Development of a robust and repeatable UPLC− MS method for the long-term metabolomic study of human serum E Zelena, WB Dunn, D Broadhurst, S Francis-McIntyre, KM Carroll, ... Analytical chemistry 81 (4), 1357-1364, 2009 | 388 | 2009 |
Molecular phenotyping of a UK population: defining the human serum metabolome WB Dunn, W Lin, D Broadhurst, P Begley, M Brown, E Zelena, ... Metabolomics 11 (1), 9-26, 2015 | 189 | 2015 |
Illuminating disease and enlightening biomedicine: Raman spectroscopy as a diagnostic tool DI Ellis, DP Cowcher, L Ashton, S O'Hagan, R Goodacre Analyst 138 (14), 3871-3884, 2013 | 186 | 2013 |
A metabolome pipeline: from concept to data to knowledge M Brown, WB Dunn, DI Ellis, R Goodacre, J Handl, JD Knowles, ... Metabolomics 1 (1), 39-51, 2005 | 186 | 2005 |
Closed-loop, multiobjective optimization of analytical instrumentation: gas chromatography/time-of-flight mass spectrometry of the metabolomes of human serum and of yeast … S O'Hagan, WB Dunn, M Brown, JD Knowles, DB Kell Analytical Chemistry 77 (1), 290-303, 2005 | 166 | 2005 |
COordination of Standards in MetabOlomicS (COSMOS): facilitating integrated metabolomics data access RM Salek, S Neumann, D Schober, J Hummel, K Billiau, J Kopka, ... Metabolomics 11 (6), 1587-1597, 2015 | 108 | 2015 |
Closed-loop, multiobjective optimization of two-dimensional gas chromatography/mass spectrometry for serum metabolomics S O'Hagan, WB Dunn, JD Knowles, D Broadhurst, R Williams, ... Analytical Chemistry 79 (2), 464-476, 2007 | 106 | 2007 |
A ‘rule of 0.5’for the metabolite-likeness of approved pharmaceutical drugs N Swainston, J Handl, DB Kell Metabolomics 11 (2), 323-339, 2015 | 72 | 2015 |
GeneGini: Assessment via the Gini coefficient of reference “housekeeping” genes and diverse human transporter expression profiles S O'Hagan, MW Muelas, PJ Day, E Lundberg, DB Kell Cell systems 6 (2), 230-244. e1, 2018 | 44 | 2018 |
The apparent permeabilities of Caco-2 cells to marketed drugs: magnitude, and independence from both biophysical properties and endogenite similarities S O’Hagan, DB Kell PeerJ 3, e1405, 2015 | 44 | 2015 |
Software review: the KNIME workflow environment and its applications in Genetic Programming and machine learning S O’Hagan, DB Kell Genetic Programming and Evolvable Machines 16 (3), 387-391, 2015 | 34 | 2015 |
DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach Y Khemchandani, S O’Hagan, S Samanta, N Swainston, TJ Roberts, ... Journal of cheminformatics 12 (1), 1-17, 2020 | 33 | 2020 |
Consensus rank orderings of molecular fingerprints illustrate the ‘most genuine’similarities between marketed drugs and small endogenous human metabolites, but highlight … S O’Hagan, DB Kell ADMET and DMPK 5 (2), 85-125, 2017 | 31 | 2017 |
Understanding the foundations of the structural similarities between marketed drugs and endogenous human metabolites S O'Hagan, DB Kell Frontiers in pharmacology 6, 105, 2015 | 31 | 2015 |
A brain-permeable inhibitor of the neurodegenerative disease target kynurenine 3-monooxygenase prevents accumulation of neurotoxic metabolites S Zhang, M Sakuma, GS Deora, CW Levy, A Klausing, C Breda, KD Read, ... Communications biology 2 (1), 1-10, 2019 | 28 | 2019 |
MetMaxStruct: a Tversky-similarity-based strategy for analysing the (sub) structural similarities of drugs and endogenous metabolites S O'Hagan, DB Kell Frontiers in pharmacology 7, 266, 2016 | 25 | 2016 |
Analysing and navigating natural products space for generating small, diverse, but representative chemical libraries S O’Hagan, DB Kell Biotechnology Journal 13 (1), 1700503, 2018 | 22 | 2018 |
VAE-Sim: a novel molecular similarity measure based on a variational autoencoder S Samanta, S O’Hagan, N Swainston, TJ Roberts, DB Kell Molecules 25 (15), 3446, 2020 | 21 | 2020 |
Analysis of drug–endogenous human metabolite similarities in terms of their maximum common substructures S O’hagan, DB Kell Journal of cheminformatics 9 (1), 1-17, 2017 | 21 | 2017 |
The role and robustness of the Gini coefficient as an unbiased tool for the selection of Gini genes for normalising expression profiling data M Wright Muelas, F Mughal, S O’Hagan, PJ Day, DB Kell Scientific reports 9 (1), 1-21, 2019 | 20 | 2019 |