Senior Principal Investigator: Beatriz Roson

We are dedicated to applying computational tools on single-cell and other omic-based sequencing data to answer questions regarding the biology of female reproductive organs. Our main aim is to model different biological processes (such as regeneration, niche interactions, or tumor formation) to contribute to an understanding of the uterus under healthy and pathological conditions.

The team builds project-tailored pipelines and uses machine learning algorithms to solve questions such as the description of new cell populations and cell states, identification of changes in cell abundances, determination of differentiation trajectories and progenitor populations, characterization of cell-to-cell molecular networks, the discovery of disease biomarkers for early onset prediction, screening of new drug targets, or potential repurposing of pre-existing drugs.

To learn more about what we do and access our main publications, visit

The Uterus from a Systems Biology and Artificial Intelligence Perspective