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. 



Djekic D, Pinto R, Repsilber D, et al., 2019, Serum untargeted lipidomic profiling reveals dysfunction of phospholipid metabolism in subclinical coronary artery disease., Vasc Health Risk Manag, Vol:15, Pages:123-135

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

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