Lines of research

Advanced metabolomics data processing and analysis for multidimensional analytical techniques and clinical applications

The analysis of the huge amount and complex raw data from metabolomics instruments, requires sophisticated signal and data processing approaches, which usually is an important bottleneck in data analysis. This is even more challenging when developing advanced multidimensional signal processing algorithms, data analysis approaches and advanced statistical concepts.

We work to provide open-source, open-box algorithmic workflow approaches to take humans out of the loop and allow fully automatic processing of raw data into metabolomic information that will be crucial for the secondary goal, which will be to turn all this wealth of metabolomic data into clinically relevant information through Machine Learning algorithms.

Collaborations

• Prof. Santiago Marco
  Signal and information processing for sensing systems group. Institute for Bioengineering of Catalonia (IBEC), Spain

• Prof. Oliver Fiehn
  UC Davis Genome Center
  West Coast Metabolomics Center, Fiehn Lab. University of California, Davis (UC Davis), United States of America

• Dr. Josep Gumà, MD
  Oncology Area Director. Hospital Universitari Sant Joan de Reus. Institut d'Investigació Sanitària Pere Virgili (IISPV), Spain

• Dr. Horacio Saggion
  Large Scale Text Understanding Systems Lab
  Universitat Pompeu Fabra (UPF), Spain

• Dr. Paolo Bonini
  OMICS LIFE LAB
  oloBion, Parc Científic de Barcelona (PCB), Spain

• Dr. Núria Malats, MD
  Genetic & Molecular Epidemiology Group
  Centro Nacional de Investigaciones Oncológicas (CNIO), Spain

• Dr. Esther Molina
  Facultad de Ciencias de la Salud
  Universidad de Granada (UGR), Spain