Imperial College London


Faculty of MedicineSchool of Public Health

Research Associate in Chemometrics/Metabolomics



+44 (0)20 7594 9761r.pinto Website




155Norfolk PlaceSt Mary's Campus





The focus of my research is metabolomics data processing and analysis. With that objective I test, develop and apply chemometrics and machine learning methods, mostly programming in Matlab. Currently I am working on the large Combibio and Airwave LC-MS datasets, in order to achieve the best data quality possible, and analyzing it for multiple projects, including cardiovascular disease, ageing and dementia.

I have been developing a method to match metabolomic features in multiple peak-picked untargeted LC-MS datasets. That will allow us to concatenate similarly acquired datasets in order to increase power, or to use a dataset as discovery and another as validation. 



Pênčík A, Casanova-Sáez R, Pilařová V, et al., 2018, Ultra-rapid auxin metabolite profiling for high-throughput mutant screening in Arabidopsis, Journal of Experimental Botany, Vol:69, ISSN:0022-0957, Pages:2569-2579

Lomnytska M, Pinto R, Becker S, et al., 2018, Platelet protein biomarker panel for ovarian cancer diagnosis, Biomarker Research, Vol:6, ISSN:2050-7771

Rådjursöga M, Karlsson GB, Lindqvist HM, et al., 2017, Metabolic profiles from two different breakfast meals characterized by 1H NMR-based metabolomics., Food Chem, Vol:231, Pages:267-274

Magdalinou NK, Noyce AJ, Pinto R, et al., 2017, Identification of candidate cerebrospinal fluid biomarkers in parkinsonism using quantitative proteomics., Parkinsonism Relat Disord, Vol:37, Pages:65-71

Boles U, Pinto RC, David S, et al., 2017, Dysregulated fatty acid metabolism in coronary ectasia: An extended lipidomic analysis., Int J Cardiol, Vol:228, Pages:303-308

More Publications