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Computational Metabolomics
& Systems Biology to Drive
Fundamental Discovery











About



The Metsys Lab is part of the Omics Sciences Unit at The Technology Centre of Catalonia (EURECAT), and the Department of Electrical, Electronic and Control Engineering at the University Rovira i Virgili (URV). We combine bioinformatics and analytical chemistry to develop computational tools applied to mass spectrometry-based metabolomics.

Computational metabolomics

Metabolites are the downstream product of cellular biochemistry. At the same time, metabolites are the central hub in microbiome-host interactions. The identification (annotation) of metabolites in biomedical experiments is the cornerstone for gaining new insights into cell biology, physiology and medicine. Mass spectrometry-based metabolomics is a widely used technique that allows measuring metabolites in biofluids and tissues from living organisms. At the Metsys lab we combine signal processing, machine learning, statistical and analytical chemistry techniques to develop bioinformatics tools and resources for mass spectrometry-based metabolomics data analysis and metabolite identification.


Our lab is supported by:

Research

Our lab works at the intersection between different disciplines...


SIGNAL PROCESSING

MACHINE LEARNING

ANALYTICAL CHEMISTRY

To process mass spectrometry signals and leverage their multivariate nature to enhance data processing performance. To predict chemical properties or analyze complex molecular interactions. To increase the algorithm's performance by designing specific analytical solutions and methods.

SYSTEMS BIOLOGY

STATISTICS

To understand complex biological interactions through multi-omics data integration. To make our methods robust and assess the accuracy of our algorithms and findings.

... applying them for fundamental discovery in metabolomics research:


with the following overarching research aims:


- Design methods and tools for metabolite annotation and identification

- High-throughput metabolomics data processing algorithm development

- Systems Biology-based molecular mechanism elucidation

THE TEAM

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Xavier Domingo-Almenara, Ph.D

Principal Investigator
  • "La Caixa" Junior Leader, EURECAT, Barcelona, Catalonia, Spain (2021-)
  • Adjuct Professor at the University Rovira i Virgili, Tarragona, Catalonia, Spain (2019-)
  • Postdoctoral Researcher at Scripps Research, La Jolla, California, US (2017-2019)
  • PhD in Bioengineering at Universitat Rovira i Virgili, Tarragona, Catalonia, Spain (2016)
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Sara M. de Cripan

PhD candidate
  • M.S. Bioinformatics and Biostatistics, Universitat Oberta de Catalunya (UOC) (2020)
  • ERASMUS Student at University of the West of Scotland (UWS) (2018)
  • B.Sc. Biochemistry and Molecular Biology, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain (2018)
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Trisha Arora

PhD candidate
  • Marie Curie ITN Research Fellow, EURECAT, Barcelona, Catalonia, Spain (2021-)
  • Dual B.Sc/M.S. degree in Biological Sciences, Indian Institute of Science Education and Reseach (IISER), Bhopal, India (2021)
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Aleksandr (Alex) Zubov

PhD candidate
  • Data and Research Scientist in the industry (2017-2023)
  • Master’s Degree with honors (Chemistry), Peoples' Friendship University of Russia, Moscow, Russia (2015)
  • Bachelor's Degree (Chemistry), Peoples' Friendship University of Russia, Moscow, Russia (2013)
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Adrià Olomí

Bioinformatics Scientist
  • Double B.Sc degree in Biotechnology and Informatics Engineering, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain (2023)
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Pau Orts

Undergraduate Student
  • B.Sc degree in Biomedial Engineering, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain
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Melanie Garvizu

Undergraduate Student
  • B.Sc degree in Biomedial Engineering, Universitat Rovira i Virgili, Tarragona, Catalonia, Spain

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Xula

Lab's mascot
  • Rescue Shelter

Past members

- Júlia Vall Carabasa.
BSc student (2023)
- Pedro M. López Zarzuela.
Staff Bioinformatics Scientist (2022)
- Adrià Olomí.
BSc student (2022)

PUBLICATIONS

(Selected)