springScape: visualisation of microarray and contextual bioinformatic data using spring embedding and an "information landscape". - Timothy M. D. Ebbels; Bernard F. Buxton; David T. Jones (ISMB (Supplement of Bioinformatics), 2006)

Piecewise multivariate modelling of sequential metabolic profiling data. - Mattias Rantalainen; Olivier Cloarec; Timothy M. D. Ebbels; Torbjörn Lundstedt; Jeremy K. Nicholson; Elaine Holmes; Johan Trygg (BMC Bioinform., 2008)

Genetic algorithms for simultaneous variable and sample selection in metabonomics. - Rachel Cavill; Hector C. Keun; Elaine Holmes; John C. Lindon; Jeremy K. Nicholson; Timothy M. D. Ebbels (Bioinform., 2009)

Correction of mass calibration gaps in liquid chromatography-mass spectrometry metabolomics data. - H. Paul Benton; Elizabeth J. Want; Timothy M. D. Ebbels (Bioinform., 2010)

MetAssimulo: Simulation of Realistic NMR Metabolic Profiles. - Harriet J. Muncey; Rebecca Jones; Maria De Iorio; Timothy M. D. Ebbels (BMC Bioinform., 2010)

Correlation Network Analysis reveals a sequential reorganization of metabolic and transcriptional states during germination and gene-metabolite relationships in developing seedlings of Arabidopsis. - Elizabeth Allen; Annick Moing; Timothy M. D. Ebbels; Mickaël Maucourt; A. Deri Tomos; Dominique Rolin; Mark A. Hooks (BMC Syst. Biol., 2010)

A statistical framework for biomarker discovery in metabolomic time course data. - Maurice Berk; Timothy M. D. Ebbels; Giovanni Montana (Bioinform., 2011)

Integrated pathway-level analysis of transcriptomics and metabolomics data with IMPaLA. - Atanas Kamburov; Rachel Cavill; Timothy M. D. Ebbels; Ralf Herwig; Hector C. Keun (Bioinform., 2011)

Consensus-Phenotype Integration of Transcriptomic and Metabolomic Data Implies a Role for Metabolism in the Chemosensitivity of Tumour Cells. - Rachel Cavill; Atanas Kamburov; James K. Ellis; Toby J. Athersuch; Marcus S. C. Blagrove; Ralf Herwig; Timothy M. D. Ebbels; Hector C. Keun (PLoS Comput. Biol., 2011)

BATMAN - an R package for the automated quantification of metabolites from nuclear magnetic resonance spectra using a Bayesian model. - Jie Hao; William J. Astle; Maria De Iorio; Timothy M. D. Ebbels (Bioinform., 2012)

diXa: a data infrastructure for chemical safety assessment. - Diana M. Hendrickx; Hugo J. W. L. Aerts; Florian Caiment; Dominic Clark; Timothy M. D. Ebbels; Chris T. A. Evelo; Hans Gmuender; Dennie G. A. J. Hebels; Ralf Herwig; Jürgen Hescheler; Danyel G. J. Jennen; Marlon J. A. Jetten; et al. (Bioinform., 2015)

Over-representation of correlation analysis (ORCA): a method for identifying associations between variable sets. - Yotsawat Pomyen; Marcelo Segura; Timothy M. D. Ebbels; Hector C. Keun (Bioinform., 2015)

The future of metabolomics in ELIXIR. - Merlijn N. van Rijswijk; Charlie Beirnaert; Christophe Caron; Marta Cascante; Victoria Dominguez Del Angel; Warwick B. Dunn; Timothy M. D. Ebbels; Franck Giacomoni; Alejandra N. González-Beltrán; Thomas Hankemeier; Kenneth Haug; Jose L. Izquierdo-García; et al. (F1000Research, 2017)

Predictive modelling using pathway scores: robustness and significance of pathway collections. - Marcelo P. Segura-Lepe; Hector C. Keun; Timothy M. D. Ebbels (BMC Bioinform., 2019)

Metabolomics in the Cloud: Scaling Computational Tools to Big Data. - Jianliang Gao; Noureddin Sadawi; Ibrahim Karaman; Jake T. M. Pearce; Pablo A. Moreno; Anders Larsson; Marco Capuccini; Paul Elliott; Jeremy K. Nicholson; Timothy M. D. Ebbels; Robert C. Glen (CoRR, 2019)

Targeted realignment of LC-MS profiles by neighbor-wise compound-specific graphical time warping with misalignment detection. - Chiung-Ting Wu; Yizhi Wang; Yinxue Wang; Timothy M. D. Ebbels; Ibrahim Karaman; Gonçalo Graça; Rui Pinto; David M. Herrington; Yue Wang 021; Guoqiang Yu (Bioinform., 2020)

Integrative analysis of time course metabolic data and biomarker discovery. - Takoua Jendoubi; Timothy M. D. Ebbels (BMC Bioinform., 2020)

Multiple-testing correction in metabolome-wide association studies. - Alina Peluso; Robert C. Glen; Timothy M. D. Ebbels (BMC Bioinform., 2021)

Pathway analysis in metabolomics: Recommendations for the use of over-representation analysis. - Cecilia Wieder; Clément Frainay; Nathalie Poupin; Pablo Rodríguez-Mier; Florence Vinson; Juliette Cooke; Rachel P. J. Lai; Jacob G. Bundy; Fabien Jourdan; Timothy M. D. Ebbels (PLoS Comput. Biol., 2021)

Single sample pathway analysis in metabolomics: performance evaluation and application. - Cecilia Wieder; Rachel P. J. Lai; Timothy M. D. Ebbels (BMC Bioinform., 2022)

Computational Metabolomics: From Spectra to Knowledge (Dagstuhl Seminar 22181). - Corey Broeckling; Timothy M. D. Ebbels; Ewy A. Mathé; Nicola Zamboni; Cecilia Wieder (Dagstuhl Reports, 2022)

Computational Metabolomics: Towards Molecules, Models, and their Meaning (Dagstuhl Seminar 24181). - Timothy M. D. Ebbels; Soha Hassoun; Ewy A. Mathé; Justin J. J. van der Hooft; Haley Chatelaine (Dagstuhl Reports, 2024)

PathIntegrate: Multivariate modelling approaches for pathway-based multi-omics data integration. - Cecilia Wieder; Juliette Cooke; Clément Frainay; Nathalie Poupin; Russell Bowler; Fabien Jourdan; Katerina J. Kechris; Rachel P. J. Lai; Timothy M. D. Ebbels (PLoS Comput. Biol., 2024)

Genome scale metabolic network modelling for metabolic profile predictions. - Juliette Cooke; Maxime Delmas; Cecilia Wieder; Pablo Rodríguez-Mier; Clément Frainay; Florence Vinson; Timothy M. D. Ebbels; Nathalie Poupin; Fabien Jourdan (PLoS Comput. Biol., 2024)

LAVASET: Latent Variable Stochastic Ensemble of Trees. An ensemble method for correlated datasets with spatial, spectral, and temporal dependencies. - Melpomeni Kasapi; Kexin Xu; Timothy M. D. Ebbels; Declan P. O'Regan; James S. Ware; Joram M. Posma (Bioinform., 2024)