 database in 2014: a doubling of data”, Nucleic Acids Research, 2014

  8. Vavoulis DV, Straub VA, Aston JAD & Feng JF. “A self-organising state-space-model approach for parameter estimation in Hodgkin-Huxley-type models of single neurones”. PLoS Computational Biology, 2012

  9. Vavoulis DV, Nikitin ES, Kemenes I, Feng JF, Benjamin PR & Kemenes G. “Balanced plasticity and stability of the electrical properties of a molluscan modulatory interneuron after conditioning: a computational study”. Front Behav Neurosci, 2010

  10. Ashmole I, Vavoulis DV, Stansfeld PJ, Mehta PR, Feng JF, Sutcliffe MJ & Stanfield PR. “The response of the tandem pore potassium channel TASK-3 (K2P9.1) to voltage: gating at the cytoplasmic mouth”. J Physiol, 587(20):4769-4783, 2009

  11. Nikitin ES, Vavoulis DV, Kemenes I, Marra V, Pirger Z, Michel M, Feng JF, O’Shea M, Benjamin PR & Kemenes G. “Persistent sodium current is a non-synaptic substrate for long-term associative memory”. Curr Biol 18(16): 1221-1226, 2008

  12. Vavoulis DV, Straub VA, Kemenes I, Kemenes G, Feng JF & Benjamin PR. “Dynamic control of a Central Pattern Generator circuit: a computational model of the snail feeding network”. Eur J Neurosci, 2007