Author

Xavier Correig

Centro de Investigación Biomédica en Red Diabetes y Enfermedades Metabólicas AsociadasORCID 0000-0002-6902-3054Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 3 Bioengineering· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 2 Research Focus:imputation· 2 Assay:metabolomics· 2 Research Focus:benchmarking· 1 Assay:imaging· 1 Approach:machine learning (classical)· 1 Assay:metagenomics· 1 Organism:mouse· 1

Frequent Co-Authors

María García‐AltaresiD· 3 shared Pere RàfolsiD· 3 shared Gerard BaqueriD· 2 shared Lluc SementéiD· 2 shared Bram HeijsiD· 1 shared Carsten HopfiD· 1 shared Cristina Gomez Serna· 1 shared Daniel CañuetoiD· 1 shared

Activity by Year

2018-2025 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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3 shared papersBioinformatics

María García‐AltaresORCID

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4 papers

Recent·Most cited

Improving MALDI Mass Spectrometry Imaging Performance: Low-Temperature Thermal Evaporation for Controlled Matrix Deposition and Improved Image Quality

Toufik Mahamdi, Cristina Gomez Serna, Roger Giné, Jordi Rofes, Shad A. Mohammed, Pere Ràfols, Xavier Correig, María García‐Altares, Carsten Hopf, Stefania Alexandra Iakab, Óscar Yanes

This paper introduces low-temperature thermal evaporation (LTE) for matrix deposition in MALDI-MSI, showing improved image quality, purity, and stability compared to traditional methods.

Journal of the American Society for Mass Spectrometry · Apr 18, 2025Peer-reviewedBioengineering

Discovering Matrix Adducts for Enhanced Metabolite Profiling with Stable Isotope-Labeled MALDI-MSI

Gerard Baquer, Miguel Bernús, Lluc Sementé, René J. M. van Zeijl, María García‐Altares, Bram Heijs, Omar Boutureira, Xavier Correig, Pere Ràfols

This study introduces a workflow using isotopic labeling to identify and remove matrix adducts in MALDI-MSI, improving metabolite annotation and tissue morphology interpretation.

bioRxiv · Jun 28, 2023 · PreprintBioinformatics

rMSIcleanup: An open-source tool for matrix-related peak annotation in mass spectrometry imaging and its application to silver-assisted laser desorption/ionization

Gerard Baquer, Lluc Sementé, María García‐Altares, Young‐Jin Lee, Pierre Chaurand, Xavier Correig, Pere Ràfols

rMSIcleanup annotates and removes matrix-related peaks in MSI data, improving post-processing by reducing redundant signals.

Journal of Cheminformatics · Jul 22, 2020Peer-reviewedBioinformatics

Maximizing the quality of NMR automatic metabolite profiling by a machine learning based prediction of signal parameters

Daniel Cañueto, Miriam Navarro, Mònica Bulló, Xavier Correig, Nicolau Cañellas

This study improves NMR automatic metabolite profiling by using machine learning to predict signal parameters, reducing uncertainty and enhancing profiling quality.

bioRxiv · Nov 8, 2018 · PreprintBioinformatics