RESEARCH
Marçal Vázquez-Valls is a Visiting Student Researcher at the King Abdullah University of Science and Technology (KAUST), specializing in bioinformatics, computational biology, and comparative genomics. His research focuses on understanding epigenetic regulation during hematopoiesis, with a particular interest in the role of linker histones (H1 variants) as modulators of chromatin architecture and gene expression. By integrating single-cell RNA sequencing (scRNA-seq) and differential gene expression (DGE) analyses, he investigates how subtype-specific expression of histone variants influences hematopoietic lineage specification.

Previously, during his tenure at the Institute of Evolutionary Biology (CSIC–Pompeu Fabra University), he conducted large-scale comparative genomics and transcriptomics analyses across diverse animal lineages. His work involved the application of protein language models, functional prediction of uncharacterized proteins, and long-read transcriptome assembly benchmarking. In the field of biotechnology and applied bioinformatics, his internship at HIPRA focused on drug discovery and mutant strain characterization, integrating nucleotide sequence analysis, plasmid design, and functional phenotyping to support therapeutic development.

BIOGRAPHY
Marçal Vázquez-Valls earned his Bachelor of Science in Bioinformatics from Pompeu Fabra University (Barcelona, Spain), where he completed a thesis evaluating clustering algorithms and assembly techniques for de novo transcriptome assembly from long-read sequencing data. He is currently pursuing an Inter-university Master of Science in Health Data Science at Rovira i Virgili University (Tarragona, Spain).

In 2025, he joined the King Abdullah University of Science and Technology (KAUST) as a Visiting Student Researcher, where he investigates the epigenetic roles of linker histones in hematopoietic differentiation. His previous research experiences at the Institute of Evolutionary Biology (CSIC–UPF) and HIPRA equipped him with a strong interdisciplinary background, spanning evolutionary genomics, functional annotation, and computational approaches to drug discovery.