Author

Roger Guimerà

Institució Catalana de Recerca i Estudis AvançatsORCID 0000-0002-3597-4310Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Approach:deep learning· 2 Organism:human· 2 Assay:metabolomics· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:protein structure prediction· 1

Frequent Co-Authors

Alexandra JunzaiD· 2 shared Josep M. BadiaiD· 2 shared Maribel Pérez-Ribera· 2 shared Marta Sales‐PardoiD· 2 shared Muhammad Faizan-KhaniD· 2 shared Óscar YanesiD· 2 shared Roger GinéiD· 2 shared Abubaker PataniD· 1 shared

Activity by Year

2025-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersBioinformatics

Alexandra JunzaORCID

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Author profile →

2 papers

Recent·Most cited

ChemEmbed: A deep learning framework for metabolite identification using enhanced MS/MS data and multidimensional molecular embeddings

Muhammad Faizan-Khan, Roger Giné, Josep M. Badia, Maribel Pérez-Ribera, Manuel Ruíz-Botella, Alexandra Junza, Jordi Capellades, Iván Pérez-López, Shipei Xing, Abubaker Patan, Laura Brugnara, Anna Novials, Joan‐Marc Servitja, María Vinaixa, Pieter C. Dorrestein, , Óscar Yanes

ChemEmbed improves metabolite identification by combining enhanced MS/MS data with multidimensional molecular embeddings, achieving high accuracy in benchmark tests.

Briefings in Bioinformatics · Jan 1, 2026Peer-reviewedBioinformatics

SingleFrag: A deep learning tool for MS/MS fragment and spectral prediction and metabolite annotation

Maribel Pérez-Ribera, Muhammad Faizan-Khan, Roger Giné, Josep M. Badia, Alexandra Junza, Óscar Yanes, Marta Sales‐Pardo, Roger Guimerà

SingleFrag predicts MS/MS fragments and annotates metabolites using deep learning, outperforming existing tools and identifying three unknown compounds in human samples.

Briefings in Bioinformatics · Jul 1, 2025Peer-reviewedBioinformatics