Research interests (for software see research tab)
- Multivariate statistics (metonyms: Chemometrics, Machine Learning, Pattern Recognition, Statistical Bioinformatics, ...),
- with types of application such as Data Fusion, Robust Methods, Repeated Learning, Graph Theory, Multivariate Image Analysis, Statistical Spectroscopy and Biomedical Natural Language Processing,
- in areas of application that include Metabolic Phenotyping, Precision Nutrition, Molecular Epidemiology, (Immersive) Data Visualization, Biological Networks, Computational Drug Discovery and Text Mining.
I am a Senior Lecturer in the Department of Metabolism, Digestion and Reproduction since 09/2022 to work on adaptive information recovery, robust data fusion and immersive data visualization of omics data, focusing on applications in biomedicine (cardiometabolic diseases, cancer, nutrition - e.g. via MRC and EPSRC funded research) including biomedical natural language processing (e.g. via ELIXIR and EU-HORIZON funded research).
I was a Lecturer in Cancer Informatics in the Department of Metabolism, Digestion and Reproduction (previously in the Department of Surgery and Cancer) from 08/2018 until 08/2022 to work on adaptive information recovery, robust data fusion and immersive data visualization of omics data, focusing on applications in cancer, as well as cardiometabolic diseases, and their interface with nutrition, and to the biomedical literature more generally.
Previously (02/2018 to 01/2022) I was recipient of a Rutherford Fund Fellowship (Health Data Research UK Fellow) at HDR UK to work on my project titled "Identification of Metabolic Phenotypes and Systemic Biochemical Reaction Networks Associated with Human Blood Pressure". I worked with Prof Paul Elliott and Prof Jeremy Nicholson for this project in the department of Epidemiology and Biostatistics (School of Public Health) and the department of Metabolism, Digestion and Reproduction.
From 11/2014 to 02/2018 I was a postdoctoral Research Associate in the department of Surgery and Cancer (division of Computational and Systems Medicine) working under the guidance of Prof Jeremy Nicholson and Prof Elaine Holmes on novel data visualization approaches, data fusion of NMR, MS and 16S rRNA data, and various other projects (including personalized and precision nutrition, large population phenotyping studies and development of automated statistical spectroscopy tools). Before that a Research Assistant (10/2014) working on the same project.
My PhD (10/2011 to 09/2014) was funded by an MRC-PHE Centre for Environment & Health studentship jointly between the department of Surgery and Cancer (division of Computational and Systems Medicine) and department of Epidemiology and Biostatistics. I was supervised by Prof Jeremy Nicholson and Prof Paul Elliott and working within the INTERMAP study on my PhD thesis titled Novel Statistical and BioinformaticTools for Identifying Predictive Metabolic Biomarkers in Molecular Epidemiology Studies. I passed my PhD viva on the 7th of October 2014 and was awarded the PhD on November 1st 2014.
et al., 2022, Integrated fecal microbiome–metabolome signatures reflect stress and serotonin metabolism in irritable bowel syndrome, Gut Microbes, Vol:14, ISSN:1949-0976, Pages:1-20
Yeung C, Beck T, Posma JM, 2022, MetaboListem and TABoLiSTM: two deep learning algorithms for metabolite named entity recognition, Metabolites, Vol:12, ISSN:2218-1989, Pages:1-23
et al., 2022, Auto-CORPus: a natural language processing tool for standardising and reusing biomedical literature, Frontiers in Digital Health, Vol:4, ISSN:2673-253X
et al., 2020, Nutriome-metabolome relationships provide insights into dietary intake and metabolism, Nature Food, Vol:1, ISSN:2662-1355, Pages:426-436
et al., 2020, Dietary metabotype modelling predicts individual responses to dietary interventions, Nature Food, Vol:1, ISSN:2662-1355, Pages:355-364
et al., 2018, Optimized phenotypic biomarker discovery and confounder elimination via covariate-adjusted projection to latent structures from metabolic spectroscopy data, Journal of Proteome Research, Vol:17, ISSN:1535-3893, Pages:1586-1595
et al., 2017, Objective assessment of dietary patterns using metabolic phenotyping: a randomized, controlled, crossover trial, The Lancet Diabetes & Endocrinology, Vol:5, ISSN:2213-8587, Pages:184-195
et al., 2015, Urinary metabolic signatures of human adiposity, Science Translational Medicine, Vol:7, ISSN:1946-6234, Pages:1-16