I am a postdoctoral research chemometrician at the MRC-NIHR Phenome Centre, a world-class facility for the metabolic phenotyping of human samples. Here, I contribute to quality-control assessment, method development and biomarker discovery and validation in patient- and population-based samples with the overarching aim of discovering robust diagnostic and prognostic markers for disease risk and personalized medicine.
As such, my main research interests include: (1) elucidating the complex relationship between health status, diet, genetics, drugs, microbiome and environment in metabolic phenotyping based analysis of patients and populations (2) development of statistical methods for enhanced information recovery from spectroscopic data.
(1) Elucidating METABOLIC relationships
For example, investigating the microbial influences on metabolism.
(2) Development of Statistical Methods for Spectroscopic Data Analysis
For example, utilizing the inherent correlations between spectral variables in order to:
- Identify, deconvolve and selectively remove drug metabolite signals from NMR data
- Explore inter- and intra-metabolite connectivities
Sands CJ; Coen M; Ebbels TMD; Holmes E; Lindon JC; Nicholson JK. (2011). Data-Driven Approach for Metabolite Relationship Recovery in Biological 1H NMR Data Sets Using Iterative Statistical Total Correlation Spectroscopy. Analytical Chemistry. 83:2075-2082.
Sands CJ; Coen M; Maher AD; Ebbels TMD; Holmes E; Lindon JC; Nicholson JK. (2009). Statistical Total Correlation Spectroscopy Editing of 1H NMR Spectra of Biofluids: Application to Drug Metabolite Profile Identification and Enhanced Information Recovery. Analytical Chemistry. 81:6458-6466.
et al., 2021, Impact of pelvic radiotherapy for prostate cancer on global metabolic profiles and microbiota-driven gastrointestinal late side-effects: a longitudinal observational study., Int J Radiat Oncol Biol Phys
et al., 2021, Representing the metabolome with high fidelity: range and response as quality control factors in LC-MS-based global profiling., Analytical Chemistry, Vol:93, ISSN:0003-2700, Pages:1924-1933
et al., 2020, Circulating metabolites and lipids are associated with glycaemic measures in South Asians, Diabetic Medicine, Vol:38, ISSN:0742-3071
et al., 2020, SMolESY: An efficient and quantitative alternative to on-instrument macromolecular ¹H-NMR signal suppression, Chemical Science, Vol:11, ISSN:2041-6520, Pages:6000-6011
et al., 2019, The nPYc-Toolbox, a Python module for the pre-processing, quality-control, and analysis of metabolic profiling datasets, Bioinformatics, Vol:35, ISSN:1367-4803, Pages:5359-5360