RESEARCH
Daniel’s research explores the epigenetic regulation of hematopoiesis, with a particular focus on linker histones (H1). Using single-cell RNA sequencing (scRNA-seq) data from human bone marrow, he investigates hematopoietic stem and progenitor cell populations. His approach combines transcriptomic analysis, computational modeling, and machine learning to assess how H1 variants and their associated regulatory networks relate to cell identity and differentiation.

BIOGRAPHY
Daniel Soto obtained his bachelor’s degree in Biology from Universidad del Valle, Colombia, where he focused on developing qPCR protocols for detecting bacteria in pharmaceutical products. Motivated by a growing interest in bioinformatics, he pursued training in metagenomics and later enrolled in the M.Sc. in Bioscience program at King Abdullah University of Science and Technology (KAUST). There, he joined Prof. David Gomez-Cabrero’s AI4BioMed Lab, where he applies computational and statistical methods to study single-cell transcriptomics, with a focus on hematopoietic systems and chromatin dynamics. His work integrates machine learning and scRNA-seq analysis to investigate gene regulation and cellular identity.