Guillermo Serrano

This study uses single-cell multiomics to analyze CAR T cell dynamics in multiple myeloma, identifying regulatory mechanisms affecting persistence and dysfunction.

This study develops patient-derived liver biopsy organoids to model alcohol-associated liver disease and identifies disease-specific features and therapeutic responses.

JIND-Multi improves cell annotation in single-cell RNA and ATAC data by transferring labels across multiple datasets, reducing unclassified cells and maintaining accuracy.

This study uses scRNA-seq to analyze del(5q) MDS patients, revealing shared and unique transcriptional alterations and lenalidomide's impact on disease and treatment response.

GeNNius uses a graph neural network to predict drug-target interactions more efficiently and accurately than existing methods across multiple datasets.

The paper uses single-cell transcriptomics to show how genetic variants influence gene regulatory networks in honeybee brains, affecting aggression-related behaviors through specific cell populations and pathways.

This study uses single-cell RNA sequencing to analyze changes in hematopoietic stem and progenitor cells during aging and myeloid malignancies, identifying altered gene expression and regulatory networks.

JIND improves automated cell-type annotation in single-cell RNA-seq by learning a latent space for reliable classification and batch alignment without retraining.

The paper introduces SimiC, a method for inferring gene regulatory networks per cell phenotype and comparing them across conditions, revealing regulatory dynamics missed by single GRN approaches.