Imperial College London


Faculty of MedicineDepartment of Metabolism, Digestion and Reproduction

Professor of Biomedical Data Science



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




315DBurlington DanesHammersmith Campus





  • Metabolomic data integration

    Metabolomic data integration

  • BATMAN NMR modelling

    BATMAN NMR modelling

  • Metabolomics power analysis

    Metabolomics power analysis

  • Differential association networks

    Differential association networks

  • Large scale metabolomic data processing

    Large scale metabolomic data processing

  • Short time series analysis

    Short time series analysis

  • Data visualisation

    Data visualisation

  • Metabolomic/transcriptomic pathway analysis

    Metabolomic/transcriptomic pathway analysis

  • Modelling mass spectrometry data

    Modelling mass spectrometry data

I am Professor of Biomedical Data Science and Head of the Section of Bioinformatics within the Division of Systems Medicine of the Department of Metabolism, Digestion and Reproduction. I am also Director of the MRes in Biomedical Research and co-lead for its Data Science stream. 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, artificial intelligence, 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. My main area of interest is computational metabolomics: solving the problems of metabolomics through computational and statistical means. These broad aims lead to several themes in my 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
  6.  Computational identification and annotation of metabolomics data.

Current projects are detailed on my Research page.  


Tim Ebbels introduces the MRes in Biomedical Research

Dr Tim Ebbels introduces the MRes in Biomedical Research

medicine, postgraduate study, biomedical, teaching

Selected Publications

Journal Articles

Tzoulaki I, Castagné R, Boulangé CL, et al., 2019, Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease, European Heart Journal, Vol:40, ISSN:1522-9645, Pages:2883-2896

More Publications