For my master’s thesis I joined the Max Planck Institute for Chemical Ecology, Jena, Germany, to analyze the transcriptional profiles of diurnally oscillating genes in wild tobacco and to get experience in time series analysis. While my master’s thesis focused on the analysis of transcriptional profiles to answer ecological questions, I switched to the medical field for my PhD by joining the Spanish National Center for Cardiovascular Research, Madrid, Spain, as an early stage researcher, working on the analysis of transcriptome data related to immunology and cardiovascular research in mouse and pig.

The work further manifested my interest in the analysis of transcriptomic data to obtain a deeper understanding of underlying gene regulatory and cell-cell interaction networks. The opportunity to work on large NGS data sets also persuaded me to join the Munich Leukemia Laboratory in 2017, where I’ve been working ever since.

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Especially because RNA sequencing (RNA-Seq) has made it possible to broaden the analytical spectrum to study multiple transcriptional events (e.g. chimeric transcripts, isoform switching, expression, etc.) at once and the multifaceted output can greatly benefit clinical diagnostics. I am interested to use partial deconvolution of transcriptional profiles to identify the contribution of different activation programs, to apply network analysis to identify core transcriptional programs and to perform in silico perturbation experiments, and to apply machine learning techniques for the data integration and classification of patients.

Another integral part of the data analysis process I am interested in is the visualization of the obtained results.  I like the challenge of finding a way to combine various data types to enhance graphical representation of context-dependent, relevant information. Overall, the main research goal is to get the most out of the available data for the benefit of the patients.

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