Imperial College London


Faculty of MedicineDepartment of Surgery & Cancer

Reader in Computational Bioinformatics



+44 (0)20 7594 3160t.ebbels Website




131Sir Alexander Fleming BuildingSouth Kensington Campus





I am a Reader within the Computational and Systems Medicine Section of the Department of Surgery and Cancer. My overall research interests lie at the interface between two broad areas:

multivariate data analysis,


post-genomic technologies.

More specifically, on the computational side these include, machine learning, bioinformatics, chemometrics, and multivariate statistics, and on the experimental side, the fields of genomics, transcriptomics and metabolomics. I am interested in applying diverse computational and mathematical methods in order to disentangle the mass of information at multiple biological levels generated by the –omics technologies. The ultimate aim is to synthesise the information provided by each of these techniques, thus facilitating a multi-scale understanding of biological systems. This broad aim leads to several themes in my current research:

  1. Improving information extraction from Nuclear Magnetic Resonance (NMR) spectroscopy & Liquid Chromatography–Mass Spectrometry (LC-MS) metabolic profiles
  2. Novel methods for predictive modelling of post-genomic data
  3. Statistical association networks as complex phenotypes in post-genomics
  4. Statistical integration and visualisation of metabolic profiles with other post-genomic data
  5. Time series analysis of post-genomic data

Current projects are detailed on my Research page.


Dr Tim Ebbels introduces the Biomedical Research stream of the MRes in Biomedical Research

medicine, postgraduate study, biomedical, teaching



Chan Q, Loo RL, Ebbels TMD, et al., 2017, Metabolic phenotyping for discovery of urinary biomarkers of diet, xenobiotics and blood pressure in the INTERMAP Study: an overview, Hypertension Research, Vol:40, ISSN:0916-9636, Pages:336-345

Weber RJM, Lawson TN, Salek RM, et al., 2017, Computational tools and workflows in metabolomics: An international survey highlights the opportunity for harmonisation through Galaxy, Metabolomics, Vol:13, ISSN:1573-3882

Blaise BJ, Correia G, Tin A, et al., 2016, Power Analysis and Sample Size Determination in Metabolic Phenotyping, Analytical Chemistry, Vol:88, ISSN:0003-2700, Pages:5179-5188

David R, Ebbels T, Gooderham N, et al., 2016, Synergistic and Antagonistic Mutation Responses of Human MCL-5 Cells to Mixtures of Benzo[a]pyrene and 2-Amino-1-Methyl-6-Phenylimidazo[4,5-b]pyridine: Dose-Related Variation in the Joint Effects of Common Dietary Carcinogens, Environmental Health Perspectives, Vol:124, ISSN:0091-6765, Pages:88-96


Griep LMO, Chekmeneva E, Stamler J, et al., 2016, Urinary hippurate and proline betaine relative to fruit intake, blood pressure, and body mass index, Summer meeting 2016: New technology in nutrition research and practice, CAMBRIDGE UNIV PRESS, Pages:E178-E178, ISSN:0029-6651

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