Research group: Stem Cells and Cancer Lab
I graduated in biotechnology, followed by Master’s degree in Bioinformatics and Biostatistics and a PhD in the field of biotechnology and bioinformatics under supervision of Prof. Nicole Borth at University of Natural Resources and Life Sciences, Vienna, Austria. After my PhD, I moved to UK for two years, where I worked as a bioinformatician in a computational biology group at the Institute of Cellular Medicine, Newcastle University, led by Dr. Daniel Rico. We were developing analytical strategies to integrate different layers of information, comparing gene expression and epigenomic data from men and women in immune cells, through the analysis of microarrays, RNA-seq, ChIP-seq and network analysis with R programming. By the end of 2018, I moved to Barcelona, where I worked for few months as a research assistant, giving bioinformatic support to the Stem Cells and Cancer group from IRB, led by Prof. Salvador Aznar. In April 2019, I started PROBIST postdoctoral fellowship and I got integrated into the single cell genomics group from CNAG-CRG, led by Dr. Holger Heyn, where I developed my expertise in single cell data analysis, working in close collaboration with the hospital and analysing different immune cell states in the blood of patients with acute systemic inflammation in different diseases and healthy donors.
My technical skills include programming (highly experienced in R and shell scripting), bioinformatics software and tools, genome analysis and also laboratory techniques. Furthermore, I provide help to undergraduate and PhD students to develop their analytical techniques and I am involved into Diversity and equity activities together with Equity Working Group (EqWG) which aims to promote and support progress towards equity in the Human Cell Atlas. After I have gained extensive research experience at several leading academic institutions in Europe, I am fluent in English and German and Spanish is my native language.
As a computational biologist, part of single cell genomics team, my research focuses on the systematic integration of genomic data from individual cells to characterize the underlying phenotype. As a team, we develop new computational pipelines on High Performance Computing (HPC) clusters, applying statistical and biological knowledge to identify tissue composition, cell type markers and transcriptional dynamics.
I am currently working on the characterization of the spectrum of different immune cell states in the blood of patients with acute systemic inflammation in different diseases and healthy donors. Our research enables the analysis of transcriptomes at single-cell level to investigate about the heterogeneity of the disease at unprecedented resolution by a combination of statistical methods and open-source software specifically designed for single cell data analysis. Deconvolution of cells into subpopulation is crucial to characterise them as cell identity by a specific gene expression program (GEP) and by other activity programs (e.g. cell cycle, immune-response) shared between other cell groups. The conjunction of these transcriptional programs is informative to learn a trajectory analysis to determine if and how the changes elicited by different degrees of the disease are related to each other and map every cell to its pseudo-time along this trajectory, providing new insights to the molecular mechanisms of acute systemic inflammatory events.