Author

Quim Aguado-Puig

Universitat Autònoma de BarcelonaORCID 0000-0003-4871-3192Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 4

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Assay:whole-genome sequencing· 3 Research Focus:benchmarking· 2 Approach:experimental assay· 2 Research Focus:software / tool· 2 Assay:DNA methylation· 1 Research Focus:imputation· 1 Assay:long-read sequencing· 1

Frequent Co-Authors

Miquel MoretóiD· 4 shared Santiago Marco‐SolaiD· 4 shared Cristian IñigueziD· 2 shared Max DoblasiD· 2 shared Albert Jiménez-BlancoiD· 1 shared Alejandro Alonso-MaríniD· 1 shared Antonio Espinosa· 1 shared Christos Matzoros· 1 shared

Activity by Year

2022-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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4 shared papersBioinformatics

Miquel MoretóORCID

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4 papers

Recent·Most cited

Singletrack: An Algorithm for Improving Memory Consumption and Performance of Gap-Affine Sequence Alignment

Lorién López‐Villellas, Cristian Iñiguez, Albert Jiménez-Blanco, Quim Aguado-Puig, Miquel Moretó, Jesús Alastruey-Benedé, Pablo Ibáñez, Santiago Marco‐Sola

Singletrack improves memory efficiency and performance for gap-affine sequence alignment without sacrificing accuracy.

Bioinformatics · Apr 10, 2026Peer-reviewedBioinformatics

QuickEd: High-performance exact sequence alignment based on bound-and-align

Max Doblas, Oscar Lostes-Cazorla, Quim Aguado-Puig, Cristian Iñiguez, Miquel Moretó, Santiago Marco‐Sola

QuickEd improves sequence alignment speed for long reads by using a bound-and-align strategy, achieving faster performance than existing tools while maintaining accuracy.

Bioinformatics · Mar 1, 2025Peer-reviewedBioinformatics

BIMSA: Accelerating Long Sequence Alignment Using Processing-In-Memory

Alejandro Alonso-Marín, Ivan Fernandez, Quim Aguado-Puig, Juan Gómez-Luna, Santiago Marco‐Sola, Onur Mutlu, Miquel Moretó

BIMSA accelerates long sequence alignment using Processing-In-Memory, achieving significant speedups over existing PIM and CPU implementations.

Bioinformatics · Oct 17, 2024Peer-reviewedBioinformatics

WFA-GPU: Gap-affine pairwise alignment using GPUs

Quim Aguado-Puig, Max Doblas, Christos Matzoros, Antonio Espinosa, Juan Carlos Moure, Santiago Marco‐Sola, Miquel Moretó

This paper introduces WFA-GPU, a GPU-accelerated tool for exact gap-affine sequence alignment, showing significant speed improvements over CPU and other GPU implementations.

bioRxiv · Apr 18, 2022 · PreprintBioinformatics