Description
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.
Description
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.
Team members
Beatriz Roson is a leading biodata scientist interested in untangling the complexity of biological processes such as homeostasis, regeneration, and microenvironmental interactions.
Dr. Roson completed her M.Sc. program in Cellular and Molecular Biology at IE University (Segovia, Spain) with an Excellence Studentship Award, followed by a Marie Curie-funded research training program at the European Bioinformatics Institute (EMBL-EBI) (Cambridge, UK). She then conducted her Ph.D. studies (2009-2015) at the crossroads of genomics and cell therapy at the Cancer Research Institute of Salamanca (Spain), publishing the most comprehensive transcriptomic signature of human mesenchymal stem cells. Her thesis received the University’s Extraordinary Prize distinction. At this stage, she became particularly interested in single-cell sequencing technology and enrolled in a post-doctoral program at the Karolinska Institute (Sweden) where she expanded her knowledge of cellular and tissue heterogeneity, focusing on human adipose tissues, their regeneration pathways, and their alterations in obesity and type II diabetes.
She recently gained broad experience in applying bioinformatics in different scenarios: the deployment of single-cell analysis supported by the Swedish Bioinformatics Service (SciLife-Lab), involvement in a genomics unit for precision medicine at IIS La Fe, and hosting the single-cell analysis of the HUTER project (https://www.huter-hca.eu/).
Dr. Roson recently joined the Carlos Simon Foundation as an emergent principal investigtor, to provide the institute with cutting-edge methods for processing, modeling and integrating largescale multiomics data.
ResearcherID: ABA-6235-2021
Diego Amoros
Senior Bioinformatician
Irene Perez
Data Scientist
Raul Perez
Doctoral Researcher
Jaime Llera
Bioinformatician
Esther Tercero
Biostatistics
Yolanda Castello
Bioinformatician
Main Publications
Single-cell RNA sequencing of SARS-CoV-2 cell entry factors in the preconceptional human endometrium
Vilella F, Wang W, Moreno I, Roson B, Quake SR, Simon C.
Hum Reprod. 2021 Sep 18;36(10):2709-2719.
https://doi.org/10.1093/humrep/deab183.
PMID: 34329437; PMCID: PMC8385818.