DrTimothyEbbels

Faculty of Medicine, Department of Surgery & Cancer

Reader in Computational Bioinformatics

Contact

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

Location

131Sir Alexander Fleming BuildingSouth Kensington Campus

Summary

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

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,

and

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:

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

Current projects are detailed on my Research page.

teaching

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

medicine, postgraduate study, biomedical, teaching

Publications

Journals

Gao Q, Dragsted LO, Ebbels T, 2019, Comparison of Bi- and Tri-Linear PLS Models for Variable Selection in Metabolomic Time-Series Experiments., Metabolites, Vol:9, ISSN:2218-1989

Tzoulaki I, Karaman I, Dehghan A, et al.Tzoulaki I, Karaman I, Dehghan A, Ebbels T, Holmes E, Chambers J, Kooner J, Evangelou E, Boulange C, Kaluarachchi M, Chadeau M, Chekmeneva E, Castagne R, Loh M, Lindon J, Elliott P close, Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease, European Heart Journal, ISSN:1522-9645

Open Access Link

Peters K, Bradbury J, Bergmann S, et al.Peters K, Bradbury J, Bergmann S, Capuccini M, Cascante M, de Atauri P, Ebbels TMD, Foguet C, Glen R, Gonzalez-Beltran A, Gunther UL, Handakas E, Hankemeier T, Haug K, Herman S, Holub P, Izzo M, Jacob D, Johnson D, Jourdan F, Kale N, Karaman I, Khalili B, Khonsari PE, Kultima K, Lampa S, Larsson A, Ludwig C, Moreno P, Neumann S, Novella JA, O'Donovan C, Pearce JTM, Peluso A, Piras ME, Pireddu L, Reed MAC, Rocca-Serra P, Roger P, Rosato A, Rueedi R, Ruttkies C, Sadawi N, Salek RM, Sansone S-A, Selivanov V, Spjuth O, Schober D, Thevenot EA, Tomasoni M, van Rijswijk M, van Vliet M, Viant MR, Weber RJM, Zanetti G, Steinbeck C close, 2019, PhenoMeNal: processing and analysis of metabolomics data in the cloud, Gigascience, Vol:8, ISSN:2047-217X

Conference

Kamp H, Beger R, Dorne J-LCM, et al.Kamp H, Beger R, Dorne J-LCM, Ebbels T, Ekman D, Guillou C, Goetz A, Loizou G, Leonards P, van Ravenzwaay B, Sperber S, Viant M, Walk T close, 2018, MEtabolomics standaRds Initiative in Toxicology (MERIT), 54th Congress of the European-Societies-of-Toxicology (EUROTOX) - Toxicology Out of the Box, ELSEVIER IRELAND LTD, Pages:S214-S214, ISSN:0378-4274

More Publications