Author

Sergio Vázquez Montes de Oca

Hospital del Mar Research InstituteORCID 0009-0004-0269-8876Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Cancer Biology· 1 Genetic & Genomic Medicine· 1

Signature Assays, Organisms & Methods

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Organism:human· 3 Assay:bulk RNA-seq· 2 Research Focus:differential expression· 2 Research Focus:benchmarking· 1 Research Focus:drug response / drug discovery· 1 Approach:machine learning (classical)· 1 Approach:optimal transport· 1 Assay:scRNA-seq· 1

Frequent Co-Authors

Ariadna Acedo-TerradesiD· 2 shared Joaquim Bellmunt BiD· 2 shared Júlia Perera‐BeliD· 2 shared Alejandro Ríos-HoyoiD· 1 shared Alejo Rodriguez-VidaiD· 1 shared Cristina CarratoiD· 1 shared Eduardo EyrasiD· 1 shared Eulàlia PuigdecanetiD· 1 shared

Activity by Year

2024-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 37 mutual co-author links

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2 shared papersBioinformatics

Ariadna Acedo-TerradesORCID

Mutual co-authors in cluster

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3 papers

Recent·Most cited

BioinformaticsbioRxivPreprintAug 20, 2026

Cross-Cohort Optimal Transport Maps Macrophage Plasticity and Competing Routes to Inflammation and Fibrosis in Human Atherosclerotic Plaques

Sergio Vazquez Montes de Oca, Ariadna Acedo-Terrades, Jose F Carreno Martinez…·María Rodríguez Martínez

The paper develops a computational framework using optimal transport to analyze macrophage state transitions in atherosclerosis, identifying origin-dependent plasticity mechanisms and shared regulatory circuits in inflammation and fibrosis.

DOI 10.64898/2026.05.15.725379

humanscRNA-seq

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Cancer BiologyNature CommunicationsPeer-reviewedFeb 20, 2025

Predicting immunotherapy response in advanced bladder cancer: a meta-analysis of six independent cohorts

Lilian Marie Boll, Sergio Vázquez Montes de Oca, Marta E. Camarena…·M. Mar Albà

This study identifies factors predicting immunotherapy response in advanced bladder cancer using data from six cohorts.

31 citations

humanbulk RNA-seq

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Genetic & Genomic MedicinemedRxivPreprintJun 28, 2024

Transcriptomics-Driven Machine Learning Models Accurately Predict Chemotherapy Response in Muscle-invasive Bladder Cancer

Ariadna Acedo-Terrades, Alejo Rodriguez-Vida, Oscar Buisán…·Joaquim Bellmunt B

The paper develops a machine learning model using transcriptomic data to predict chemotherapy response in muscle-invasive bladder cancer with high accuracy.

1 citation

humanbulk RNA-seq

𝕏 PostBluesky