ProfessorTimothy Ebbels
Professor of Biomedical Data Science
Department of Metabolism, Digestion and Reproduction - Faculty of Medicine
Orcid identifier0000-0002-3372-8423 (opens in a new tab)
- Professor of Biomedical Data ScienceDepartment of Metabolism, Digestion and Reproduction - Faculty of Medicine
- 020 7594 3160 (Work)
- 315D, Burlington Danes, Hammersmith Campus, United Kingdom
BIO
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,
and
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:
Improving information extraction from Nuclear Magnetic Resonance (NMR) spectroscopy & Liquid Chromatography–Mass Spectrometry (LC-MS) metabolic profiles
Novel methods for predictive modelling of post-genomic data
Statistical association networks as complex phenotypes in post-genomics
Statistical integration and visualisation of metabolic profiles with other post-genomic data
Time series analysis of post-genomic data
Computational identification and annotation of metabolomics data.
Current projects are detailed on my Research page.
Some key interests:
Metabolomic data integration
BATMAN NMR modelling
Metabolomics power analysis
Differential association networks
Large scale metabolomic data processing
Short time series analysis
Data visualisation
Metabolomic/transcriptomic pathway analysis
Modelling mass spectrometry data
Metabolic networks and pathways
Multi-omics integration
Teaching
I am a founding Director of the MRes in Biomedical Research
I run the short course 'Hands-on Data Analysis for Metabolomics'
multivariate data analysis,
and
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:
Improving information extraction from Nuclear Magnetic Resonance (NMR) spectroscopy & Liquid Chromatography–Mass Spectrometry (LC-MS) metabolic profiles
Novel methods for predictive modelling of post-genomic data
Statistical association networks as complex phenotypes in post-genomics
Statistical integration and visualisation of metabolic profiles with other post-genomic data
Time series analysis of post-genomic data
Computational identification and annotation of metabolomics data.
Current projects are detailed on my Research page.
Some key interests:
Metabolomic data integration
BATMAN NMR modelling
Metabolomics power analysis
Differential association networks
Large scale metabolomic data processing
Short time series analysis
Data visualisation
Metabolomic/transcriptomic pathway analysis
Modelling mass spectrometry data
Metabolic networks and pathways
Multi-omics integration
Teaching
I am a founding Director of the MRes in Biomedical Research
I run the short course 'Hands-on Data Analysis for Metabolomics'
ACADEMIC POSITIONS
- Professor of Biomedical Data ScienceImperial College London, London, United Kingdom1 Sep 2021 - present
- Reader in Computational BioinformaticsImperial College London, Department of Surgery & Cancer, London, United Kingdom1 Aug 2013 - 31 Aug 2021
- Senior Lecturer in Computational BioinformaticsImperial College London, Department of Surgery & Cancer, London, United Kingdom1 Oct 2010 - 31 Aug 2013
- Lecturer in Computational BioinformaticsImperial College London, London, United Kingdom1 Mar 2005 - 30 Sep 2010
- Head, Section of Bioinformatics, Department of Metabolism, Digestion & ReproductionImperial College London, London, United Kingdom1 Aug 2019 - present
DEGREES
- PhD, AstronomyUniversity of Cambridge, Cambridge, United Kingdom1 Oct 1994 - 1 Mar 1998
- BA, PhysicsUniversity of Cambridge, Cambridge, United Kingdom1 Oct 1991 - 1 Jul 1994
CERTIFICATIONS
- Certificate of Advanced Study in Teaching and Learning (CASLAT)Imperial College London, London, United Kingdom1 Jul 2007 - present
FACULTY
- Faculty of Medicine
POSITION NAME
- Professor of Biomedical Data Science